INTERNATIONAL JOURNAL OF INNOVATIVE … JOURNAL OF INNOVATIVE RESEARCH IN ADVANCED ENGINEERING...

INTERNATIONAL JOURNAL OF INNOVATIVE

RESEARCH IN ADVANCED ENGINEERING

Volume 3, Issue 01 of January 2016 ISSN: 2349-2763

A Monthly Journal of Advanced Engineering

Index Copernicus 2014= 6.57 (IC Value)

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IJIRAE Editorial Board Editor – Chief Dr.A.Arul L.S., (International Journal of Innovative Research in Advanced Engineering) Editorial Board Member Dr.Abdel-Badeh M Salem, Ph.D., Ain Shams University, Egypt Dr. Ali Ahmed, Ph.D., Monash University (Sunway Campus), Malaysia Dr. Dana Prochazkova, Ph.D., Czech Technical University, Czech Republic Dr.Hyo Jong Lee, Ph.D., Chonbuk National University, South Korea Dr. Jose Maria de Fuentes, Ph.D., Univ. Carlos III, Spain Dr.M. A. Siddiqui, Ph.D., Najran University, Saudi Arabia Dr. Mincheol Kim, Ph.D., Jeju National University, South Korea Dr. Mohamad Kamal Bin A. Rahim, Ph.D., Universiti Teknologi Malaysia, Malaysia Dr. Mohd Zaidi Abdul Rozan, Ph.D., Universiti Teknologi Malaysia, Malaysia Dr. Ramakrishnan Sundaram, Ph.D., Gannon University, USA Dr.Shyamala C. Doraisamy, Ph.D., University Putra Malaysia, Malaysia Dr. Steven Guan, Ph.D.,Xi’an Jiaotong-Liverpool University, China Dr. Afzaal H. Seyal, Ph.D., Institut Teknologi Brunei, Brunei Darussalam Dr. Chen Zhi Yuan, Ph.D., University of Nottingham, Malaysia Dr. Frans A. Henskens, Ph.D., University of Newcastle, Australia Dr. Inas Khayal, Ph.D., Masdar Institute of Science and Technology, UAE Dr.Lakshmi Prayaga, Ph.D., University of West Florida, USA Dr. Marenglen Biba, Ph.D., University of New York in Tirana, Albania Dr. Md Mahmud Hasan, Ph.D., Kazakh-British Technical University – Kazakhstan Dr. Mohammad Nazir Ahmad, Ph.D.,Universiti Teknologi Malaysia, Malaysia Dr. Peng Guan, Ph.D., Brown University, USA Dr. Rukshan I. Athauda, Ph.D., The University of Newcastle, Australia Dr. Steve Reames, Ph.D., A’Sharqiyah University, Oman Dr. Yunkai Liu, Ph.D., Gannon University, USA

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Dr. Jammi Ashok, Professor, Guru Nanak Institute of Technology,Hyderabad,INDIA Prof.Mohammad Jannati, Faculty of Electrical Engineering, Universiti Teknologi, MALAYSIA Prof. Anbu Kumar.S,Associate Professor, Dept. Of Civil Engg., Delhi Technological University, Delhi,INDIA Prof. Appasami.G., Associate Professor, Dr. Pauls Engineering College, Villupuram, Tamilnadu,INDIA Prof. Chandrashekhar Shankar Shinde, Dr. J. J. Magdum College of Engineering, Jaysingpur, INDIA Prof. Komarasamy G.,Assistant Professor, Bannari Amman Institute of Technology,Tamil Nadu,INDIA Prof.Kamal Kulshreshtha,Associate Prof, Modi Institute of Management & Technology, Kota,INDIA Prof.Vivek Kumar Srivastava, Assistant Professor,Faculty of Engg,R.B.S.College,Bichpuri,Agra,INDIA Prof.Anand Nayyar, AP, Dept of CA & IT,KCL Institute of Management and Technology, Jaland,,INDIA Prof. Chittaranjan Pradhan, AP, School of Computer Engineering, KIIT University, Odisha, ,INDIA Dr. Sohail Ayub, Assoc Professor, Dept of Civil, Z. H. College, Faculty of Engg. & Technology, Aligarh Prof. Zairi Ismael Rizman,Faculty of Electrical Engineering,Universiti Teknologi MARA,MALAYSIA Prof.Jaymin R. Desai, Professor,Government Polytechnic, Valsad, Gujarat,INDIA Prof.Naveen Kolla, Assistant Professor, Geetanjali Institute of Science and Technology, Nellore,INDIA Dr.K.R.Ananthapadmanaban, Assoc.Prof,Dept of CS, SRM Arts and Science College, Chennai,INDIA Dr.Ramalingam Shanmugam, Professor,Texas State University, San Marcos, TX 78666, USA Prof. Hemakumar Gopal, AP & Head,Dept of CS,Govt. College for Women, Mandya,INDIA Dr. Mohamed, UniversityConstantine,Faculty of Sciences,Constantine,ALGERIA Dr Sobhana N V, Professor, Department of Computer Science & Engineering, NIT Calicut,INDIA Dr. S.Kishore Reddy,Assoc. Prof, Adama science & Technology University, Adama, Ethiopia Dr. Abhinav Sharma,Assistant Professor in Govt. R.R. PG College, Alwar (Raj.),INDIA Dr.Mukesh Thakur, Reader, Rungta College of Engineering & Technology, Raipur, Chhattisgarh Dr.L.M.Karthikeyan,Asst Prof/ Dept of Aeronautical Engineering,Techno Global University,INDIA Dr. D. Prince Winston, Assoc.Prof / EEE, Kamaraj College of Engineering, Virudhunagar,INDIA Dr. Ramachandra C G,Professor& Head/Mech ,Srinivas Institute of Technology, Mangalore,INDIA Prof. Leila Bendifallah, Associate Professor, University of Boumerdes, ALGERIA Prof. Amod Shrotri, Assoc.Prof / Mech, PVP Institute of Technology, Budhgaon Prof. Anand Nayyar, Raman Enclave Extension, Ludhiana, INDIA Prof.Sharmila N. Rathod, Rajiv Gandhi Institute of Technology,Versova, Andheri,INDIA Prof. Anuradha Bhatia, Head, Dept of CS, VES Polytechnic, Chembur, Mumbai,INDIA Prof. R.Kavin,Asst Prof, Excel College Of Engineering & Technology, INDIA Prof. S.Balamurugan , Asst.Prof, Kalaignar Karunanidhi Institute of Technology, India. Prof.Patel DipalKumar,Assistant professor, Charotar University of Science & Technology, India Dr.B.Venkateswarlu, Senior Assistant Prof, School of Advanced Sciences, V.I.T University, Vellore,India Dr.RamaChandra C G, Head, Dept of Marine Engineering, Srinivas Institute of Technology, Mangalore Dr.P.Ezhilarasu, Associate Professor, Dept of CSE, Hindusthan College of Engg & Tech, Coimbatore,India Dr.D.M.Mate, Professor/Mechanical Engineering, Dr.D.Y. Patil Institute of Engg & Tech., Ambi, Pune, India Dr.V.N.Srinivasa Rao Repalle, Professor, Nalanda Institute of Engineering & Tech, Kantepudi, A.P, India Prof. Saurabh Sanjay Joshi, Assistant Prof, KIT‘s College of Engineering, Kolhapur Prof. Abhijith Augustine, Assistant Prof/ EEE, MET’S School of Engineering, Mala-680735, Thrissur, Kerala,

S.No

IJIRAE:: Volume 3, Issue 01 of January 2016 Issue Title & Authors Details

Paper ID

01

Barriers to Implement Lean Principles in the Indian Construction Industry

Authors: S M Abdul Mannan Hussain , Apoorva Mercy Nama , Asra Fatima

JAAE10082

02

Towards an Arbitrage Analysis of Optimization Speculation

Author: Kalyana Kumar. S

JAAE10085

03

Studies on Stabilized MUD Block as a construction material

Authors: Vinu Prakash , Amal Raj , Aravind S , Basil Mathew , Sumith V R

JAAE10087

04

Approaches and models of professional competence: Definition of competence in the training of engineers in Latin America

Authors: Martín Palma , Dante Guerrero , Ignacio de los Ríos Carmenado

JAAE10086

05

Study of the Effect of Length and Inclination of Tube settler on the Effluent Quality

Authors: Kshitija Balwan, Aarju mujawar, Dhanashri Bhabuje, Manisha karake

JAAE10091

06

Power Quality Improvement Using GUPFC

Authors: Rajesh Reddy, R.Veera Sudarasana Reddy

JAAE10080

07

Dynamically Partitioning Big Data Using Virtual Machine Mapping

Authors: D.Saritha , R.Veera Sudarasana Reddy , G.Narasimha Reddy

JAAE10081

08

Improving the Performance of Mapping based on Availability Alert Algorithm Using Poisson Arrival for Heterogeneous Systems in Multicore Systems

Authors: Sheshappa S.N,G. Appa Rao, K V Ramakrishnan

JAAE10092

09

Performance Study of Silicone Rubber Polymer was Filled Fly Ash as Insulator Material on High Voltage Transmission Tower

Authors: Ikhlas Kitta , Salama Manjang ,Wihardi Tjaronge, Rita Irmawaty

JAAE10093

International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2763 Issue 01, Volume 3 (January 2016) www.ijirae.com

__________________________________________________________________________________________________ IJIRAE: Impact Factor Value - ISRAJIF: 1.857 | PIF: 2.469 | Jour Info: 4.085 | Index Copernicus 2014 = 6.57 © 2014- 16, IJIRAE- All Rights Reserved Page -1

Barriers to Implement Lean Principles in the Indian Construction Industry

S M Abdul Mannan Hussain1 Apoorva Mercy Nama2 Asra Fatima3

Research Scholar, GITAM University,Hyd B.Tech Final Year Student Research Scholar, GITAM University Assistant Professor ,Dept. of Civil Engg Malla Reddy Engineering College Assistant Professor, Civil Eng. Dept

Malla Reddy Engineering College Department of Civil Engineering Muffakham Jah Engineering College Autonomous Campus, Secundrabad. Autonomous Campus, Secundrabad Banjara Hills, Hyderabad

Abstract— Lean construction emerged from attempts of transferring and applying the Japanese Lean production philosophy to the construction industry. Lean construction is a confluence of ideas including continuous improvement, flattened organization structure, efficient usage of resources, elimination of waste, and cooperative supply chain. Based on the success of Lean Production in manufacturing and the development of Lean Construction in countries such as Brazil, Denmark and the USA, the application of Lean Construction is currently debated in India. The aim of the study is identification of barriers to successful implementation of lean construction in the Indian construction sector. The data was collected by questionnaire survey of project managers of building construction organizations and senior consultants of architectural and project management firms. The data collected was then analyzed to rank the main barriers and lean principles are suggested to overcome these barriers

Keywords—Lean construction; waste; barriers; management; project

INTRODUCTION Toyota was the first to bring the Lean principles into limelight. Toyota created a focus on eliminating waste and grew to be the world’s largest automotive industry by adopting seven principles of reducing waste. It believed in preserving value with less work and also improvement in efficiency by improving the workflow. Today Lean manufacturing is practiced by many leading auto makers.

Lean principles have slowly made inroads into the construction industry because of its approach to waste elimination and providing value with less effort and time. Construction management is defined as the judicious allocation of resources to finish a project on time, at budget and at desired quality [1]. The biggest cost impact of the construction today is the way the whole process is managed and not the cost of labor and materials. Construction process consists of countless activities that add no value to the product. According to Hines and Rich, these non value adding activities (e.g. waiting time ,double handling, searching for material etc) are pure waste and should be eliminated completely [2]. In a study conducted by Josephson and Saukkorippi, a group of workers were followed around for 22 working days and it was noted that 33.4% of their time was waste [3].

I. NEED FOR STUDY

India‘s rapid economic growth over the past few decades has placed a tremendous stress on its limited infrastructure. Construction industry is one of the largest industries which support the economy of a country. Since construction has a major and direct influence on many other industries reducing waste in construction can go a long way in helping the economy of the world.

II. LITERATURE REVIEW Existing data and literature on lean principles and its applications in construction industry around the world was collected. This formed the reference for framing the questionnaire for survey.

A. Lean construction According to Chick G. et al, waste is more than the physical wastes that are the focus of construction site activity [4].

In fact waste is any activity (or inactivity) that does not add value to the product or service. Waste can be

Value-adding (VA): is the work that the customer is willing to pay for. Essential non-value adding: these are the tasks that must be completed to enable the value-adding activity to be

completed, but do not add value. For example, inspection is not that the customer pays for but is necessary. Waste: Waste can be of two types. Waste in the work itself (e.g. excessive walking, looking for tools and

materials, poor quality). Introduced or enforced‘waste (e.g. waiting for information, materials not supplied), which has prevented work activity from being carried out.



According to Koskela and Howell, Lean Construction is a way to design to minimize waste of materials, time, and effort in order to generate the maximum possible amount of value [5] According to Dulaimi and Tanamas, managing construction under lean construction is different from typical contemporary practice [6] because it:

Has a clear set of objectives for the delivery process Is aimed at maximizing performance for the customer at the project level Designs concurrently product and process Applies production control throughout the life of the project

B. Lean principles Womack and Jones describe Lean thinking as a cycle of five guiding principles where the implementation of the first

four lead to achieving the fifth [7]. The ultimate goal is the elimination of waste. The principles are described below: Specify value

Only what the customer considers as value should be taken into consideration, ―nothing more, and nothing less”. In construction activities can be classified as 3 types: 1. Value Adding (VA) 2. Non-value Adding (NVA) 3. Necessary Waste (NW)

Identify the value stream

This is about identifying all the steps in the value stream in order to determine activities that do not add value and seek for their elimination.

Make value flow without interruption This is done by minimizing delays, inventories, defects and downtime.

Use pull logistics All components and information are made and supplied at the necessary time to deliver the product or service to the customer at exactly the time the customer wants it.

Pursue perfection Lean consists of continuously improving through collaboratively identifying and removing wastes to provide the desired results.

C. Lean Project Delivery System (LPDS)

According to Ballard, the Lean Project Delivery System (LPDS) [8] consists of the following phases: project definition lean design lean supply lean assembly Use

Essential features of LPDS include:

the project is structured and managed as a value generating process downstream stakeholders are involved in front end planning and design through cross functional teams project control has the job of execution as opposed to reliance on after-the-fact variance detection optimization efforts are focused on making work flow reliable as opposed to improving productivity pull techniques are used to govern the flow of materials and information through networks of cooperating

specialists feedback loops are incorporated at every level, dedicated to rapid system adjustment; i.e., learning.



IV. METHODOLOGY The main tool for the collection of data includes questionnaires. The target population for the data collection

includes project managers of building construction organizations.

Review existing Literature Preparation of Questionnaire Questionnaire survey Analysis of data

Conclusions, Recommendations and

Suggestions

Fig. 1 Proposed methodology for the project

The questionnaire was uploaded to Google drive in the form of Google docs so that the survey details could be collected online. The questionnaire was circulated as a link to the architects, civil engineers and project managers of construction firms through emails. The questionnaire was circulated to about 50 companies. The representatives were to fill the questionnaire and submit the data online. The questionnaire when submitted collects the data in an excel sheet real- time in the Google drive database.

V. RESULTS AND DISCUSSIONS To identify the barriers for successful implementation of lean construction, a questionnaire was prepared after thorough literature study of barriers faced in other countries. Table 1 lists out the mean score of various barriers to implementation of lean principles in India. The main barriers to applying Lean principles in Construction industry in India have been identified as

Lack of exposure on the need to adopt lean construction Uncertainty in the supply chain The tendency to apply traditional management Culture & human attitudinal issues (Mindset issues) Lack of commitment from top management Non-participative management style for workforce



Fig. 2 Barriers To Implementation Of Lean Principles In India

TABLE 1. MEAN SCORE OF BARRIERS TO IMPLEMENTATION OF LEAN PRINCIPLES IN INDIA

`BARRIERS TO IMPLEMENTATION OF LEAN PRINCIPLES IN INDIA MEAN SCORE Lack of exposure on the need for lean Construction 3.88 Uncertainty in the supply chain 3.85 The tendency to apply traditional management 3.75 Culture & human attitudinal issues (Mindset issues) 3.70 Lack of commitment from top management 3.55 Non-participative management style for workforce 3.52 Attitude and ability to work in group 3.42 Difficulties in understanding the concept of lean construction 3.42 Lack of client and supplier involvement 3.33 Fragmentation and subcontracting 3.18 Lack of proper training 3.12

Lean construction principles are still a new concept in Indian construction sector. The benefits of lean construction has been recognized by some of the leading construction firms like Larsen and Toubro, Tata Realty & Infrastructure, Shapoorji Pallonji & Co., GMR Group and other such organizations, but it is yet to percolate down to the medium and smaller construction firms. ―Lack of exposure on the benefits of adopting Lean constructionǁ is one of the main barriers identified in the survey. The next important barrier identified in the survey is the Uncertainty in the supply chainǁ. The Lean Construction principles stress on waste minimization. This can be achieved through maintaining the right inventory; there should be no over-ordering or under-ordering of materials. Lean principles also stress on just-in-time supply. This does minimize waste but the risk involved is also high. Therefore the uncertainties in the supply chain can prove to be a big risk and a barrier which can prevent the practitioners from adopting the Lean principles.



The third barrier identified is the ―Human attitudinal issues and cultural mindsetǁ and the tendency to apply the traditional concepts of project management. Human beings are people of habits and there is a general tendency to resist change. Construction industry is a huge and old industry. People are used to and are comfortable with the traditional style of management and so do not want to disturb what is already working. But with the construction sector on the boom and resources depleting at a fast pace, it is high time that the construction industry which has a big role in waste generation and environment pollution, changes and adopts principles which will result in waste minimization and prevention of environment pollution. Lack of commitment from the top management and the Non-participative style of managementǁ is also a barrier in implementing Lean concepts in construction. Indian construction industry is used to working as a bureaucratic style of management, where orders are given by the managers and they are executed by the workers. Managers are resistant to change, as they feel that workers would not work properly if they are included in the decision making process. Previously workers in the construction sector were illiterate and learnt on the job, but with technological advances in construction, at present the workforce consists of engineers and other educated and experienced personnel, who if given responsibility, will be motivated and assume responsibility to provide better and faster results.

VI. CONCLUSION AND RECOMMENDATION

Most of the respondents who have not heard about lean management principles are from the public sector executing huge projects along with big firms. Though the big firms are using lean principles, people from the government sector should also be educated about the savings due to adopting lean principles, so that they can mandate it on all government sponsored projects. Individual practitioners can also be made aware of lean concepts by workshops, conferences, journals, and business magazines. Lack of exposure on the need to adopt lean construction can be overcome by communicating the benefits of Lean construction through seminars and conferences to the construction practitioners. Also the government should enact policies which appreciate the effort by firms which adopt Lean principles. Recommendation is to take companywide initiative to apply Lean principles and it is not enough to send a few managers or personnel for workshops and seminars. This way of working should eventually percolate to the lower levels. The sub contractors and suppliers should also be made to attend these workshops and take initiatives to implement Lean management principles. Barriers in uncertainty in the supply chain can be overcome by choosing proper suppliers who not quote less price, but deliver good quality and who also have a proven track record. By working closely with suppliers and subcontractors, problematic issues can be minimized by participative style of managing projects and establishing strategic alliances with them. This can be done effectively if one works with the same supplier again and again

There is a tendency to apply traditional management principles. People generally do not want to disturb processes which have been going on since a long time, but now with so much construction boom, it is high time the construction industry gives cognizance to the fact that waste produced by industry is high and needs to be minimized. This can be achieved by training all managers and workers in the firm on the benefits of Lean construction. Workshops on the comparisons on Lean and traditional methods of construction, and how Lean is better should be conducted. Suitable metrics should be developed so that practitioners apply Lean management principles.

Managers should promote lean construction, as it can bring considerable revenue savings for the firm. Managers should change with times and new technology. This can be done by bringing about a change in organization culture by making the adoption of lean principles mandatory, by enacting new policies for waste minimization, and by partnering with suppliers and subcontractors to ensure that they follow Lean construction methods.

ACKNOWLEDGMENT The authors record their appreciation for the time and effort taken by the project managers to complete the questionnaire survey, in spite of their hectic schedule.

REFERENCES

[1]. Clough, R.H. & Sears, G.A. (1994) Construction Contracting. (6th edition) John Wiley & Sons Inc., New York. [2]. Hines, P., Jones, D. and Rich, N. (1998), Lean Logistics, Pergamon, London. [3]. Josephson, P-E., and Saukkoriipi, L. (2005). Waste in construction projects. Call for a new approach. Report

0507. The centre for Management of the Built Environment, Building Economics and Management, Chalmers University of Technology, Gøteborg.

[4]. Chick, G., Corfe, C., Dave, B., Fraser, N., Kiviniemi, A., Koskela, L., [5]. O‘Connor, R., Owen, R., Smith, S., Swain, B. and Patricia



[6]. Tzortzopoulous (2013), Implementing lean in construction, CIRIA, London, United Kingdom. [7]. Koskela, L., Ballard, G., Howell, G., and Iris D. Tommelein (2002), [8]. ‗The foundations of lean construction‘, Design and construction: building in value, Butterworth Heinemann,

Oxford, UK, pp. 211-226. [9]. Dulaimi, M. F., and Tanamas, C. (2001), ‗The principles and application of lean construction in Singapore‘,

Proceedings of the 9th Annual [10]. Conference of the International Group for Lean Construction, Singapore. [11]. Womack, J. P. and Jones, D. T. (1996), Lean Thinking: Banish waste and create wealth in your corporation,

Simon and Schuster, New York, USA. [12]. Ballard, G. (2000), Lean Project Delivery System, LCI White Paper – 8, Lean Construction Institute.


________________________________________________________________________________________________________ IJIRAE: Impact Factor Value - ISRAJIF: 1.857 | PIF: 2.469 | Jour Info: 4.085 | Index Copernicus 2014 = 6.57

© 2014- 16, IJIRAE- All Rights Reserved Page -7

Towards an Arbitrage Analysis of Optimization Speculation

Dr.Kalyana Kumar. S Professor & Head, Department of Mathematics,

Dr.T.Thimmaiah Institute of Technology, Kolar Gold Fields- 563 120, Karnataka., India

INTRODUCTION: FINDING THE MARKETS IN THE MATH

One of the fundamental insights of mainstream neoclassical economics is the connection between competitive market prices and the Lagrange multipliers of optimization theory in mathematics. Yet this insight has not been well developed. In the standard theory of markets, competitive prices result from the equilibrium of supply and demand. But in a constrained optimization problem, there seems to be no mathematical version of supply and demand functions so that the Lagrange multipliers could be seen as equilibrium prices. How can one "Find the markets in the math" so that Lagrange multipliers will emerge as equilibrium market prices? We argue that the solution to the "Finding the markets in the math" problem is to reconceptualize equilibrium as the absence of profitable arbitrage instead of the equating of supply and demand. With each proposed solution to a classical constrained optimization problem, there is an associated market. The maximand is one commodity, and each constraint provides another commodity on this market. Given a marginal variation in one commodity, one can define the marginal change is any other given commodity so the market has a set of exchange rates between the commodities. The usual necessary conditions for the proposed solution to solve the maximization problem are the same as the conditions for this mathematically defined "market" to be arbitrage-free. The prices that emerge from the arbitrage-free system of exchange rates (normalized with the maximand as numeraire) are precisely the Lagrange multipliers. We also show the cofactors of a matrix describing the marginal variations can be taken as the prices (before being normalized) so the Lagrange multipliers can always be presented as ratios of cofactors. Starting with any square m m matrix (with rank m–1), a market can also be defined and the cofactors given a price interpretation so that an economic interpretation can be constructed for the inverse matrix and for Cramer's Rule.

The relevant mathematical result, which dates back to Augustin Cournot in 1838, is that:there exists a system of prices for the commodities such that the given exchange rates are the price ratios if and only if the exchange rates are arbitrage-free (in the sense that they multiply to one around any circle). This simple graph-theoretic theorem is known in its additive version as Kirchhoff's Voltage Law (KVL): there exists a system of potentials at the nodes of a circuit such that the voltages on the wires between the nodes are the potential differences if and only if the voltages sum to zero around any cycle. Kirchhoff's work was published in 1847, so it might be called "the Cournot-Kirchhoff law." There is also an additive version of the additive KVL. If two commodities are swapped, one unit for one unit, then usually some additional "boot" must be paid for the higher valued commodity. For each pair of goods i and j, suppose we are given an amount boot(i,j) that is the additional cash boot that needs to be paid along with one unit of good i in order to receive one unit of good j.

Then KVL takes the form: Given a system of boots for commodity swaps, there exists a set of unit prices for the goods such that the boot necessary for an exchange of units is the price difference if and only if the system of boots is arbitrage-free in the sense of summing to zero around any circle. We show that this Cournot-Kirchhoff law has many applications outside of electrical circuit theory and economics. For instance, the second law of thermodynamics can be formulated as the impossibility of a certain form of "heat arbitrage" between temperature reservoirs, and the "prices" that emerge in this case are the Kelvin absolute temperatures of the reservoirs. Yet another application of the arbitrage framework is in probability theory. Profitable arbitrage in the market for contingent commodities is called "making book." A person's subjective probability judgments satisfy the laws of probability if they are "coherent" in the sense of not allowing book to be made against the person. Thus arbitrage on the market for contingent commodities enforces the laws of probability.

Arbitrage-related concepts have been applied successfully in financial economics. Merton H. Miller and Franco Modigliani used impressive arbitrage arguments in proving their famous irrelevance theorem [1958]. Stephen A. Ross [Ross 1976a, 1976b] and his colleagues have developed Arbitrage Pricing Theory so that it is now recognized as a fundamental principle in finance theory [Varian 1987]. Our purpose here is not to use arbitrage concepts to study financial markets, but to find the mathematically defined "markets" and the related arbitrage-concepts in the mathematics of all classical constrained optimization problems.

ARBITRAGE IN GRAPH THEORY A directed graph G =(G0,G1, t,h) is given by a set G0 of nodes (numbered 0,1,...,m), a set G1 of arcs (numbered 1,2,...,b), and head and tail functions h,t:G1 G0, which indicate that arc j is directed from its tail, the t(j) node, to its head, the h(j) node.




t(j) h(j)Arc j

Figure 1. Arc j from Tail t(j) to Head h(j)

It is assumed that there are no loops at a node, i.e., h(j) t(j) for all arcs j. A path from node i to node i' is given by a sequence of arcs connected at their heads or tails that reach from node i to node i'. A graph is connected if there is a path between any two nodes. It is assumed that the graph G is connected. A closed circular path where no arc occurs more than once is a cycle [for more graph theory, see any text such as Berge and Ghouila-Houri 1965]. Let T be any group (not necessarily commutative) written multiplicatively (i.e., a set with a binary product operation defined on it, with an identity element 1 and with every element having a multiplicative inverse or reciprocal). For most of our purposes, T can be taken as R*, the multiplicative group of nonzero reals. In the motivating economic interpretation, a different commodity is associated with each node, and the arcs represent channels of exchange or transformation between the commodities at the nodes. A function r:G1 T is a rate system giving exchange or transformation rates. Given an arc j, one unit of the t(j) commodity can be transformed into r(j) = rj units of the h(j) commodity.

t(j) h(j)Arc j

Rate rj

Figure 2. Transformation Rate rj on Arc j

A graph (G,r) with a rate system r represents a market, so it will be called a market graph. These group-labeled graphs are also called "voltage graphs" [Gross 1974] or "group graphs" [Harary et al. 1982]. All transformations are reversible. If arc j is traversed against the arrow, the transformation rate is the reciprocal 1/rj. Given a path c from node i to i', the composite rate r[c] is the product of the rates along the path using the reciprocal rate for any arc traversed against the direction of the arrow. A function P:G0 T labeling the nodes is a price system (or absolute price system). A rate system Q(P):G1 T can be derived from a price system by taking the price ratios

Q(P)(j) = P(h(j))–1P(t(j)).

Equation 1. Derived Rate on arc j = Price at Tail Divided by Price at Head Derived rate systems have certain special properties:

1. for any path c from i to i', Q(P)[c] = P(i')–1P(i), 2. for any two paths c and c' from i to i', Q(P)[c] = Q(P)[c'], and 3. for any cycle c, Q(P)[c] = 1.

Given a market graph (G,r), the rate system r is said to be path-independent if for any two paths c and c' between the same nodes, r[c] = r[c']. The rate system is said to be arbitrage-free if for any cycle c, r[c] = 1 ["arbitrage-free" = "balanced" in much of the graph-theoretic literature following Harary 1953].

r = 1/2 r = 3

r = 3/2

r = 4/3

r = 4

r = 1/12

p = 1 p = 2 p = 6

p = 4

p = 3 p = 12

r[c] =(1/2)(1/3)(3/2)(4/3)(1/4)(12) = 1 Figure 3. An Arbitrage-Free Market Graph

In an idealized international currency exchange market with no transaction costs, if the product of the exchange rates around a circle is greater than one, profitable arbitrage is possible. If the product is less than one, then exchange around the circle in the opposite direction would be profitable arbitrage. Hence the market is arbitrage-free if the product of exchange rates around the circle is one.




A rate system derived from a price system has both the properties of being path-independent and arbitrage-free, and, in fact, the three properties are equivalent. That equivalence theorem is the finite multiplicative version of the calculus theorem about the equivalence of the conditions:

1. A vector field is the gradient of a potential function, 2. A line integral of the vector field between two points is path-independent, and 3. A line integral of the vector field around any closed path is zero.

COURNOT-KIRCHHOFF ARBITRAGE THEOREM: Let (G,r) be a market graph with r:G1 T taking values in any group T. The following conditions are equivalent: 1. There exists a price system P such that Q(P) = r, 2. The rate system r is path-independent, and 3. The rate system r is arbitrage-free. For a proof of this straightforward noncommutative generalization of Kirchhoff's Voltage Law (1847) and Cournot's earlier (1838) arbitrage-free condition, see Ellerman [1984, 1990].

EXAMPLES OF ARBITRAGE-FREE CONDITIONS KIRCHHOFF'S VOLTAGE LAW

The original "arbitrage-free" condition in electrical circuit theory is Kirchhoff's voltage law (KVL). It is the additive version of the multiplicative arbitrage principle. In economics, the commodity with the price of 1 is the numeraire. In circuit theory, the node with a potential of 0 is the "ground" or "datum" node. A real-valued function on the nodes of a graph is a "potential." The additive version of the quotient operator Q() is the difference operator, which assigns to each arrow the difference between the potentials at the tail and head of the arrow. If an assignment of reals to the arrows of the graph comes from a potential on the nodes by taking these differences, then the assignment to the arrows is called a "potential difference" or "tension." Reals assigned to the arrows can be added up around any cycle (taking care to take the negative of the number if the arrow is traversed backwards). The Arbitrage Theorem then yields:

KVL: An assignment to the arrows is a potential difference if and only if it adds to zero around any cycle.

ASSEMBLIES OF GEARS OR WHEELS A train of gears (or wheels) that went around in a circle would be perfectly useless, but it provides an amusing example of an arbitrage-free condition. Gear ratios multiply along a gear train so this example uses the arbitrage theorem in its multiplicative form. Angular velocities on the shafts play the role of the commodity prices. If angular velocities can be assigned to the shafts so that their quotients are the gear ratios, then the whole gear assembly can move. Otherwise it would be rigid. Thus a gear assembly has a motion if and only if the product of gear ratios around any circular gear train is one. By placing two or more gears on the same shaft, a circular gear train need not have all the gears in the same plane. But if all the gears are in the same place (e.g., if they are all lying on a table), then the product of gear ratios around any circle will always be plus one (even number of gears in the circle) or minus one (odd number of gears in the circle). Thus a circular gear train with all the gears in the same plane can move if and only if it has an even number of gears. Graphic artists sometimes draw a simple picture of three gears meshing in a circle, and some organizations have even used such an image as their logo. But such a gear train is a perfect example of gridlock since it cannot move.

Figure 4. A Rigid Circular Wheel Assembly

CLIQUE FORMATION IN SOCIAL GROUPS The arbitrage condition applied to "likes" and "dislikes" in social groups might give some insight into the ethnic mentality where likes and dislikes are based largely on being inside or outside of the clique, clan, or tribe. Each node in the graph is a person and each arrow has +1 or –1 according to whether the person at the tail of the arrow likes or dislikes the person at the head of the arrow. Then a graph is said to be "balanced" if it is arbitrage-free in the sense of the likes and dislikes multiplying to +1 around any circle [e.g., Harary 1953, Harary, Norman and Cartwright 1965]. The classic "mother-in-law triangle" is an example of an unbalanced graph.

?




Mother-in-Law

Husband Wife+1

+11

Figure 5. An "Unbalanced" Social Group

A "price system" marks each node or person with +1 or –1, and a given pattern of likes and dislikes is derived from such a marking if each person likes others with the same marking and dislikes those with a different marking. Then the arbitrage theorem gives the following result. A social group with a given pattern of likes and dislikes can be partitioned into two clans such that all likes are intraclan and all dislikes are between clans if and only if the pattern of likes and dislikes is balanced (arbitrage-free). Thus there is no way to group the three people in the mother-in-law triangle into two families to account for the likes and dislikes. The husband and mother-in-law (wife's mother) have to be in different families to account for their dislike, but then the wife has an identity crisis. When arbitrage is possible then, in effect, a commodity has two prices (so one can buy low and sell high). In the previous example, a wheel had to rotate in two directions at once in order for the wheel assembly to move. In this example, the pattern of likes and dislikes in the mother-in-law triangle puts the wife in the position of having two conflicting family identities.

HEAT ARBITRAGE IN THERMODYNAMICS The Carnot engine approach to the second law of thermodynamics (simplified for a finite number of temperatures) gives an application of the arbitrage theorem in physics. Each node is a heat reservoir with a different temperature (including for calibration purposes the freezing and boiling points of water). Each arrow is a Carnot engine that can reversibly withdraw the heat dQc from the low-temperature reservoir by performing the work dW, and dump the heat dQh into the hotter reservoir where dQh = dW + dQc by the first law of thermodynamics (conservation of energy). The ratio r = dQc/dQh is called the efficiency debit and is the positive real number assigned to the arrow. When Carnot engines are hooked in series, the composite efficiency debit is the product of the efficiency debits of the individual engines.

Hot

Cold

dQ h

dQ c

dW dQ h dQ c r = /

Figure 6. A Carnot Engine

One formulation of the second law of thermodynamics is that between any two temperatures, there is path independence in the sense that the various connecting paths must have the same efficiency debit [e.g., Morse 1964, 50]. Otherwise one could perform a type of "heat arbitrage" (move heat from the cold to hot reservoir with no net expenditure of energy) and have a "perpetual motion machine of the second kind" [e.g., Castellan 1964, Chapter 8]. By the arbitrage theorem, the second law implies that there exists a thermodynamic "price" T at each node or reservoir such that the efficiency debit of each Carnot engine is the "price ratio" Tcold/Thot. If we normalize the freezing point of water to 0 and the boiling point to 100, then the "prices" are the Kelvin absolute temperatures of the reservoirs.

ARBITRAGE IN PROBABILITY THEORY "Making book" means making a series of bets so that one has positive net earnings no matter what happens. That is equivalent to performing profitable arbitrage on the market for contingent commodities. A contingent commodity is a commodity conditioned on the occurrence of an event, e.g., $1000 if your number comes up in a lottery.




A person subjectively assigns a probability p(E) to an event E if the person is just willing to pay p(E)S in order to receive the stake S if the event E occurs. Thus p(E) is the price the person is willing to pay for the contingent commodity "$1 if E." Suppose that a bettor places two bets with a bookie: the bettor pays $1 to get $2 if it is raining at noon, and pays $1.05 to get $2 if it is not raining at noon. By taking both bets, the bookie "makes book." No matter what happens, the bookie gives up $2 and receives $2.05 (= 1.00+1.05) for a net profit of $.05. The bettor's probability assignments are said to be coherent if book cannot be made against the bettor (unlike the example). Ramsey [1960 (orig. 1926)] and de Finetti [1964 (orig. 1937)] showed that the laws of probability theory, such as p(E) + p(not-E) = 1, could be derived from the requirement of coherence. Arbitrage on the market for contingent commodities enforces the laws of probability. Even if each person has coherent probability judgments, bookies can still make their living off the combined incoherence of different people's probability judgments.

ARBITRAGE AND OPTIMIZATION THEORY A simple example of an optimization problem will now be used to illustrate our main topic, the interpretation of the necessary conditions for optimization as an arbitrage-free condition. Suppose that the problem is to find the proportions for a rectangular fenced field of maximum area for a given cost when one length of the field requires a form of fencing costing four times the fencing used on the other three sides.

$4 per foot

$1 per foot on other three sides

Width = W ft.

Length = L ft.

Figure 7. Maximize Rectangular Area with Given Cost

There are two commodities on the market, cost dollars and square feet of area. There are two ways to transform an extra dollar into area: spend the dollar to increase the width of the field or to increase the length of the field. If the dollar is spent on the width, then it buys an extra half foot on the width (the extra foot needs to be split between the two widths to keep the rectangular shape) so the area goes from WL to (W + 1/2)L. Hence the extra area is L/2. If the dollar is spent on the length, then only one-fifth of a foot can be added to the length ($.80 for one-fifth foot on the expensive side and $.20 for one-fifth foot on the cheap side). Thus the area is increased from WL to W(L + 1/5) and the extra area is W/5. Hence there are two exchange rates from the cost dollars to the square feet of area are L/2 and W/5. This "market" can be pictured in an "arbitrage diagram."

Cost Dollars Square Feet of Area

L/2

W/5

Figure 8. Arbitrage Diagram for Maximum Area Problem This market is arbitrage-free if and only if the two exchange rates between the commodities are equal: L/2 = W/5. Hence the maximum area field is obtained when the length is two-fifths or 40 percent of the width. When formulated as a constrained maximization problem (maximize area subject to a fixed cost), that common rate L/2 = W/5 is the Lagrange multiplier for the problem. ARBITRAGE-FREE CONDITIONS ON MARKET GRAPHS The value group T will now be specialized to R*, the multiplicative group of nonzero real numbers. But price systems P will now be extended by allowing zero values in the reals R, i.e.,

P:G0 R. An extended price system P and a rate system r are associated if for any arc j,

P(h(j))rj – P(t(j)) = 0. If the price system has all nonzero values, this is the same as the rate system being derived from the price system.




The zero-price system (all zero prices) is trivially associated with any rate system. If a rate system is not arbitrage-free, then the zero-price system is the only associated price system. With that fixed-rate system, profitable arbitrage means "getting something for nothing," so all commodities become free goods and have zero prices. It is useful to reformulate some of the graph-theoretic notions using incidence matrices. Given (G,r), the node-arc incidence matrix S = [Sij] is the (m+1) b matrix where:

S ij

r j if Arc j

1 ifArc j

0 Otherwise

Node i

Node i

Equation 2. Node-Arc Incidence Matrix

The jth column of S has a minus one (–1) and a rate rj, which are the results of transforming one unit of the t(j) good into rj units of the h(j) good. Any linear combination of the columns would represent a possible market-exchange vector using the rate system r. The negative components represent the goods given up in exchange for the goods represented by the positive components. Thus the vector space of all linear combinations of columns of S, the column space Col(S), will be called the exchange space of the market graph (G,r).

Let S0, called the reduced incidence matrix, be the m b matrix obtained from S by deleting the top row, the row corresponding to node 0. If G is a connected graph (a path between any two nodes), then the reduced incidence matrix S0 has linearly independent rows, i.e., S0 has full row rank. Let P* = (P1,...,Pm) be a row vector such that P*S0 = 0. Some node i was connected to the "deleted" node 0 by some arc j. In order for P* to zero the jth column of S0, Pi must be zero. If arc j is from node i to i' both in the node set {i,...,m}, then P*S0 = 0 implies Pi'rj – Pi = 0 so Pi' and Pi are both zero or both nonzero. Thus each node connected to node i must have a zero price. Since G is connected, all prices must be zero, i.e., P* = 0, so the rows of S0 are linearly independent.

Adding back the top row, the row rank of S is either m or m+1, so the column rank, i.e., the dimension of Col(S), is also either m or m+1. A subspace of Rm+1 of dimension m (one less than the dimension of the full space) is a hyperplane through the origin. Thus the exchange space is either a hyperplane in Rm+1 or is the full space. The left nullspace LeftNull(S) of any matrix S is the space of vectors P such that PS = 0. If S is the incidence matrix of a market graph (G,r) and P = (P0,P1,...,Pm) is in LeftNull(S), i.e., PS = 0, then for all arcs j Ph(j)rj – Pt(j) = 0 so P is a price system associated with the rate system r. Hence LeftNull(S) is called the price space associated with the exchange space Col(S) and the elements P are called price vectors. The exchange space Col(S) and the price space LeftNull(S) are orthogonal complements of one another, i.e.,

a. X is an exchange if and only if for any price vector P, PX = 0, and b. P is a price vector if and only if for any exchange X, PX = 0. Since they are orthogonal complements, dim[Col(S)] + dim[LeftNull(S)] = m+1. Since the exchange space is of dimension m or m+1 (G is assumed connected), the dimension of the price space is either one or zero. A price vector with any nonzero components must have all nonzero components. Any two nonzero price vectors must be scalar multiples on one another. The two cases of a one or zero dimensional price space correspond to the cases of (G,r) being arbitrage-free or allowing profitable arbitrage. If profitable arbitrage is possible, then the fixed nonzero exchange rates r would allow one to generate any quantities of the goods so all commodities are free goods, i.e., P = 0 is the only price vector. These results and some easy consequences are collected together in the following theorem. ARBITRAGE THEOREM FOR MARKET GRAPHS: Let (G,r) be a market graph where G is connected and r:G1 R*. The following conditions are equivalent: 1. There exists a price system P:G0 R* such that Q(P) = r, 2. The rate system r is path-independent, 3. The rate system r is arbitrage-free, 4. The price space LeftNull(S) is one-dimensional, 5. The exchange space Col(S) is a hyperplane (with a nonzero price vector as a normal vector),




6. The top row of S, s0, can be expressed as a linear combination of the bottom m rows S0 of S, i.e., there exist µ = (µ1,...,µm) such that s0 + µS0 = 0, and

7. If an exchange vector b = Sx has b1 = ... = bm = 0, then b0 = 0. The incidence-matrix treatment of market graphs suggests a generalization of the economic interpretation to a more general matrix context. The rows represent commodities. The columns specify exchange or production possibilities. Negative entries represent goods given up in exchange or inputs to production, while positive components stand for goods received or the outputs. Any scalar multiple, positive or negative, of a column also represents a possible exchange or transformation so the column space is the space of possible exchanges or transformations. The orthogonally complementary left nullspace is the set of price vectors such that all the exchanges can be obtained as trades at those prices [for more linear algebra, see any text such as Strang 1980]. AN ECONOMIC INTERPRETATION OF COFACTORS, DETERMINANTS, AND CRAMER'S RULE Let A be a square (m+1) (m+1) of reals, and let A(k) be the (m+1) m matrix obtained by deleting column k for k = 0,1,...,m. The column space Col(A(k)) is the space of exchanges spanned by the remaining m columns. Let P(k) = (P0(k),P1(k),...,Pm(k)) be the cofactors of the deleted column k. By the property of "expansion by alien cofactors," P(k)A(k) = 0 so P(k) is a "price vector" in LeftNull(A(k)). The cofactors in P(k) will be called the k-prices. The cofactors of any column of A are prices so that the exchanges defined by the remaining columns can be obtained at those market prices. Now introduce the exchange (or productive) possibilities given by the deleted column k into the market. Its value at the reigning prices P(k) is the determinant |A| obtained by the cofactor expansion of column k. If |A| 0 then any vector b can be obtained as an exchange vector Ax = b. As in a market that allows profitable arbitrage at fixed exchange rates, any exchange is allowed and the only price vector is the zero vector. It is therefore desirable to alter temporarily the interpretation of the columns of A. Previously the columns represented exchange or production possibilities with all commodities involved as inputs or outputs listed as components. We now interpret each column as representing the reversible input-output vector of a machine operating at unit level. But the machine's services are not represented in the input-output vector, so the value of the vector can now be interpreted as the competitive rent imputed to a unit of the machine services. The vector of cofactor k-prices P(k) = (P0(k),P1(k),...,Pm(k)) can now be interpreted as a set of commodity prices that impute zero

rents to all the other m machines (excluding the kth machine). The determinant |A| is the competitive rent (or subsidy, if negative) imputed to the unit services of machine k at those k-prices. Dividing by the determinant-as-rent, the normalized k-prices are the k-prices expressed in terms of the units of machine k services as numeraire.

P kP kA

*

Equation 3. Prices to Give Unit Rent to Machine k, Zero Rent to Other Machines At the normalized k-prices P*(k), all machines have zero imputed rent—save machine k, which has an imputed rent of unity. This yields an economic interpretation of the inverse matrix A–1 as the normalized price matrix obtained as the column of row vectors P*(k) for k = 0,1,...,m.

1A

m*P

1*P0*P

*P

Equation 4. Inverse Matrix as Matrix of Normalized Price Vectors Suppose the machines are operated at the levels x = (x0,x1,...,xm)T so the net product vector is Ax = b. In competitive equilibrium, the competitive rents due on the machines must equal the value of the net product vector leaving no pure profits for arbitrageurs. Given a commodity price vector P = (P0,P1,...,Pm), the unit machine rents R = (R0,R1,...,Rm) must be such that the total rent Rx equals the value Pb of any net product b = Ax, i.e., Rx = Pb = PAx for any x. Equation 5. Machine Rent = Value of Net Product in Competitive Equilibrium Thus competitive equilibrium requires the competitive rents R = PA in terms of P. Now consider the specific price vector P*(k). The competitive rents R = P*(k)A impute a rent only to machine k, and that rent is unity. Hence the total rent Rx = xk = P*(k)Ax = P*(k)b is the level of operation xk of machine k so we have derived Cramer's Rule.




Competitive Machine Rent = xk = P*(k)b = Value of Net Product. Equation 6. Cramer's Rule as a Competitive Equilibrium Condition

ARBITRAGE-FREE MARKET MATRICES We now return to the "full-disclosure" interpretation of the columns of A. All commodities and services involved in the exchange or productive transformation are exposed as components of the column vectors. When is a matrix like a market? One answer is when it is like the node-arc incidence matrix of a market graph. Let A be a rectangular (m+1) n matrix with m+1 n. Any matrix or its transpose has that form. Such a matrix A is a market matrix if rank(A) m. A market matrix has a rank of m or m+1. A market matrix A is said to be arbitrage-free if rank(A) = m. The node-arc incidence matrix of a connected market graph is a market matrix. The market graph is arbitrage-free (as a graph) if and only if its incidence matrix is arbitrage-free (as a matrix). A market matrix has m linearly independent rows that, for notational convenience, we may take to be the bottom m rows numbered i = 1,...,m (the top row is row 0). Every set of m columns from the (m+1) n matrix A determine a (m+1) m submatrix A* (taking the columns in the same order as in A). As a visual aid, we can consider a (m+1) 1 "dummy" column vector [?,?,...,?]T appended to the left of A* to form a m+1 square matrix. The cofactors P0, P1, ..., Pm of the dummy column are the local cofactor prices determined by the m columns of A*. The binomial coefficient C(n,m) = n!/(m!(n–m)!) gives the number of ways of choosing m columns from among n columns, so there are C(n,m) vectors of local cofactor prices (not necessarily all distinct). At least one vector of local cofactor prices is nonzero since rank(A) m. The rows have been arranged so the bottom m rows are linearly independent. Let A* be a submatrix of m linearly independent columns so it has a vector of local cofactor prices P* = (P0*, P1*, ..., Pm*) such that P0* 0. These cofactor prices may be normalized by taking commodity 0 as the numeraire to obtain the relative prices: (1,µ1,...,µm) = (1, P1*/P0*, ..., Pm*/P0*). Equation 7. Normalized Cofactor Prices To complete the development of a "market" in the market matrix A, we need to define transformation rates between commodities. The important rates are the transformation rates ri of good i into good 0 for i = 1,...,m, which can be defined using any m linearly independent columns A*. The m activities are to be run at levels so that exactly one unit of good i is used-up and zero units of good j are produced or used up for j i,0. Then the number of units of good 0 produced gives the transformation rate ri so that the 1 unit of good i used up is transformed into ri units of good 0. In matrix notation, let A0* be the bottom m rows of a (m+1) m matrix A* of m linearly independent columns of A so that |A0*| = P0* 0. Let a0* be the top row of A*. The activity vector x that uses up exactly one unit of good i is the x such that

A0*x = (0,...,0,–1,0,...,0)T = –Ii

where Ii is the ith column of the m m identity matrix I so x = –(A0*)–1Ii. Let

ri = a0x = –a0*(A0*)–1Ii

Equation 8. Transformation Rate of ith Good into Numeraire 0th Good so the vector r = (r1,...,rm) of the transformation rates defined by A* is r = –a0*(A0*)–1. Cofactor Price Theorem: Given any (m+1) m submatrix A* of linearly independent columns, the transformation rates r determined by A* are equal to the normalized cofactor prices: (r1,...,rm) = (P1*/P0*,...,Pm*/P0*) = (µ1,...,µm). Proof: For notational simplicity, we take the m columns of A* to be the first m columns of A. For the x used above in the definition of ri, we have the following:

.

0

1

0r

x

aa

aa

aaaa

i

mm1m

im1i

m111

m001




Hence the (m+1) x (m+1) matrix obtained by adding the RHS column vector as the m+1st column is singular. Thus its determinant obtained by the cofactor expansion of the m+1st column is zero, i.e., P0*ri – Pi* = 0 so ri = Pi*/P0*. The next theorem states a number of conditions equivalent to the market matrix A being arbitrage-free. An arbitrage-free market has unique relative prices so the C(n,m) local cofactor prices must mesh or fit together in the sense of being scalar multiples of the nonzero price vector P* which was normalized to (1,µ1,...,µm). The space spanned by the C(n,m) cofactor price vectors is the one-dimensional space Left Null(A). In the application to classical optimization, the µi's are the Lagrange multipliers of m constraints, which are thus interpreted as the unique prices of m resources in terms of the maximand as numeraire. Arbitrage Theorem for Market Matrices: Let A be any (m+1) n market matrix where we assume the rows 1 through m are linearly independent. Let a0 be the top row, and let A0 be the bottom m rows of A. The following conditions are equivalent: 1. A is arbitrage-free, 2. The price space Left Null(A) is one-dimensional, 3. The exchange space Col(A) is a hyperplane (with a cofactor price vector as a normal vector), 4. There exists µ = (µ1,...,µm) such that a0 + µA0 = 0, and 5. If an exchange vector b = Ax has b1 = ... = bm = 0, then b0 = 0. [See Ellerman 1990 for the proof.] FIRST-ORDER NECESSARY CONDITIONS AS ARBITRAGE-FREE CONDITIONS The intuitive arbitrage reasoning as well as the formal results for arbitrage-free market matrices can be applied to yield the first-order necessary conditions for regular constrained optimization problems with equality constraints. Consider the one-constraint problem: Maximize y = f(x1,...,xn) Subject to: g(x1,...,xn) = b where all functions are continuously twice differentiable. There are two commodities, the resource b and the maximand y. There are n "instruments" with the levels of operation x1,...,xn. At the levels x1,...,xn, the amount of the resource used-up is g(x1,...,xn), and f(x1,...,xn) is the amount of the maximand produced. Let xo = (x1o,...,xno) be levels of the instruments that use up all of the available resource, i.e., g(x1o,...,xno) = b. Moreover, we assume that xo is "regular" in the sense that not all the partials g(xo)/ xi = gi are zero. We consider an intuitive "marginal market" defined by the possible marginal transformations of b into y. In an international currency market (without transaction costs), there might be n banks or exchange houses that to prevent arbitrage would have to offer the same rate of exchange between any two currencies. In our market, the n instrument variables offer n ways to transform the resource b into the maximand y. A marginal variation xi uses-up gi xi units of b and produces fi xi units of y so the rate of transformation is

b y

f xg x

fg

i ii i

ii

Equation 9. Rate of Transformation of Resource into Maximand The market is arbitrage-free if and only if the n transformation rates fi/gi provided by the n instruments are equal where the common rate of transformation is the Lagrange multiplier µ.

n

n

2

2

1

1

gf

gf

gf

Equation 10. Arbitrage-Free Condition

y b µ

f /g1 1

n nf /g

2 2f /g

Figure 9. Arbitrage Diagram for the Marginal Market




Thus the first-order necessary conditions for xo to be a constrained maximum are equivalent to the intuitive market being arbitrage-free. To use the machinery of market matrices, let

n21

n21

gggfff

A

where –gi is used instead of +gi since g(x1,...,xn) represents the amount of the resource used up. Consider any column of this market matrix coupled with the dummy column to form a square matrix:

??

.fgi

i

The cofactors of the dummy column are the local prices Py = –gi and Pb = –fi, so (assuming gi 0) the cofactor price ratio is the transformation rate defined by the marginal variations in the instrument xi.

b y

P P f gb y i i

Equation 11. Transformation as Cofactor Price Ratio Since m = 1, there are C(n,1) = n sets of cofactor prices. The market matrix is arbitrage-free if and only if the n cofactor price vectors define the same price of b in terms of y (i.e. the condition of Equation 10). For the previous example of maximizing the area of the rectangular field using different types of fencing, the mathematically formulated problem is: Maximize y = x1x2 Subject to: 2x1 + 5x2 = b. The market matrix is:

Af fg g

x x

1 2

1 2

2 12 5

and the cofactor price ratios are given by the cofactors of the dummy columns in the matrices:

??

??

.x

orx1 2

5 2

The mathematically defined "market" is arbitrage-free if all the cofactor price ratios are the same:

PP

x xb

y

1 25 2

which gives the previous necessary conditions that the length x2 must be two-fifths or 40 percent of the width x1. Consider a problem with m = 2 constraints:

Maximize y = f(x1,...,xn) Subject to: g1(x1,...,xn) = b1 g2(x1,...,xn) = b2

where n > m = 2. Let G be the matrix of partials of the constraints evaluated at xo:

.gggggg

G 2n

22

21

1n

12

11

The candidate point xo is assumed to be regular in the sense that G is of full row rank. There are three commodities in the intuitive market for the problem: the maximand y and the two resources b1 and b2. To define a transformation rate from b1 into y, one cannot just vary one instrument xi because that may also vary b2.




One must consider variations in (m) two variables xi and xj which leave b2 constant and yield variations –db1 and dy to define a transformation rate r1 = dy/db1 from b1 into y. The rate for transforming b2 into y can be similarly defined. Using the cofactor price theorem, these rates can be obtained as ratios of local cofactor prices. Since G is of full row rank, there are m = 2 instruments xi and xj such that

Gg gg g

i j

i j*

1 1

2 2

is nonsingular. Given the matrix (with the unknown dummy column)

?

?

?

f f

g g

g g

i j

i j

i j

1 1

2 2

the cofactors of the dummy column yield the prices:

P g g g g

P f g f g

P f g f g

y i j i j

b i j j i

b j i i j

1 2 2 1

2 2

1 11

2 Equation 12. Cofactor Prices where Py 0 by the choice of i and j. By the cofactor price theorem, the cofactor price ratios yield the transformation rates from the resources into the maximand. For instance, if xi and xj are varied to hold b2 constant, the relative cofactor price of b1 in terms of y, Pb1/Py = µ1, gives the rate of transformation of b1 into y defined by the variation in xi and xj. For the intuitive market to be arbitrage-free, all the local cofactor prices (Py',Pb1',Pb2') defined by any set of m = 2 instruments must be scalar multiples of the nonzero price vector (Py,Pb1,Pb2). In formal terms, the market matrix defined by the problem is

AfG

.

The first-order necessary conditions for the candidate point to be a constrained maximum are then expressed by the market matrix A being arbitrage-free and by the other equivalent conditions given in the Arbitrage Theorem for Market Matrices. All these results for m = 2 extend to the general problem with m constraints and n variables (n > m): Maximize y = f(x1,...,xn) Subject to: g1(x1,...,xn) = b1 … gm(x1,...,xn) = bm. The candidate point xo satisfies the constraints and is regular in the sense that the m n matrix G = [ gji ] is of full row rank. Thus there are m columns forming a nonsingular submatrix G*. If f* is the vector of the corresponding m partials of f, then consider the (m+1) (m+1) matrix:

? *? *

.fG

The cofactors of the dummy column form the local cofactor prices Py,Pb1,...,Pbm determined by the m chosen instruments. The intuitive market is arbitrage-free if all the C(m,n) vectors of local cofactor prices are scalar multiples of this nonzero vector. In formal terms, the first-order necessary condition for the candidate point xo to be a constrained maximum is equivalent to the condition that the market matrix of the problem

AfG

is arbitrage-free, which in turn is equivalent to the other conditions stated in the Arbitrage Theorem for Market Matrices.




These results point to a research program that could be developed in several directions. One direction is to show how the second-order sufficient conditions for optimality could be interpreted economically as the conditions for arbitrage to eliminate its own possibility. Preliminary results in this direction are outlined in the appendix. Another direction of development is to extend the arbitrage interpretation to other areas of optimization theory such as optimization with inequality constraints and optimal control theory.

REFERENCES [1]. Berge, Claude, and A. Ghouila-Houri, 1965. Programming, Games and Transportation Networks. John New York: Wiley

and Sons. [2]. Castellan, Gilbert. 1964. Physical Chemistry. New York: Addison-Wesley. [3]. Cournot, Augustin. 1897 (orig. 1838). Mathematical Principles of the Theory of Wealth Trans. Nathaniel Bloom. New

York: Macmillan. [4]. de Finetti, Bruno. 1964 (orig. 1937). "Foresight: Its Logical Laws, Its Subjective Sources. In Studies in Subjective

Probability ed. H. Kyburg and H. Smokler, 93-158. New York: John Wiley. [5]. Ellerman, David P. 1984. "Arbitrage Theory: A Mathematical Introduction." SIAM Review. 26: 241-61. [6]. Ellerman, David P. 1990. "An Arbitrage Interpretation of Classical Optimization." Metroeconomica 41, no. 3: 259-76. [7]. Gross, Jonathan. 1974. "Voltage graphs." Discrete Math 9: 239-46. [8]. Harary, Frank. 1953. "On the notion of balance of a signed graph." Michigan Math. J. 2: 143-46. [9]. Harary, Frank, R. Z. Norman, and D. Cartwright. 1965. Structural Models. New York: John Wiley. [10]. Harary, Frank, B. Lindstrom, and H. Zetterstrom. 1982. "On balance in group graphs." Networks 12: 317-21. [11]. Kirchhoff, G. 1847. "Über die Auflosung der Gleichungen, auf welche man dei der Untersuchung der linearen Verteilung

galvanischer Strome gefuhrt wird." Annalen der Physik und Chemie 72: 497-508. [12]. Modigliani, Franco, and Merton H. Miller. 1958. "The Cost of Capital, Corporation Finance, and the Theory of

Investment." American Economic Review 48: 261-97. [13]. Morse, Philip. 1964. Thermal Physics. New York: W. A. Benjamin. [14]. Ramsey, Frank Plumpton. 1960 (orig. 1926). Truth and probability. In The Foundations of Mathematics, ed. R. B.

Braithwaite. Paterson N.J.: Littlefield, Adams & Company. [15]. Ross, Stephen A. 1976. "The Arbitrage Theory of Capital Asset Pricing." J. Econ. Theory 13: 341-60. [16]. Ross, Stephen A. 1976. "Return, Risk and Arbitrage." In Risk and Return in Finance, ed. Irwin Friend and James L.

Bicksler. Cambridge, Mass.: Ballinger. [17]. Strang, Gilbert. 1980. Linear Algebra and its Applications. Second edition. New York: Academic Press. [18]. Varian, Hal R. 1987. "The Arbitrage Principle in Financial Economics." The Journal of Economic Perspectives 1, no. 2: 55-

72.


_____________________________________________________________________________________________________ IJIRAE: Impact Factor Value - ISRAJIF: 1.857 | PIF: 2.469 | Jour Info: 4.085 | Index Copernicus 2014 = 6.57


STUDIES ON STABILIZED MUD BLOCK AS A CONSTRUCTION MATERIAL

Vinu Prakash**, Amal Raj *, Aravind S*, Basil Mathew*, Sumith V R * ** (Asst. Professor, Department of Geology, Mar Athanasius College of Engineering, Kothamangalam *(Civil Engineering VIII Semester Students, Mar Athanasius College of Engineering, Kothamangalam

ABSTRACT- Soil as a building material is available in most areas of the world. In developing countries, earth construction is economically the most efficient means for house construction with the least demand of resources. Investigation is carried out to find the suitable proportion of locally available materials such as soil , coir , straw etc. with cement as stabilizers for improving the strength of locally available mud blocks and thus to provide affordable housing. Using soil (from areas of Neriamangalam) and stabilizers (cement, lime, straw fibre, coir fibre, plastic fibre), eleven different types of samples were prepared. Tests were conducted on these samples in order to evaluate their performance such as compressive strength and total water absorption on which the durability of the blocks depend. The investigation has revealed that, out of all block samples, blocks which are produced from10% cement (C10), 10% cement with 3% coir fibre (C10C) and 10% cement with 3% plastic fibre (C10P) have compressive strength and total water absorption values above the recommended minimum values for structural work.(IS 1725:1992)

Keywords: Stabilizers, compressive strength, water absorption, affordable housing.

1. INTRODUCTION

Adequate shelter is one of the most important basic human needs. Currently, the majority of developing countries are faced with a problem of providing adequate and affordable housing in sufficient numbers. In the last few decades, shelter conditions have been worsening: resources have remained scarce, housing demand has risen and the urgency to provide immediate practical solutions has become more sensitive [4], [5].

For providing low-cost housing, we must rely on locally available raw materials. Home brick-makers have long been using fibrous ingredients like straw to improve the tensile strength of mud bricks. However, they have not had a chance to do scientific experimental investigation on the balance of ingredients and the optimisation of this production [9]. The fibres, which are connected together by mud, provide a tensile strength in mud bricks. The fibres provide a better coherence between the mud layers. The stress–strain relation of mud bricks under compression is very important. The compressive strength of fibre reinforced mud brick has been found to be higher than that of the conventional fibreless mud brick, because, fibres are strong against stresses. Furthermore, such materials are abundantly available and renewable in nature. Local soil has always been the most widely used material for earthen construction in India. However, such type of construction has some serious drawbacks such as, i) Water penetration ii) Erosion of walls at the plinth level/ lower level by splashing of water from ground surfaces. iii) Attacks by termites and pests. iv) High maintenance requirements. v) Low durability.

Mudbrick has several advantages over conventional fired clay or concrete masonry. Mud bricks perform considerably better, in environmental terms, then fired bricks. They have significantly less embodied energy, contribute fewer CO2 emissions and help to promote the local economy and local labour. At first glance they appear to be an ideal candidate for an economically viable sustainable construction material. However, the major drawback of unfired mud bricks is that they tend to be less durable than their fired counterparts and are more susceptible to water damage. Traditionally, unfired mud bricks have been stabilised with cement to overcome these short comings but the use of cement and other stabilizers reduces the environmental differential between unfired bricks and fired ones. Research into alternative stabilisers is both relevant and necessary to ensure unfired mud bricks remain a competitive alternative to modern construction methods. They have high thermal mass and sound absorbing property. Stabilized mud blocks can be produced easily without any skilled labour and sophisticated machinery.

2. SCOPE OF THE PROJECT

Relevance of the project includes providing a low cost alternative to the contemporary building materials. Especially in the areas of low rainfall, stabilized compacted earth blocks are a better alternative considering cost as a factor. Since India is a tropical country, mud blocks preserves a good living atmosphere inside the houses, it prevents too much heat from entering the building.




3. OBJECTIVE

The objectives of this project are [2]:- To investigate local soils to identify their suitability in stabilized earth block production. To study experimentally the effect of altering important variables such as cement, lime, straw fibre, coir, plastic

fibre content on the properties and performance of stabilized earth blocks. To meet the economic requirements of the local situation by: reducing dependence on outside sources and ensuring

low cost alternatives. To determine the percentage of stabilizer and the most effective stabilizer for the chosen soil [11].

4. EXPERIMENTAL SETUP 4.1 COLLECTION OF SAMPLES

Different soil samples were collected from Koothattukulam, Neriamangalam, Nellikuzhy, and Cheladu of Ernakulam district. All the samples were properly dried. Sieve analysis was done on the samples to get different fractions of gravel, sand, silt and clay. A good soil sample for mud block construction should have 10-15% gravel, 50-75% sand, and 15-30% silt & clay.

4.2 MOULD Moulds were prepared with dimensions 254 mm X 127mm X 76 mm size. And the mould was prepared with wood [1].

4.3 SIEVE ANALYSIS Purpose: This test is performed to determine the percentage of different grain sizes contained within a soil. The mechanical or sieve analysis is performed to determine the distribution of the fine and coarser or larger-sized particles [10]. This test consists of filtering the soil through a series of standard mesh sieves placed one above the other in decreasing order (i.e. the finest mesh at the bottom) and in determining the proportion of soil particles left in each sieve. The final test result gives a complete and quantitative proportion of the different grain sizes within the soil mass. Observations:-The results obtained from different samples are,

Figure 1: Sieve analysis results of sample 1.

Figure 2: Sieve analysis results of sample2.

020406080

100

10 100 1000 10000

% fi

ner

Particle size (microns)

020406080

100

10 100 1000 10000

% fi

ner


Percentage of gravel = 6.6% Percentage of sand = 89.6% Percentage of silt & clay = 3.8%






Figure 5 : Desirable proportions for brick making.

From the results obtained from sieve analysis of the collected samples ,it was found that sample 2,has almost similar proportions for making a good brick as shown in Figure 5.Sample 2 contains 16.2% gravel , 76% sand & 7.8% silt and clay. Proportions selected The various proportion of stabilizers used are [6],

TABLE 1: STABILIZER PROPORTIONS. PROPORTIONS SELECTED DESCRIPTION S Soil only L5 Lime-5% C5 Cement-5% L10 Lime-10% C10 Cement-10% C5C Cement-5%,coir-3% C5P Cement-5%,plastic fibre-3% C5S Cement-5%, straw fibre-3% C10P Cement-10%, plastic fibre-3% C10S Cement-10%, straw fibre-3% C10C Cement-10%, coir-3%

020406080

100

10 100 1000 10000

% fi

ner

Particle Size (microns)

0

20

40

60

80

100

10 100 1000 10000

% fi

ner





4.4 COMPRESSION TEST Compressive strength of each mud blocks were tested in the compression testing machine, initially the self-weight of the compression testing machine was balanced. The maximum compressive strength value obtained was 3.20 N/mm2 for the mud block with 10%cement and 3% coir fibre. As per IS 1725,the compressive strength range is between 2-3 N/mm2 [3].Results of compression test are shown in Table 2.For mud blocks with cement as stabilizing agent showed more compressive strength than the mud blocks with lime as the stabilizing agent. For lime when percentage of stabilizer is increased, the change/increase in compressive strength was very slight. Whereas for the mud blocks with cement as stabilizer, the compressive strength were increased reasonably [7].

For mud blocks which are reinforced with coir showed more compressive strength than the plastic fibre and straw fibre, for the same proportion of stabilizer. Mud block with 5% cement & 3% straw fibre showed more compressive strength than the mud block reinforced with plastic fibre (3%).But when the percentage of stabilizer (cement) increased to 10%, the strength is more shown by the mud blocks which were reinforced with plastic fibre. The size of fibre used in the experiment for coir, straw fibre and plastic fibre were 2.5 cm. Maximum dry density was shown by the mud block with 10% cement and 3% straw fibre(C10S).

TABLE 2: RESULTS OF COMPRESSION TEST.

4.5 WATER ABSORPTION TEST Initially the weight of each of the mud block specimen were taken (W1), then mud block specimen were soaked in water . After 24 hours of water absorption, specimens were taken out, wiped and weighed (W2).The % water absorption can be calculated as :-

%waterabsorbed = 푊2−푊1

푊1 × 100 Results of water absorption test are given in Table 3. Adding 5 percent cement failed to satisfy the water as absorption criteria, but this level of cement addition can be useful for applications where stability is not a governing criteria such as in internal walls, partition walls, etc. and appears to be the most economical option [8].

As per IS specification the maximum allowable percentage of water absorption is 15 percentage [3]. Some of the bricks failed in the test, since the water absorption rate of the bricks were higher than the allowable value. Mud blocks stabilized with lime absorbed more amount of water and failed IS criteria, and cannot be used effectively. The mud block with 10 percentage cement and 3 percentage plastic fibre showed maximum reduced water absorption rate of 12.50 percentage

ITEM DESCRIPTION FIBER SIZE WEIGHT (KG)

AVERAGE COMPRESSIVE STRENGTH 28 DAYS (N/MM2)

S Sand only --- 3.60 1.06 L5 5% lime --- 3.58 1.09 C5 5% cement --- 3.63 1.33 L10 10% lime --- 3.61 1.15 C10 10% cement --- 3.60 1.52 C5C 5% cement+3%coir 2.5cm 3.65 2.03 C5P 5% cement+3% plastic 2.5cm 3.65 1.94 C5S 5% cement +3% straw 2.5cm 3.68 1.99 C10P 10% cement +3% plastic 2.5cm 3.60 2.86 C10S 10% cement+3%straw 2.5cm 3.64 2.53 C10C 10%cement +3% coir 2.5cm 3.62 3.20




TABLE 3: RESULTS OF WATER ABSORPTION.

5. COST ANALYSIS

Cost of a burnt brick = Rs 7/- Therefore, from cost analysis, it is understood that blocks with 10 % cement are about 55.7% cheaper than burnt bricks. Blocks having 10% cement 3% coir are about 17.14% cheaper than burnt bricks. 6. CONCLUSION

1. Compressive strength increased with increase in cement content. However, increase in lime content showed very little increase in strength.

2. Compressive strength increased by 43.39% for 10% cement content. 3. Compressive strength increased by 201.88% for 10% cement content & 3% coir . 4. Compressive strength increased by 169.811% for 10% cement & 3% plastic. 5. The average water absorption for blocks having 10% cement (C10),10% cement 3% coir (C10C) , 10% cement 3%

plastic fibre (C10P) were less than 15% satisfying the IS recommendation. 6. Cost analysis of production shows that blocks with 10 % cement are about 55.7% cheaper than burnt bricks. Blocks

having 10% cement 3% coir are about 17.14% cheaper than burnt bricks. 7. REFERENCES [1]. Kabiraj.K, Mandal.U.K, Experimental investigation and feasibility study on stabilized compacted earth block using

local resources, International Journal Of Civil And Structural Engineering Volume 2, No 3, 2012 [2]. Yaser Khaled Abdulrahman, Al-Sakkaf, Durability properties of stabilized earth blocks. Indian Standard1725-1982,

(First Revision), Specification for Soil Based Blocks used in General Building Construction, Bureau of Indian Standards, New Delhi.

[3]. B.V. Venkatarama Reddy, K.S Gagdish, Embodied energy of common and alternative building materials and technologies,Energy and Buildings 35 (2003) 129–137

[4]. Satprem Maïni, Compressed stabilized earth block sand stabilized earth techniques, Research and development by the Auroville earth institute (AVEI).

[5]. Habtemariam Molla, Study of stabilized mud block as an alternative building material and development of models, A thesis submitted to Mechanical Engineering Department School of Graduate Studies of Addis Ababa University.

ITEM WEIGHT BEFORE WATER ABSORPTION(KG)

WEIGHT AFTER WATER ABSORPTION (KG)

% WATER ABSORPTION

S 3.60 4.45 23.61 L5 3.58 4.33 20.94 C5 3.63 4.35 19.83 L10 3.61 4.25 17.72 C10 3.60 4.10 13.88 C5C 3.65 4.25 16.44 C5P 3.65 4.23 15.89 C5S 3.68 4.40 19.56 C10P 3.60 4.05 12.50 C10S 3.64 4.30 18.13 C10C 3.62 4.10 13.25

RAW MATERIALS RATE C10 C10C Soil 200 per truck(180 ft) 4.05 kg - Rs .09 3.915 kg - Rs. .08 Cement 335 per bag (50 kg) .45 kg - Rs 3.01 .45 kg - Rs 3.01 Coir fiber 20 per kg (aprox) ---------- .135 kg - Rs 2.7 Total ----------- Rs 3.10/- Rs 5.80/-




[6]. Bansal Deepak, Masonry from stabilized earth Blocks-Sustainable & structurally viable Option, International Journal of Earth Sciences and Engineering pp. 772-779.

[7]. Hanifi Binici, Orhan Aksogan, Tahir Shah, Investigation of fibre reinforced mud brick as a building material, Construction and Building Materials 19 (2005) 313–318.

[8]. S.Krishnaiah, P.Suryanarayana Reddy, Effect of Clay on Soil Cement Blocks,The 12th International Conference of [9]. International Association for Computer Methods and Advances in Geomechanics (IACMAG). [10]. Doug Harper, Alternative Methods of Stabilisation for Unfired Mud Bricks, School of Civil Engineering &

Geosciences, Newcastle University. [11]. Dr. L. Dinachandra Singh, Shri Ch. Sarat Singh, Final Report On Low Cost Housing Using Stabilised Mud Blocks,

Manipur Science & Technology Council.


_______________________________________________________________________________________________________ IJIRAE: Impact Factor Value - ISRAJIF: 1.857 | PIF: 2.469 | Jour Info: 4.085 | Index Copernicus 2014 = 6.57


Approaches and models of professional competence: Definition of competence in the training of engineers in Latin America

Martín Palma

Department of Industrial Engineering University of Piura, Perú

Dante Guerrero Department of Industrial Engineering

University of Piura, Perú

Ignacio de los Ríos Carmenado Department of Projects and Rural Planning Polytechnic University of Madrid, Spain

Abstract- The article discusses the review of the state of professional competence art, presenting a compilation of indexed research in the two most comprehensive multidisciplinary databases: "Scopus" and "Web of Science" from 1950 to 2012. By analyzing scientific domain of research literature the existence of eight approaches of professional competence is shown, some related to the corresponding international system of competence certification which are supported by different philosophies with a common base. These theoretical and visually positions presented are compared with each other and serve to approach the competence analysis for higher education in engineering. From the presented approaches, it is emphasized that the holistic approach is the most appropriate for coding competence for higher education in engineering. In the analysis of competence in engineering the Tuning Project in Latin America is described and two competence encodings are presented: CDIO and IPMA, both are compared to the Tuning Project for Latin America in order to answer the question of what would be the most useful to cover professional competence needs in Engineering in Latin America.

Key words- professional competence, competence in engineering, analysis of scientific domain.

I. INTRODUCTION In today's academia, there are a variety of definitions and different approaches of professional competence used in the

various disciplines of science. Initiatives and strategic processes of change have led to the term "professional competence" to be part of a discourse and innovative training proposals more "professional" such as: the rapprochement between the labor world and education/training; the adaptation of workers to technology changes and social organization of production and work; the renovation of education/ training institutions, of professors /instructors, of the educational/training offer itself; and of the methods of acquisition and recognition of occupational qualifications [1], [2], [3], [4].

This renewal of approaches has led us to revise the two most comprehensive multidisciplinary databases: "Scopus" and "Web of Science", and the research literature of professional competence from 1950 to 2012, in order to define the models in which they are based and to be able to have a visual outline of the state of the professional competence art. Through scientific maps generated by specialized software the display of information is achieved: Citespace II and VosViewer.

Eight models were found which are algorithmically classified based on the characteristics, research themes in common and the relationships established by the authors in formulating hypotheses and in developing their research. For every model a description of their characteristics, findings and principal representatives were presented. This was done in order to establish which features are the most important for training in higher education in engineering and thereby find professional competence coding which are useful for the training of engineers.

The results lead the researchers to consider, as suitable, three encodings competence: CDIO (from the Massachusetts Institute of Technology MIT) based on the life cycle of a process: Conceive, Design, Implement and Operate. The second from the Project Management of International Project Management Association (IPMA), and the Tuning Project for Latin America. The comparison of encodings reveals which one that will have better results in the training of engineers in Latin America.

II. METHODOLOGY

The methodology for reviewing the state of the art of professional competence through the analysis of scientific domains is based on the methodologies proposed by Börner, Chen and Boyack [5] Marsden [6] and McCain [7] including: a) Previous bibliographic analysis, b) Selection of sources and data extraction, c) Quality of data, d) Analysis level and software selection, and e) information display and interpretation. The work review of Sergio Tobon [7], of Weinert [9] and of Guerrero, De los Rios & Diaz-Puente [10] are highlighted in the literature review. In the data extraction 3641 documents of Scopus and 1279 documents of Web of Knowledge were collected.

The level of analysis of this study involves a mixed co-citation of documents [11], [12], [13] and co-occurrence of words [14], [15]. By using the software Citespace II, considered the most appropriate for our level of analysis, 2 graphs (see Figure 1 and 2) that are interpreted in the results section were made.




For this analysis, it is important to take into account the following [16]: a) The scientific papers are represented by nodes, b) nodes with high relevance are highlighted in the chart with a purple outer ring b) the radius of the nodes represents the level of citation thereof, c) the node citation history is represented by colored rings around the node, d) The color of the relations between two nodes represent the year that both nodes were cited by other nodes. e) The color scale used is shown at the bottom of each graph.

III. RESULTS In Figure 1 and 2, 8 groups of scientific papers are identified. 5 of these groups related to professional competence

approaches described by Guerrero, De Los Rios and Diaz Puente [10]: # 1 individual behavioral competence, # 2 competence in the workplace, # 3 cognitive and motivational competence, # 4 integration of competence and #5 core of competence in organizations.

Figure 1. Mixed analysis of co-citation of documents and co-occurrence of words - Web of Science

Figure 2. Mixed analysis of co-citation of documents and co-occurrence of words - Scopus




In Group # 1 McClelland [17], Boyatzis [18] Spencer [19] are referred and have a high degree of centrality and maintain relationships of co-citation with at least one member of the other groups, i.e. in research related to professional competence the behavioral approach is considered. As Guerrero [10] refers the research of these authors reflect on the individual's behavior as a major factor in the performance of tasks that helps obtain specific results in certain contexts.

In Group # 2 Taylor [20] is identified as lead author and the NVQs documented by Fletcher [21] who presents the overview and key issues of NVQ movement to create, implement and maintain a standard competence-based program. In this approach competence is established from the essential functions of the individual which contribute significantly to the desired results. Hyland’s work [22]; he exposes the limitations of the work approach and Sandberg’s work [23], who through his results shows that the particular way of conceiving work, defines certain essential attributes and organizes them in a distinctive structure of competence at work.

In Group # 3 Bloom’s work is identified and described through Krathwohl’s reflection [24]: Bloom's taxonomy. This small group is closely related to the group # 6 due to the contribution of Bloom's taxonomy to examine the importance, curriculum alignment and educational opportunities in order to improve the planning of the curriculum. In this group Michael Eraut’s work [25] is framed; he analyzes the different types of knowledge and know-how used by professionals in their work; Winograt’s work [26] who described the person’s cognitive processes; and Polanyi’s work [27] with his "tacit knowledge".

In Group # 4 the contributions of Schon [28] and Cheetham [29] are mainly identified; they consider the competence as the result of a mixture of underlying personal issues. This group is related to group # 2, # 3, # 6 and # 1 as it integrates different approaches in a complex set which is called meta-competence, which determine the existence of functional cognitive competence, of behavior and ethical values.

In Group # 5 the work of Prahalad and Hamel [30], [31] are identified; they focus on the core organization competence which seek to generate competitive advantages, promote learning and developing of new skills. In this group Wernerfelt’s work [32] is highlighted with his company resource-based theory; Grant’s [33] and Barney’s work [34] with the approach of the business strategy formulation by effective use of resources and capabilities; and the contributions of Vidal-Gomez [35] to provide a framework for identifying competence in organizations.

Group # 6 is related to the competence formation in higher education, where Biggs [36] is identified as the main author with his most influential contribution referred to "constructive alignment" to achieve the development of students’ skills. Here Barnett’s work [37] is also framed; he suggested that the notions of competence were totally inadequate for higher education; Hackett's work [38] which describes two training approaches in higher education: training based on competence and reflective practice; Zimmerman’s contributions [39] in the reflection of self-regulation to redirect the thoughts, feelings and actions of students towards the achievement of the objectives from a cognitive, motivational and behavioral view; Sampson’s contribution [40] with its standard metadata model for the description of skills in formal education.

Group # 7 is related to the competence from the perspective of industrial and organizational psychology, where Shippmann’s work [41] is mainly highlighted with his analysis of competence models through 10 scale levels which are being used in the work evaluation, in new models of competence and in the development of standards for practice. The contributions of authors like Athey [42], Blancero [43] Lucia [44], Mansfield [45], Mirabile [46] and Rodriguez [47] are also found. They described the competence models to promote professional development and the need of a consistent and systematic strategy of application.

In Group #8 competence architecture is studied from the perspective of Engineering and Technology. The main authors in this group are: Hakkarainen [48] who introduced the concept of innovative communities, generators of competence. Draganidis [49] who concluded that technology plays an important role in the evolution of management systems for competence; and Jansma [50], who develops a competence list of systems engineers.




TABLE 1 COMPARISON OF APPROACHES OF COMPETENCE

Mod

els o

f Com

pete

nce b

ased

on

Characteristics Area Approach Related institutions

Information Systems Restrictions Beginning

Place of work

It is established from the essential functions of the individual contributing significantly to the desired results. The role of the worker must be understood in relation to the environment and other functions.

Labor Empiricist QCAD, Ofqual NVQ – GCSE

It analyzes business functions and not human competence. The objectives and functions of the company are formulated in terms of their relationship with the environment.

The United Kingdom

Behavioral theory

This approach prevails behavior of individuals in the task performance and will see specific results in a given context. Results-oriented standards. Superior performance specifications defined by educational research.

Labor / Educational Behaviorist NCEE – NCCA -

ICE SCANS - PMI

It preponderates the observation of the people’s behavior in confronting the task from the description of what he/she can do and no what he/she actually does, regardless of other personal dimensions.

The United States

Business strategy

The competition is a reality that helps direct the company efforts on a given route, and therefore requires certain skills of its participants. It introduces the Core Competence concept.

Labor Behaviorist - -

The approach is proposed as a method for achieving competitiveness. Managers can lose opportunities to achieve a higher performance by focusing its efforts on some competence.

Japan, USA

Cognitive - motivational

The competence are attributed to the cognitive activity and motivational components of the individual. Furthermore, by identifying competence and indicators it is based on N. Bloom's taxonomy, the work of Piaget and Vygotsky.

Educational Constructivist,

Rationalist, Empiricist

- -

This thorough approach is associated with a highly comprehensive and meaningful learning; but this need not necessarily lead to good professional performance

USA and Europe.

Holistic Approach

The education of a critical and reflective individual, meaningful learning and innovative in terms of collaboration, co-leadership of the learner and trainer. Development of basic, transferable and transferable competence are essential aspects of this approach.

Labor / Educational

Gestalt, Systemic,

Existentialist IPMA 4-L-C system

It is more complex, looking at all dimensions of the individual, and subsumes the previous levels within all of that representation.

Europe and USA




TABLE 1 COMPARISON OF APPROACHES OF COMPETENCE

(Continue)

Characteristics Area Approach Related institutions

Information Systems

Restrictions Beginning

Mod

els o

f Com

pete

nce b

ased

on

Competence is greater than a skill; it includes knowledge, attitudes which are connected with work performance and can be improved and even achieve excellent professional performance when these constitute an integrated whole. Human Resources Management requires competency models for effective consistency, continuity and performance.

Labor Systemic / Interpretative ETED “bilan de

compétences”

Although it goes beyond the reductionist vision of the working approach, there is a strong contextual dependence of attributes, obtained through the worker’s experience (access through the subject). There is difficulty in generalizing the results.

France, Austria.

Place of work

Here competence are seen as complex processes that people put into action-action-creation, to solve problems and do activities (of everyday life and in the labor-professional context), contributing to the construction and transformation of reality. The competence involve people as agents of social wellness capable of performing in an unknown future.

Educational / Social

Socio-constructive Cedefop, HBO KMK, WEB

There is the question of how to determine if the person has reached competition or not. Competence development is time consuming, and some skills are only acquired after the Higher Education, which makes it difficult the evaluation of continuous learning.

Netherlands, Germany

Behavioral theory

Here the role of technology and engineering is highlighted; apart from being an innovative component, it is a component associated with the knowledge, training and aptitude of people. It promotes the concept of creativity that includes ongoing development, the relationship with the environment, and use of existing resources. Technology plays an important role in the evolution of management systems for skills and lifelong learning.

Labor Constructivist / Behavioral - -

It always has in mind a trio in perfect communion elements: people, technology and processes, ignoring social and innermost issues of the person.

Europe




The Table 1 above presents a comparative table of eight approaches of professional competence described as a summary: the characteristics, the area in which they operate, the philosophical approach to which they belong, certification systems related to the model, the limitations and the country where they originate.

From the comparative approaches it is emphasized that the holistic approach is the most appropriate for competence coding for higher education in engineering. Here professionals are increasingly required and bring into action a complex mixture of knowledge, skills, attitudes and values which, depending on the needs of a particular context, specific attributes are involved for an intelligent performance, helping to place ethics and values as part of the competent performing elements and the need for reflective practice. On the other hand, they have to be prepared for lifelong learning and must also have good communication and teamwork, where technical skills are not enough in today's world [51], [52], [53], [54] [55], [56].

However to achieve this demand, higher education institutions required learning methodologies different from today’s, where actors and responsible of institutions carry out a set of activities to achieve the best training of future professionals [56] [54]. In this context, Education in engineering should be more holistic; it must have a body of knowledge and skills which are based on a set of coded competence, such as competence in the area of subject matter as well as general competence on business and social contexts and activity, and understanding of the characteristics of future professional [57 [58], [59].

In the holistic approach IPMA world certification system [60] is emphasized. This proposes its model in 4 levels (4-LC system): IPMA Levels A, B, C and D, which through the "Eye of the competition" show the three dimensions of professional competence: contextual and behavioral techniques. Within these three dimensions there are 46 elements of competence (See Table 2) considered suitable for engineering students as previously mentioned.

TABLE 3

CODE OF IPMA COMPETENCE [60] 1. TECHNICAL COMPETENCE 2. BEHAVIOURAL COMPETENCE 3. CONTEXTUAL COMPETENCE

1.01 Success in Project Management 2.01 Leadership 3.01 Guidance to projects 1.02 Parties involved 2.02 Commitment and motivation 3.02 Guidance to programs

1.03 Project requirements and objectives 2.03 Self-control 3.03 Guidance to portfolios 1.04 Risk and opportunity 2.04 Self-confidence 3.04 Implantation of projects, programs and portfolios

1.05 Quality 2.05 Relaxation 3.05 Permanent organization 1.06 Project organización 2.06 Open attitude 3.06 Business

1.07 Teamwork 2.07 Creativity 3.07 Systems, products and technologies 1.08 Problem solving 2.08 Guiding to results 3.08 Personnel management 1.09 Project structures 2.09 Efficiency 3.09 Health, safety and environment

1.10 Scope and deliverables 2.10 Consultation 3.10 Finances 1.11 Time and project phases 2.11 Negociation 3.11 Legal

1.12 Resources 2.12 Conflicts and crisis 1.13 Costs and financing 2.13 Reliability

1.14 Procurement and Contracts 2.14 Appraisal of values 1.15 Changes 2.15 Ethics

1.16 Control and reports 1.17 Documentation and Information

1.18 Communication 1.19 Launching

1.20 Closing Furthermore, within engineering, necessary skills have been detected in modern engineers. Those competence have been defined in one of the most serious work: the proposal CDIO (Conceive, Design, Implement and Operate) of the Massachusetts Institute of Technology (MIT). This proposal has three general objectives: master a thorough knowledge of basic techniques, leadership in the creation and operation of new products, processes and systems and understand the importance and strategic impact of research and technological development in society, which are proposed through the development of standards and the CDIO syllabus. This syllabus defines the competence that students must have when finishing their training as engineers, being the result of the conjunction of interests of all those involved in engineering activity. In the definition of competence, participation is used as a key tool through surveys: faculty, industry, alumni, and among others. In Table 3, the first and second level competence are shown defined by CDIO and organized into four areas of training: technical knowledge and critical thinking, professional and personal skills, interpersonal skills and CDIO (Conceive-Design-Implement-Operate) [60] [61].




TABLE 4 OBJETIVES OF FIRST AND SECOND LEVEL OF CDIO SYLLABUS

1 TECHNICAL KNOWLEDGE AND REASONING 3 INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION

1.1 Necessary basic knowledge of underlying sciences 3.1 Teamwork 1.2 A body of knowledge of the Basic Engineering 3.2 Communication 1.3 Knowledge of the fundamentals of Advanced Engineering 3.3 Mastery of a foreign language

2 SKILLS AND PERSONAL AND PROFESSIONAL ATTRIBUTES 4 CONCEIVE, DESIGN, IMPLEMENT AND OPERATE SYSTEMS IN THE COMPANY AND SOCIAL CONTEXT

2.1 Engineering Reasoning and Problem Solving 4.1 Social and external context 2.2 Experimentation and knowledge discovery 4.2 The contexts of businesses and companies 2.3 Systemic thinking 4.3 Conceive

2.4 Personal skills and attitudes 4.4 Design

2.5 Professional skills and attitudes 4.5 Implement 4.6 Operate

With the revision of the context of competence approaches made here and the presentation of two competence encodings defined above, the authors proceed to make comparisons between IPMA and CDIO proposals to try to determine the best competence coding for engineering education in Latin America, that is why a common denominator is used : The Tuning America Latina project.

The Tuning America Latina project is one of the most serious work undertaken in the definition of competence for the training of professionals. This project is intended to "tune" educational structures of Latin America initiating a debate whose aim is to identify, exchange information and improve cooperation between institutions of higher education for the development of quality, effectiveness and transparency [51]. The Tuning America Latina looks for common points of reference focused on competence, presenting a final list of 27 generic competencies (see Table 4), which are important in a changing society where demands tend to be in constant reformulation [63].

TABLE 4 COMPETENCE TUNING-AMERICA LATINA

1) Capacity for abstraction, analysis and synthesis 14) Capacity for creativity. 2) Ability to apply knowledge in practice 15) Ability to identify, propose and solve problems

3) Ability to organize and plan time. 16) Ability to make decisions. 4) Knowledge the study field and the profession 17) Teamwork skills

5) Social responsibility and civic engagement 18) Interpersonal skills. 6) Oral and written communication skills. 19) Capacity to motivate and lead to common goals

7) Communication skills in a second language. 20) Commitment to environmental protection. 8) Information and communication technology skills. 21) Commitment to their sociocultural environment.

9) Research capacity. 22) Value and respect for diversity and multiculturalism. 10) Ability to learn and update knowledge continually. 23) Ability to work in international contexts.

11) Skills for searching, processing and analyzing information from various sources. 24) Ability to work autonomously.

12) Critical capacity and self-criticism. 25) Ability to formulate and manage projects 13) Ability to act in new situations. 26) Ethical commitment

27) Commitment to quality. Table 5 shows how the CDIO competence are reflected in the competence Tuning AL. It is also noted that there are two Tuning competence which are not clearly addressed by CDIO: 24. "Ability to work autonomously". It could be attributed to element 2.4. "Interpersonal skills and attitudes" of CDIO but it is not expressed clearly and it is more widespread. It is noted that Item 3. "Ability to organize and plan the time", from Tuning generic competences, it is not treated exactly in the competent elements in first and second level of CDIO. But if we look at the elements of the third and fourth level, one could say that this 3 competence is developed from Tuning 3. However Tuning better defines and clearly such an important generic competence and not as a detail of that competence.

With regard to the comparison with IPMA, the competence defined by Tuning undoubtedly are incorporated in all the competence elements defined by IPMA for Project Management. Competence 7 of Tuning, to master a second language, it is not expressly stated in IPMA and the competence element 1.18 will have to be emphasized. Thus, Tuning competence are more complete in that area.




IV. CONCLUSIONS

By going beyond traditional methods of study bibliographies, a more refined answer is provided to analyze large sets of data. Also there is convergence work around professional competence, finding 8 groups formed from common characteristics and research topics. These are: a) The behavioral competence, b) Competence in the workplace, c) Cognitive and motivational competence, d) Holistic approach of competence, e) Competence Core as business strategy, f) Competence in higher education g) Competence in industrial psychology, h) Competence in the context of engineering and technology.

The holistic approach is the least reductionist of the models studied and analyzed and contains essential aspects which facilitate direct application to the professional competence in higher education of engineering in which the graduate profile should contain key elements of knowledge, skills and professionals abilities, and especially attitudes and values, within a holistic approach of professional competence.

The authors state that Tuning-AL competence coding can be used for the holistic training of engineering students from Latin America to take on the challenge of developing of competence required in the professional training process. Therefore, it is necessary to design and complement an educational model whose curriculum is based on these competence leading to the development of skills, knowledge and attitudes of undergraduates that society needs.




TABLE 5 COMPARISON OF TUNING LATIN AMERICA COMPETENCE AND IPMA AND CDIO COMPETENCE ELEMENTS




REFERENCES [1] Arbizu Echavarri, F. (2002). Competencias profesionales. Enfoques y modelos a debate. Montevideo: CINTERFOR. [2] CINDA. (2000). Las nuevas demandas del desempeño profesional y sus implicaciones para la docencia universitaria. Santiago de Chile:

Ministerio de Educacion. [3] Guerrero, D., De los Ríos, I., & Díaz-Puente, J. (2008). Competencias profesionales: marco conceptual y modelos internacionales. II

Jornadas de intercambio de experiencias en Innovación Educativa (INECE) (p. 17). Madrid: UPM. [4] CIDEC. (1999). Competencias profesionales, enfoques y modelos a debate. Vitoria-Gasteiz: Gobierno Vasco. [5] Börner, K., Chen, C., & Boyack, K. (2003). Visualizing knowledge domains. Annual Review of, 37, 179-255. [6] Marsden, P. (1990). Network data and measurement. Annual Review of Sociology, 16, 435-463. [7] McCain, K. (1990). Mapping authors in intellectual space: a technical overview. Journal of the american society for information science,

433-443. [8] Tobón, S. (2006). Formación Basada en Competencias. Pensamiento complejo, diseño curricular y didáctica. Bogotá: Ecoe Ediciones

Ltda. [9] Weinert, F. E. (2004). Concepto de competencia: Una aclaración conceptual. In D. Simone Rychen, & L. Hersh Salganik, Definir y

seleccionar las competencias fundamentales para la vida (pp. 94 - 127). México: Fondo de Cultura Económica. [10] Guerrero, D., De los Ríos, I., & Díaz-Puente, J. (2008). Competencias profesionales: marco conceptual y modelos internacionales. II

Jornadas de intercambio de experiencias en Innovación Educativa (INECE) (p. 17). Madrid: UPM. [11] Garfield, E. (1998). Mapping the world of science. Retrieved febrero 23, 2012, from

http://www.garfield.library.upenn.edu/papers/mapsciworld.html [12] Small, H., & Griffith, B. (1974). the structure of scientific literature I: Identifying and Graphing Specialties. Science Studies, 17-40. [13] Small, H. (1973). Co-citacion in the scientific literature: a new measure of the relationship between two documents. Journal the

American Society for Information Science (JASIS) 24, 265-269. [14] Leydesdorff, L., & Welbers, K. (2011). the semantic mapping of words and co-words in contexts. Journal of Infometrics, 5, 469-475. [15] Ortega Priego, J., & Aguillo, I. (2006). Análisis de co–enlaces: una aproximación teórica. El profesional de la información, 15, 270-277. [16] Synnestvedt, M., Chen, C., & Holmes, J. (2005). CiteSpace II: Visualization and Knowledge Discovery in Bibliographic Databases.

AMIA 2005 Symposium Proceedings, (pp. 724-728). [17] McClelland, D. (1973). Testing for competence rather

than for intelligence. American Psychologist Vol.20, 321-33. [18] Boyatzis, R. (1982). The competent manager A Model for Effective Performance. New York: John Willey & Sons. [19] Spencer, L., & Spencer, S. (1993). Competence at work: models for superior performance. New York: John Wiley and Sons. [20] Taylor, F. W. (1980). Principios de la administración científica. In B. d. económicas, Principios de la administración científica.

Administración industrial y general. Buenos Aires: El Ateneo. [21] Fletcher, S. (1991). NVQs Standards and Competence. A Practical Guide for Employers, Mangers and Trainers. London: Kogan Page. [22] Hyland, T. (1993). Competence, Knowledge and Education. Journal of Philosophy of Education, 57-68. [23] Sandberg, J. (2000). Understanding Human Competence at Work: An Interpretive Approach. Academy of Management Journal V43, 9-

25. [24] Krathwohl, D. (2002). A revision of bloom's taxonomy: An overview. THEORY INTO PRACTICE, V41, 212-218. [25] Eraut, M. (1994). Developing Professional Knowledge and Competence. London: Falmer Press. [26] Winograd, T. (1987). Understanding Computers and Cognition: A New Foundation for Design. Addison-Wesley Professional. [27] Polanyi, M. (1966). The Tacit Dimension. First published Doubleday & Co. [28] Schon, D. (1987). The Reflective Practitioner: How Professionals Think In Action. . San Francisco: Jossey Bass. [29] Cheetham, G., & Chivers, G. (1998). The reflective (and competent) practitiones: a model of professional competence which seeks to

harmonise the reflective practitioner and compentence-based approaches. Journal of European Industrial Training, vol. 22(n° 7), 267-276. Obtenido de EBSCO Business Source Complete.

[30] Prahalad, C. K., & Hamel, G. (1990). The Core Competence of the Corporation. Harvard Business Review, 79-91. Obtenido de EBCOHost Business Source Complete.

[31] Hamel, G., & Prahalad, C. (1994). Competing for the future. Harvard Business School Press. [32] Wernerfelt, B. (1995). The Resource-Based View of the Firm: Ten Years After. Strategic Management Journal, V16, 171-174. [33] Grant, R. (1991). : The Resource-Based Theory of Competitive Advantage: Implications for Strategy Formulation. California

Management Review, v33, 114-135. [34] Barney, J. (1991). Firm Resources and Sustained Competitive. Journal of Management, 99-120.




[35] Vidal-Gomel, C., & Samurcay, R. (2002). Qualitative analysis of accidents and incidents to identify compete ncies. The electrical

systems maintenance case. Safety Sci, 479-500. [36] Biggs, J., & Tang, C. (2011). Teaching for Quality Learning at University. Open University Press, 4ta edición. [37] Barnett, R. (1994). The Limits of Competence: Knowledge, Higher Education and Society. Open Univ Pr. [38] Hackett, S. (1997). Educating for competency and reflective practice: fostering a conjoint approach in education and training. Journal of

Workplace Learning, 103 - 112. [39] Zimmerman, B. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. Pintrich, & M. Zeidner, Handbook

of self-regulation (pp. 13-39). San Diego: Academic Press. [40] Sampson, D., Karampiperis, P., & Fytros, D. (2007). Developing a common metadata model for competencies description. Interactive

Learning Environments, 137-150. [41] Schippmann, J. (2000). The practice of competency modeling. Personnel Psychology, V53, 703-740. [42] Athey, T. (1999). Emerging competency methods for the future. Human resource management, 231. [43] Blancero, D. (1998). Key competencies for a transformed human resource organization: Results of a field study. Human Resource

Management, 383-403. [44] Lucia, A. (1999). The Art and Science of Competency Models. San Francisco: Jossey-Bass. [45] Mansfield, R. (1996). Building competency models: Approaches for HR professionals. Human Resource Management, 7-18. [46] Mirabile, R. (1997). Everything you wanted to know about competency modeling. Training & Development Journal: 73-77. [47] Rodriguez, D. (2002). Developing competency models to promote integrated human resource practices. Human Resource Management,

v41, 309–324. [48] Hakkarainen, K. (2004). Communities of networked expertise: professional and educational perspectives. Amsterdam: Elsevier. [49] Draganidis, F., & Mentzas, G. (2006). Competency-based management: A review of systems and approaches. Information Management

&Computer Security, 51-64. [50]Jansma, P. (2006). Advancing the Practice of Systems Engineering at JPL. IEEE Aerospace Conference. Montana. [51] Palma, M., De los Rios, I., Miñán, E., & Luy, I. (2012). Hacia un Nuevo Modelo desde las Competencias: la Ingeniería Industrial en el

Perú. Tenth LACCEI Latin American and Caribbean Conference. Panama: LACCEI. [52] Palma, M., De los Ríos, I., & Miñán, E. (2010). Generic competences in engineering field: a comparative study between Latin America

and European Union. Procedia Social and Behavioral Sciences, 576-585. [53] Ramírez, M. (2009). La importancia del desarrollo de competencias del futuro ingeniero. 3er Foro Nacional de ciencias básicas:

formación científica del ingeniero. México D.F.: Universidad Nacional Autónoma de México. [54] Tabares Mesa, J., & Londoño Vélez, B. (1991). Propuesta para innovar en unas metodologías de enseñanza universitaria. Revista

Educación y Pedagogía N°62, 49-65. [55] Maffioli, F., & Giuliano, A. (2003). Tuning engineering education into the European higher education orchestra. European Journal of the

Engineering Education, 251-273. [56] Shuman, L., Atman, C., Eschenbach, E., Evans, D., Felder, R., Imbrie, P., et al. (2002). The future of engineering education. 32nd

ASEE/IEEE Frontiers in Education Conference (pp. T4A-1– T4A-15). Boston: IEEE. [57] Kans, M. (2012). Applying an innovative educational program for the education of today’s engineers. Journal of Physics: Conference

Series 364. [58] Astigarraga, T., Dow, E., Lara, C., Prewitt, R., & Ward, M. (2010). The Emerging Role of Software Testing in Curricula. Transforming

Engineering Education: Creating Interdisciplinary Skills for Complex Global Environments. Dublin: IEEE. [59] Andersen, N., Yazdani, S., & Andersen, K. (2007). Performance Outcomes in Engineering Design Courses. Journal of professional

issues in engineering education and practice. [60] IPMA. (2009). Nacional Competence Baseline. V3.0, Revisión. Valencia: Asociación Española de Ingeniería de Proyectos [61] Bragós Bardía, R. (2012). Las competencias del profesorado en el entorno CDIO. Revista de Docencia Universitaria, 57-73. [62] Crawley, E., Malmqvist, J., Lucas, W., & Brodeur, D. (2011). The CDIO Syllabus v2.0 An Updated Statement of Goals for Engineering

Education. Proceedings of the 7th International CDIO Conference. Copenhagen: Technical University of Denmark. [63] Proyecto Tuning. (2007). Informe Final – Proyecto Tuning – América Latina 2004-2007. Retrieved from Reflexiones y perspectivas de

la Educación Superior en América Latina: http://tuning.unideusto.org/tuningal


______________________________________________________________________________________________________ IJIRAE: Impact Factor Value - ISRAJIF: 1.857 | PIF: 2.469 | Jour Info: 4.085 | Index Copernicus 2014 = 6.57


Study of the Effect of Length and Inclination of Tube settler on the Effluent Quality

Kshitija Balwan, Aarju mujawar, Dhanashri Bhabuje, Manisha karake Abstract-- Installation of new treatment plants to meet the increased demand is beyond the reach of most of the local bodies and government as well. Hence ways and means are to be explored to augment water treatment capacity and to improve the performance of existing water treatment plants. Tube settler systems are inexpensive solution for drinking water and wastewater plants to increase treatment capacity of clarifier, improve effluent water quality, and decrease operating costs. Tube settlers use multiple tubular channels sloped at an angle of about 45o to 60o and adjacent to each other, which combine to form an increased effective settling area. This is combining to form an increased effective settling area. Current study focuses on the study made to understand the effect of length and inclination of tube settler on the effluent quality through the pilot plant study. The circular tubes of 45mm diameter were used with inclination of 45o and 60o. Length of tube was varied as 60cm, 50cm and 40 cm.

Key words: Clarification, Tubesettler, removal of turbidity, inclination, length.

I. INTRODUCTION Most of the municipal towns have been covered with drinking water supply schemes and conventional treatment plants. Due to increased population, urbanization and industrialization, demand for water supply is increasing for almost every town. Installation of new treatment plants to meet the increased demand is beyond the reach of most of the local bodies and government as well. Hence ways and means are to be explored to augment water treatment capacity and to improve the performance of existing water treatment plants. Tube settler systems are inexpensive solution for drinking water and wastewater plants to increase treatment capacity of clarifier, reduce new installation footprints, improve effluent water quality, and decrease operating costs. Constructed of lightweight PVC, tube settler modules can be easily supported with minimal structures that often incorporate effluent troughs and baffles. Modules are available in a variety of sizes to fit any tank geometry and tube lengths to accommodate a wide range of flows. The work focuses on the study made to understand the effect of length and inclination of tube settler through the pilot plant study. The pilot scale model was installed at Ichalkaranji municipal water treatment plant and the flocculated water was used for analyzing the effect of length and inclination of Tube settler.

A. THE OBJECTIVES OF THE STUDY WERE: i. To design and construct pilot scale model. ii. To study the effect of length of tubes (60, 50, 40cm) and inclination of tubes (45, 60 degree) on removal of turbidity.

B. MATERIALS AND METHODS: i. The pilot scale model was prepared and installed at Ichalkaranji municipal water treatment plant.

Fig.1 Pilot scale model installed at Ichalkaranji WTP




The model had one closed base tank which was connected to influent water, which was the aerated and coagulated water. The base tank was connected to the bottom of four PVC tubes of 4.5cm diameter, representing the tubesettler. The length and inclination of these pipes were adjustable. The direction of flow was kept similar to that of conventional clarifier i.e. upward. The effluent water was collected by small collector basin and finally stored in small collector drum.

The turbidity of influent as well as effluent water was measured using Nephelometer. Lengths of tubes were kept as 40cm, 50cm and 60cm, while the inclination was kept as 45o and 60o. Thus there were six combinations tried. Combinations-

Length 40cm- with inclination of 45o and 60o. Length 50cm- with inclination of 45o and 60o. Length 60cm- with inclination of 45o and 60o.

The surface over flow rate was kept similar to that of conventional clarifier i.e 35000Lit/m²/hr.

The turbidity of influent as well as effluent was measured and compared with the turbidity of effluent produced by conventional clarifier used at Ichalkaranji WTP. The each run tried was of 120min.

II. RESULTS AND DISCUSSION: For each combination the turbidity of influent and effluent with and without tube settler were measured. The observations of various combinations are as follows:

Graph No. 1. The graph showing Turbidity Vs Time for Length 60 cm Inclination 60°

Graph No.2. The graph showing observations for Length 60 cm Inclination 45°

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Graph No. 3 The graph showing observations For Length 50cm Inclination 60°

Graph No. 4. The graph showing observations for Length 50cm Inclination 45°

Graph No. 5 The graph showing observations for length 40cm Inclination 60˚

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Graph No.6. The graph showing observations for Length 40cm Inclination 45°

III. SUMMARY OF RESULTS:

SR. NO. INCLINATION LENGTH IN CM

REMOVAL OF TURBIDITY IN %

(CONVENTIONAL)

REMOVAL OF TURBIDITY IN % (TUBE SETTLER)

REMARK

1 45° 40 60 70 - 2 45° 50 60 76 - 3 45° 60 60 80 Optimum combination 4 60° 40 60 68 - 5 60° 50 60 74 - 6 60° 60 60 78 -

Table no.01 shows the results of turbidity with different inclinations & lengths.

IV. CONCLUSIONS

After successful completion of project we come to the following conclusions: 1. Increasing the length of tube settler, results in higher turbidity. 2. Decreasing the inclination of tubes, results in higher turbidity 3. Out of 6 combinations tried, the optimum result was observed for the length 60 cm and inclination 45°.

V. FUTURE SCOPE

1. Various shapes of tube are currently available in market and also used to improve capacity as well as performance of clarifier so those shapes should be used in comparison with circular pipes.

2. Higher length as well as steeper inclination can also results in higher head loss so proper pilot scale studies to find out the limiting length and appropriate inclination should be studied.

ACKNOWLEDGEMENT

Authors of the paper are very much thankful to the Hydraulic Engineer, Ichalkaranji Municipal Corporation, Mr. Balasaheb Choudhari and Mr. Bajirao Kamble for allowing them to work at Ichalkaranji WTP and also for providing every possible help during the study period.

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REFERENCES

[1]. BRENTWOOD industries www.brentwood.com (August 2011) comparison between the tube settler and conventional settling. Mannual on water supply and treatment, 3e,Ministry of urban development, New Delhi.

[2]. Prof. Bilge A. K. of Marmara University Department of Environmental Engineering Istanbul, Turkey. parallel plat settler and incline tube settler.

[3]. CORIX Water Systems www.corix.com provides packaged water treatment plants based on the tube settler (ST) process. [4]. Prof. A. Evren Tugtas.(2014) discussed about the design criteria of the inclined tube settlers.




Power Quality Improvement Using GUPFC

D.Rajesh Reddy Dr.R.Veera Sudarasana Reddy Assistant.Professor / EEE Principal

Narayana Engineering College, Gudur Narayana Engineering College, Gudur Andhra Pradesh Andhra Pradesh

Abstract — The power quality issue will take new dimension due to power system restructuring and shifting trend towards distributed generation. Huge loss in terms of time and money has made power quality problems a major anxiety for modern industries with non-linear loads in electrical power system. Power quality consists of a large number of disturbances such as voltage sags, swells, harmonics, notch, flicker, etc. Power quality problems can be mitigated by many methods but most appropriate solution to mitigate these problems is FACTS devices. In this paper a brief survey of FACTS devices are presented which are used to mitigate power quality problems.

Keyword s— GUPFC, Restructuring, Distributed Generation, Sag, Swell, Harmonics, Notch, Flicker, PCC, FACTS devices.

INTRODUCTION

A power quality issue is an issue that is becoming increasingly important to electricity consumers at all levels of usage. PQ related issues are of most distress because of the extensive use of electronic equipment. In arrears to this, various PQ issues arises like voltage sag or dip, very short and long interruptions, voltage spike, voltage swells, harmonic distortion, voltage fluctuation, noise, voltage unbalance and altered our power system. Power quality problems have been attracting the eye of researches for decade. The presence of voltage disturbances at the point of common coupling (PCC) results in malfunction of sensitive industrial instrumentality, that turn out grid part failures, such as transformers, and economical losses. FACTS devices are the possible answer to shield sensitive loads against the most significant voltage disturbances, voltage harmonics, imbalance and sags [1].

Definition of power quality may vary from person to person because we cannot define what power quality we only define what good is or bad power quality is as we can see that two identical devices or pieces of equipment might react differently to the same power quality parameters due to differences in their manufacturing or component tolerance [2]. According to institute of Electrical and Electronic Engineers (IEEE) Standard power quality is defined as a, “the concept of powering and grounding sensitive electronic equipment in a manner suitable for the equipment”. The focus of this survey is on the use of FACTS devices in mitigation of PQ problems.

FACTS DEVICES A . Introduction Studies of power quality phenomena have emerged as a main subject in recent years due to renewed interest in improving the excellence of the generation of power. As sensitive electronic equipment continues to proliferate, the studies of power quality have been further emphasized [1]. There are two main ways for improving power quality:

a. The cost-free improving power quality. b. Not cost-free improving power quality. The cost-free means for improving power quality include actions like: 1. Using of tap changing transformers. 2. Operation of conventional compensating devices for example capacitor bank 3. Control by FACTS devices Flexible AC Transmission Systems (FACTS) forms a new domain in power system control engineering, using power electronic devices and circuits and the more recent existing technologies in automatic control. The two main objectives of FACTS are:

a) To increase the capability of transmission capacity of lines. b) Control power flow over designated transmission, electronically and statically, without need of operator’s actions and without need of mechanical manipulations or conventional breakers switching.

B. Main Sources, Causes and Effects Of Electrical Power Quality Problems Power Quality is “Any power problem manifested in voltage, current, or frequency deviations that result in failure or disoperation of customer equipments”. Power systems, ideally, should provide their customers with an uninterrupted flow of energy at smooth sinusoidal voltage at the contracted magnitude level and frequency [3-4]. Some of the primary sources of distortion can be identified as below:




Non–Linear Loads Power Electronic Devices IT and Office Equipments Arcing Devices Load Switching

C. Mitigation Echniques Using Facts Devices

The dynamic voltage restorer (DVR) has become popular as a cost effective solution for the protection of sensitive loads from voltage sags and swells. The control for DVR based on dqo algorithm was discussed in [5]. Rosli Omar et. al [5] have described the problem of voltage sags and swells and its severe impact on nonlinear loads or sensitive loads. The proposed control scheme was simple to design. Simulation results carried out by Mat lab / Simulink verify the performance of the proposed method. S. Sadaiappan et. al [6] have used a series compensator (SC) to improve power quality was an isolated power system investigated. The role of the compensator is not only to mitigate the effects of voltage sag, but also to reduce the harmonic distortion due to the presence of nonlinear loads in the network. In this proposed method, a series compensator was proposed, a method of harmonic compensation is described, and a method to mitigate voltage sag was investigated by S. Sadaiappan [6].

Chong Han et al. [7] have proposed a method in which an electrical arc furnace (EAF) is a major flicker source that causes major power quality problems. In this proposed method, flicker mitigation techniques by using a CMC-based STATCOM was presented and verified through a transient network analyzer (TNA) system. The required STATCOM capacity was first studied through a generalized steady-state analysis. Second, the STATCOM control strategy for flicker mitigation is introduced, and simulation results are given. Finally, a TNA system of the STATCOM and an EAF system are designed and implemented. This paper deals with new technique of the simulation and analysis of Generalized Unified Power Flow Controller (GUPFC) or multi-line Unified Power Flow Controller (UPFC) which is the novel concept for controlling the bus voltage and power flows of more than one line or even a sub-network. In this paper Generalized Unified Power Flow Controller (GUPFC) has been analyzed for both open loop and close loop configuration.

GUPFC

Introduction of Generalized Unified Power Flow Controller (GUPFC) An innovative approach of utilization of complex FACTS controllers providing a multifunctional power flow management device was proposed in [8] and [9]. There are several possibilities of operating configurations by combing two or more converter blocks with flexibility. Among them, there is a novel operating configuration, namely the Generalized Unified Power Flow Controller (GUPFC) which is significantly extended to control power flows of multilines or a sub-network rather than control power flow of single line by a Unified Power Flow Controller (UPFC) or Static Synchronous Series Compensator (SSSC) [11]. A fundamental model of the GUPFC consisting of one shunt converter and two series converters which can be increase if needed as shown in fig.1. and variable magnitude and phase angle. One approach involves multi-connected,.

A MATHEMATICAL MODEL OF THE GUPFC A. The Equivalent Circuit of the GUPFC

The GUPFC with combing three or more converters working together extends the concepts of voltage and power flow con-trol beyond what is achievable with the known two-converter UPFC FACTS controller [7], [8].

Fig. 1. Operational principle of the GUPFC with three converters.




Fig. 2. The equivalent circuit of the GUPFC

The simplest GUPFC consists of three converters, one connected in shunt and the other two in series with two transmission lines in a substation [12].

It can control total five power system quantities such as a bus voltage and independent active and reactive power flows of two lines .In the steady state operation, the main objective of the GUPFC is to control voltage and power flow. The equivalent circuit of the GUPFC consisting of one controllable shunt injected voltage source and two controllable series injected voltage sources is shown in Fig. 2.

Such a GUPFC, which is shown in Fig. 1, is used to show the basic operation principle for the sake of simplicity. However, the mathematical derivation is applicable to a GUPFC with an arbitrary number of series converters. From fig.2.Real power can be exchanged among these shunt and series converters via the common DC link. The sum of the real power exchange should be zero if we neglect the losses of the converter circuits. For the GUPFC shown in Figs. 1 and 2, it has total 5 degrees of control freedom, that means it can control five power system quantities such as one bus voltage, and 4 active and reactive power flows of two lines. It can be seen that with more series converters included within the GUPFC, more degrees of control freedom can be introduced and hence more control objectives can be achieved. in Fig. 2 are shunt and series transformer impedances. The controllable injected voltage sources shown in Fig. 2 are defined as,

(1.1)

(1.2)

Where n=i,j…

B. Power Flow Equations of the GUPFC

According to the equivalent circuit of the GUPFC shown in Fig. 2, the power flow equations can be derived:

(2.1)




(2.2)

(2.3)

(2.4)

(2.5)

(2.6)

(2.7)

(2.8) where .

NUMERICAL EXAMPLES A. Test Systems

Test cases in this paper are carried out on the IEEE 30 bus system. The IEEE 30 bus system has 6 generators, 4 OLTC transformers and 37 transmission lines. The IEEE 118 bus system has 18 controllable active power generation, 54 controllable reactive power generation, 9 OLTC transformers, 177 transmission lines. For all cases in this paper, the convergence tolerances are 5.0e-4 for complementary gap and 1.0 e-4 (0.01 MW/Mvar) for maximal absolute bus power mismatch, respectively.

B. The IEEE 30 Bus System Results

In order to show the power flow control capability of the non-linear interior point OPF algorithm proposed, four cases based on the IEEE 30 bus system are carried out. In the discussion thereafter, the control settings of active and reactive power flow are referred to , , which are at the sending end of a line. Active power flow and reactive power flow at the sending end of a line are referred to , ( or ) since the sending end of a line is connected to bus ( or ). Case 1): This is a base case without GUPFC.

Case 2): This is similar to case 1 expect that there is a GUPFC installed for control of voltage of bus 12 active and reactive power flow of line 12-15 and line 12-16.the control setting of the bus voltage is 1.0 p.u.the control settings for active and reactive power flow of line 12-15 and line 12-16 are 25 MW+j5 Mvar and 10MW +j2Mvar respectively.

Case 3): It is similar to the case 2 except that second GUPFC is further installed for control of voltage at bus 10 and control of active and reactive power flow of line 10–21 and line 10–22. The control setting of voltage at bus 10 is 1.0 p.u. The control settings of active and reactive power flow are 10 MW 6 Mvar and 12 MW 4 Mvar for line 10–21 and line 10–22, respectively. The active power flow set-ting of line 10–21 is about 60% of the corresponding base case active power flow. While the active power flows setting of line 10–22 is about 160% of the base case active power flow.

Case 4): This is similar to the case 3 except that third GUPFC is further installed for control of voltage at bus 6 and control of active and reactive power flow of line 6–2 and line 6–8. The control setting of voltage at bus 6 is 1.0 p.u. The control settings of active and reactive power flow are 60 MW 4 Mvar, and 10 MW 4 Mvar for line 6–2 and line 6–8, respectively.




TABLE I - TEST RESULTS OF THE IEEE 30 BUS SYSTEM

C.

Discussion of the Results

From these results on the IEEE 30 bus system it can be seen:

1) Numerical results demonstrate the feasibility as well as the effectiveness of the GUPFC model established and the OPF method proposed.

2) The OPF with GUPFC can find a solution in reasonable iterations. The number of iterations for an OPF solution with the GUPFC devices is comparable with that of a base case OPF solution, which can be found in Tables I and II. It should be pointed out here that initialization of the GUPFC variables based on the analytical solutions de-rived in this paper is very helpful to improve the convergence characteristics of the OPF.

3) The GUPFC is a quite flexible and powerful FACTS con-troller. It can control bus voltage and active and reactive power flows of several lines simultaneously. It may be in-stalled in some central substations to manage power flows of multi-lines or a group of lines and provide voltage sup-port as well.

4) By using the GUPFC devices, the transfer capability of transmission lines can be increased significantly. Furthermore, by using the multi-line management capability of the GUPFC, active power flows on lines can not only be increased, but also be decreased with respect to operating and market transaction requirements in an open access environment. In the cases 3) and 4) above, such scenarios are simulated. Therefore, the GUPFC can be used to in-crease transfer capability and relieve congestion as well in power systems.

CONCLUSIONS

In this paper, we have reviewed the mitigation techniques using FACTS devices of various PQ issues like voltage sag or dip, very short and long interruptions, voltage spike, voltage swells etc. Power system and its equipment is badly affected to this PQ issues like breakdown of information technology equipment or may be stoppage of all equipment, circuit breakers trip without being overloaded, automated systems stop for no apparent reason, electronic systems work in one location but not in another location. A mathematical model of the Generalized Unified Power Flow Controller (GUPFC), which is suitable for power flow and optimal power flow study, is established. The model with one shunt converter and two or more series converters. Most of the research highlight on product innovation and cost reduction. But few of them focuses on studying the PQ related issues are of most distress because of the extensive use of electronic equipments. Here I have intended to propose a proper change in perspective of PQ. Numerical results based on the IEEE 30 bus system with various GUPFC devices demonstrate the feasibility as well as the effectiveness of the GUPFC and the OPF method proposed. It is obvious that the implementation principles of the GUPFC proposed can also be used in modelling other members of the Convertible Static Compensator (CSC) family in power Systems.

REFERENCES: [1]. R. K. Rojin “A Review of Power Quality Problems and Solutions in Electrical Power System”, International Journal of

Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 2, No. 11, pp. 5605-5614, 2013 [2]. Hingorani N.G., “Introducing custom power”, IEEE Spectrum, Vol. 32, No. 6, pp. 41–48, 1995. [3]. Rosli Omar and Nasrudin Abd Rahim, “Modeling and Simulation for Voltage Sags/Swells Mitigation Using Dynamic

Voltage Restorer (DVR)”, in preceding of Australasian Universities Power Engineering Conference, Sydney, NSW, pp. 1-5, 2008.

[4]. S. Sadaiappan, P. Renuga and D. Kavitha “Modeling and Simulation of Series Compensator to Mitigate Power Quality Problems”, International Journal of Engineering Science and Technology, Vol. 2, No. 12, pp. 7385-7394, 2010

[5]. S. Sadaiappan, P. Renuga and D. Kavitha “Modeling and Simulation of Series Compensator to Mitigate Power Quality Problems”, International Journal of Engineering Science and Technology, Vol. 2, No. 12, pp. 7385-7394, 2010.

CASE-1 CASE-2 CASE-3 CASE-4 THE NO OF GUPFC - 1 2 3

THE TOTAL NO OF CONTROL OBJECTIVE BY GUPFC - 5 10 15

THE TOTAL NO OF CONTROLLABLE OF ACTIVE AND REACTIVE POWER FLOW BY GUPFC

- 2 P Flow 2 Q Flow

4P Flow 2 Q Flow

6 P flow 2 Q Flow

THE TOTAL NUMBER OF BUS VOLTAGES BY GUPFC - 1 2 3 THE NO OF ITERATIONS 12 13 13 14




[6]. Chong Han, Zhanoning Yang, Bin Chen, Alex Q. Huang, Bin Zhang, Michael R. Ingram and Abdel-Aty Edris “Evaluation of Cascade-Multilevel-Converter- Based STATCOM for Arc Furnace Flicker Mitigation”, IEEE Transactions On Industry Applications, Vol. 43, No. 2, March/April 2007.

[7]. B. Fardanesh, M. Henderson, B. Shperling, S. Zelingher, L. Gyugyi, C. Schauder, B. Lam, J. Moundford, R. Adapa, and A. Edris, “Convertible static compensator: Application to the New York transmission system,” in CIGRE 14-103, Paris, France, Sept. 1998.

[8]. L. Gyugyi, K.K. Sen, and C.D.Schauder, “The interline power flow controller: A new approach to power flow management in transmission systems,” IEEE Trans. Power Delivery, vol. 14, no. 3, pp. 1115–1123, July 1999.

[9]. L. Gyugyi, C.D. Shauder, S.L. Williams, T. R. Rietman, D. R. Torg-erson, and A. Edris, “The unified power flow controller: A new approach to power transmission control,” IEEE Trans. Power Delivery, vol. 10, no. 2, pp. 1085–1093, Apr. 1995.

[10]. L. Gyugyi, C.D. Shauder, and K.K.Sen, “Static synchronous series compensator: A solid-state approach to the series compensation of trans-mission lines,” IEEE Trans. Power Delivery, vol. 12, no. 1, pp. 406–413, Jan. 1997.




Dynamically Partitioning Big Data Using Virtual Machine Mapping

Mrs.D.Saritha Dr.R.Veera Sudarasana Reddy G.Narasimha Reddy Assistant .Professor/ MCA Principal Senior Manager Narayana Engineering College, Narayana Engineering College,Gudur CTS Pvt,Ltd,Hydrabed Andhra Pradesh Andhra Pradesh Andhra Pradesh

Abstract— Big data refers to data that is so large that it exceeds the processing capabilities of traditional systems. Big data can be awkward to work and the storage, processing and analysis of big data can be problematic. MapReduce is a recent programming model that can handle big data. MapReduce achieves this by distributing the storage and processing of data amongst a large number of computers (nodes). However, this means the time required to process a MapReduce job is dependent on whichever node is last to complete a task. This problem is bad situation by heterogeneous environments. In this paper a methodologyis properly to improve MapReduce execution in heterogeneous environments. It is carried out using dynamically partitioning data during the Map phase and by using virtual machine mapping in the Reduce phase in order to maximize resource utilization.

Keywords—BigData; MapReduce; Hadoop; Virtual Machine; Heterogeneous environment;

INTRODUCTION MapReduce is a programming model for creating distributed applications that can process big data using a large number of commodity computers. Originally developed by Google[1,2], MapReduce enjoys wide use by both industry and academia[3] via Hadoop[4]. The advantages of MapReduce framework is that it allows users to execute analytical tasks over big data without worrying about the myriad of details inherent in distributed programming[3,5]. However, the efficacy of MapReduce can be undermined by its implementation. For instance, Hadoop the most popular open source MapReduce framework[5] assumes all the nodes in the network to be homogenous. Consequently, Hadoop’s performance is not optimal in a heterogeneous environment[6]. In this paper we focus on the Hadoop framework. We look in particular how MapReduce handles map input and reduce task assignment in a heterogeneous environment. There are many reasons why MapReduce might execute in a heterogeneous environment. For instance, advances in technology might mean new machines in the network are different to old ones. Alternatively, MapReduce may be deployed on a hybrid cloud environment, where computing resources tend to be heterogeneous[7]. In summary, this paper presents the following contributions

� A method to improve virtual machine mapping for reducers � A method to improve reducer selection on a heterogeneous systems

The rest of this paper is organized as follows. In section 2, we present some background on MapReduce. In section 3, we present our proposed dynamic data partitioning and virtual machine mapping methods. In section 4, we evaluate our work, present our experimental results and discuss our findings. Finally, in section 5, we present our conclusion and prospects for future work. MAPREDUCE The purpose of MapReduce is to process large amounts of data on clusters of computers. At the heart of MapReduce resides two distinct programming functions, a map function and a reduce function[8]. It is the responsibility of the programmer to provide these functions. Two tasks known as the mapper and reducer handle the map and reduce functions respectively. In this paper, the terms mapper and reducer are used interchangeably with the terms map task and reduce task.

Figure 1. MapReduce data flow




The purpose of the map and reduce functions is to handle sets of keys-value pairs. When a user runs a MapReduce program, data from a file or set of files is split amongst the mappers provided and read as a series of key-value pairs. The mapper then applies the map function on these key-value pairs. It is the duty of the map function to derive meaning from the input, to manipulate or filter the data, and to compute a list of key-value pairs. The list of key-value pairs is then partitioned based on the key, typically via a hash function. During this process, data is stored locally in temporary intermediate file, as shown in Fig 1. as input a key and a list of values. Once the reduce function finishes computing the data an output file is produced. Each reducer generates a separate output file. These files can be searched, merged or handled in whatever way the user wants once all reducers have completed their workload. PROPOSED TECHNIQUES AND IMPLEMENTATION The research model for this study is presented in Fig. 2, which shows a network that consists of several physical machines. Each physical machine (PM) has a limited number of virtual machines (VM). Without losing generality, virtual machines are used as a basic unit with which to execute a task. The virtual machine may run a map task or a reduce task. Due to the heterogenerous nature of the environment, the processing capabilities of any particular virtual machine may differ from other virtual machines in the environment. Figure 3. Dataflow of MapReduce model with the proposed dynamic data partitioner and a virtual machine mapper. Six Map tasks and three Reduce tasks run on virtual machines with differing processing capabilities. A. Dynamic Data Partitioning In Hadoop, a MapReduce job begins by first reading a large input file. This file is usually stored on the Hadoop Distributed File System (HDFS). Since Hadoop assumes the environment is homogenous, the data from this file is split into fixed sized pieces. Hadoop then creates a mapper for each split. In a homogenous cluster each node has the same processing power and capabilities. In this case, each mapper will finish processing its split at approximately the same time. In a heterogeneous network, nodes that process faster than others will complete their work earlier. Since data access rates between nodes on the HDFS are inconsistent due to issues of data locality, we propose a dynamic data partitioner that partitions data on a node irrespective of other nodes on the network. An example of the dynamic data partitioner is shown in Fig. 3. In this example, a 600GB file is used as input data. In this scenario, the data is divided up into six equal sized pieces, and sent to six virtual machines. Each of these virtual machines then executes a map task. Each virtual machine is given a value n that indicates the relative processing ability of that virtual machines VPU. This is based on the number of virtual processing units (VPU) of that virtual machine, and the physical machine it is running on. For instance, the virtual machine VM1 has an n value of 10 and the virtual machine VM2 has an n value of 2. This means that VM1 is able to process data 5 times faster than VM2. The processing speed of each virtual machine is calculated prior to execution using a profiling tool.




Figure 3. Map/Reduce using worksets As previously mentioned, the proportion of data to be reassigned amongst virtual machines is determined by the processing ability of all the virtual machines running on the same physical machine. The following algorithm calculated. The machine the DDP repartitions the data on each physical machine. On PM1 there is three virtual machines VM1, VM2 and VM3. VM1 has a VM processing rate of 10, VM2 has a VM processing rate of 2 and VM3 has a processing rate of 8. Each virtual machine has an initial split size of 100GB. Consequently, the total data size of the three virtual machines is 300GB, and the total speed of the three virtual machines is 20 units. The input split is then divided into fragments. The size of fragment is calculated using the following equation:

Table I- MAP VS. MATCH VS. PREGEL BASED

TYPE FILE TIME [M] ca.CondMat.txt Match/Reduce 0.23 ca.CondMat.txt Pregel 0.23 ca.CondMat.txt Map/Reduce 0.25

com.youtube.ungraph.txt Pregel 9.98 com.youtube.ungraph.txt Match/Reduce 16.78 com.youtube.ungraph.txt Map/Reduce 34.40

web.BerkStan.txt Pregel 14.12 web.BerkStan.txt Match/Reduce 24.70 web.BerkStan.txt Map/Reduce 298.35

A closer analysis of Figure 3 reveals that data sets with less than a hundred thousand nodes play in the hands of tratosphere. Its lack of a wiring phase, as in Hama, where nodes have to be connected to their neighbors, and the lack of Hadoop’s serialization makes it the fastest of the Java-based frameworks for smaller data sets

B. Virtual Machine Mapping In Hadoop, a master node determines where mappers or reducers reside on a network. When assigning a mapper to a node, it is important that it is located on or near the data it will access. This is because transferring data from one node to another takes time and delays task execution. The problem of determining where to place a task on the network so that it is close to the data it uses is known as data locality. Data locality is a key concept in MapReduce and has a major impact on its performance. Even though Hadoop uses this concept when determining where to execute its mappers, it does not exploit this concept for its reducers and locate reducers near these partitions. We therefore propose for this purpose a virtual machine mapper (VMM) which allocates the reducer to the appropriate physical machine based on partition size and the availability of a virtual machine. Figure 4. Virtual Machine Mapper Fig. 4 shows a simple example of the VMM ascribing reduce tasks to physical machines. In this example, there are six mappers on two physical machines, with three mappers per physical machine. Since this job requests three reduce tasks, each mapper creates three partitions. The total amount of data to be received by each reducer is then deduced by summing up the respective partition at each mapper. Based on the concept of data locality, reducers are assigned locations on physical machines based on where the data for each reducer is stored. On a physical machine there are multiple virtual machines. Once a reducer is assigned to a physical machine the reducer is assigned whichever virtual machine has the fastest processing speed. The algorithm for the virtual machine mapper is presented as follows. In this example, all of the reducers are allocated to a virtual machine on an appropriate physical machine. If there are no virtual machines available, the reducer is allocated to another physical machine. This is first done using the best fit selection methodwhich eases recovery, but hampers performance [5]. However, with the relative youth of its successors, it is cur-rently the only framework that can actually recover from faults. Both distributed GraphLab and Stratosphere detect lost nodes quickly, however cannot recover




from errors. Both display an error code on the console. Only Stratosphere has a built-in recovery mechanism, which is at the time of writing unable to handle iterations properly. In Fig. 3 there are two physical machines. Both physical machines have three virtual machines each running a mapper. Each mapper produces three data partitions, which are assigned to three reducers. Using Algorithm 2, reducer 1 is assigned to physical machine 1, virtual machine 1. This is because physical machine 1 stores the largest fraction of the data designated for that reducer. Similarly, reducer 2 and reducer 3 are assigned to a virtual machine on physical machine 2. On physical machine 1 there are three viable virtual machines (VM1, VM2, VM3). Reducer 1 is assigned to VM1 as it has the fastest processing speed. On physical machine 2 there are also three viable virtual machines (VM4, VM5, VM6) each with different processing speeds. Since reducer 3 has more data stored on physical machine 2, it is assigned to the fastest virtual machine (VM6). Consequently, reducer 2 is assigned to the second fastest virtual machine (VM4). In this example, all of the reducers are allocated to a virtual machine on an appropriate physical machine. If there are no virtual machines available, the reducer is allocated to another physical machine. This is first done using the best fit selection method. If a physical machine has more reducers requesting a virtual machine than there are available virtual machines, the VMM has to locate the reducer to another physical machine. Instead of rejecting reducers based on a first come first served (FCFS), the VMM assesses the size of the data contributed to the reducer by each physical machine. The VMM then gives priority to those reducers with the greatest difference between their largest data contribution and their second largest data contribution.both scenarios using the analyzed vertex centric frameworks. The results for the Map/Reduce frameworks did not match the speed of their counterparts and have been left out. The first thing to notice is that GraphLab apparently comes from a multicore background and is still optimized for that. In that scenario, Hama performs worse than GraphLab by at least 20% for every tested data set. The gain shows up especially using large data sets in the multicore scenario, which is an important benefit. In the distributed scenario, the gain is negligible for a huge data set like Wiki-talk, and even reversed for the Berkeley data. As previously mentioned, dense data set seems to exploit a shortcoming in the implementation of distributed GraphLab. For a complete analysis of GraphLab on a multicore machine see Since data access rates between nodes on the HDFS are inconsistent due to issues of data locality, we propose a dynamic data partitioner that partitions data on a node irrespective of other nodes on the network. An example of the dynamic data both scenarios using the analyzed vertex centric frameworks. The results for the Map/Reduce frameworks did not match the speed of their counterparts and have been left out. The first thing to notice is that GraphLab apparently comes from a multicore background and is still optimized for that. In that scenario, Hama performs worse than GraphLab by at least 20% for every tested data set. The gain shows up especially using large data sets in the multicore scenario, which is an important benefit. CONCLUSIONS This paper is based on MapReduce and the Hadoop framework. Its purpose is to improve the performance of MapReduce distributed application when executing in a heterogeneous environment. By dynamically partitioning input data being read by map tasks and by judicious assignation of reduce tasks based on data locality using a Virtual Machine Mapper. Simulation and experimental results show an improvement in MapReduce performance, improving map task completion time by up to 44% and reduce task completion time by up to 29%.In future research, this work can be expanded todynamically determine the number of reducers deployed onthe MapReduceenvironment. This is an important topic,which analyzes the cost-benefits of increasing the number of reducers, and compares whether the impact on performance.

REFERENCES [1]. J. Alvarez-Hamelin, L. Dall Asta, A. Barrat, and A. Vespignani. Large scale networks fingerprinting and visualization using the

k-core decom-position. Advances in neural information processing systems, 18:41, 2006. [2]. G. D. Bader and C. W. Hogue. Analyzing yeast protein-protein interaction data obtained from different sources. Nature

biotechnology, 20(10):991–997, Oct. 2002. [3]. K.-H. Lee, Y.-J. Lee, H. Choi, Y. D. Chung, and B. Moon, "Parallel data processing with MapReduce a survey," ACM

SIGMOD Record, vol. 40, 2012, pp.11-20. [4]. J. Cohen. Graph twiddling in a mapreduce world. Computing in Science Engineering, 11(4):29 –41, July–Aug. 2009 [5]. J. Dittrich and J.-A. Quiané-Ruiz, "Efficient big data processing in Hadoop MapReduce," Proceedings of the VLDB

Endowment, vol. 5, 2012, pp. 2014-2015. [6]. J. Xie, S. Yin, X. Ruan, Z. Ding, Y. Tian, J. Majors, A. Manzanares,and X. Qin, "Improving mapreduce performance through

dataplacement inheterogeneous adoop clusters," in Parallel &Distributed Processing, Workshops and Phd Forum (IPDPSW), 2010IEEE International Symposium on, 2010, pp. 1-9.



© 2014- 16, IJIRAE- All Rights Reserved Page - 51

Improving the Performance of Mapping based on Availability-Alert Algorithm Using Poisson Arrival for Heterogeneous

Systems in Multicore Systems

*Sheshappa S.N, ** Dr. G. Appa Rao, ***Dr. K V Ramakrishnan *Associate Professor, Dept. of Information Science & Engineering, Sir MVIT, Bangalore,

**Professor, Dept. of Computer Science & Engineering, GITAM, Vishakapatnam, ***Professor, Dept. of Electronics & Communications Engineering, CMRIT, Bangalore,

Abstract- Performance of Mapping can be improved and it is needed arise in several fields of science and engineering. They'll be parallelized in master-worker fashion and relevant programming ways have been projected to cut back applications. In existing system, the performance of application is considered only for homogenous systems due to simplicity. In this we use Availability-Alert algorithm using Poisson arrival to extend our approach for Heterogeneous systems in Multi core Architecture systems. Our proposed algorithm also considers the requirement needed for the application for their execution in Heterogeneous systems in Multi core Architecture systems while maintaining good performance. Performance prediction errors are minimized by using this approach at the end of the execution. We present simulation results to quantify the benefits of our approach.

Index Terms – Availability- Alert algorithm, Poisson arrival, performance Prediction errors, Performance Mapping. 1. INTRODUCTION Over the last decade, Heterogeneous systems in Multi core Architecture systems are widely used for scientific and business applications. Applications that comprise several freelance procedure tasks arise in several domains and square measure similar temperament to master-worker execution on cluster platforms. In this paper we tend to address the matter of planning these applications with the goal of reducing execution time, or make span. This downside has been studied for 2 totally different scenarios: fixed-sized tasks and separable work. In the former situation, the application’s work consists of tasks whose size (i.e. quantity of needed computation) square measure pre-determined and variety of economical programming ways have been planned. In this work we tend to focus on the latter state of affairs, within which the computer hardware will partition the work in discretional, continuous “chunks” (in sensible situations, this usually implies that the appliance consists of many similar machine tasks). Examples of such applications area unit: feature extraction, in which a giant image is metameric, and every section is transferred to a employee and processed locally; Signal process, which tries to recover a symptom buried in a very giant file recording measurements; and sequence matching, [2], in which a single sequence is compared to a giant lexicon file, and the running time is proportional to the letters in this lexicon. The objective of mapping algorithms is to map tasks onto nodes and order their execution in an exceedingly thanks to optimize overall performance. In mapping theory, the fundamental assumption is that each one machines are always available for process. This assumption may well be affordable in some cases; however it's not valid in eventualities wherever there exist sure maintenance requirements, breakdowns, or different constraints, which make the machines unavailable for process. Examples of such constraints are often found in several application areas. As an example, machine nodes in Heterogeneous systems in Multi core Architecture systems got to be sporadically maintained to stop malfunctions. We aim to develop a mapping strategy which is used to enhance the availability of resources in Heterogeneous systems in Multi core Architecture systems while maintaining good performance. In our previous work, we tend to studied security-aware mapping for embedded systems, clusters and Grids. However, these planning algorithms area unit designed for homogenized systems. Further, our previous mapping algorithms will not seems to be appropriate for multiclass tasks with availableness necessities. The main question in mapping Separable load is how to select an optimal division of the load into chunks. One potential approach is to divide the load in as several chunks as processors and to dispatch work in a single round of allocation. This has several drawbacks, particularly poor overlap of communication and computation and poor hardiness to performance prediction errors. Consequently, variety of researchers has investigated multi-round algorithms. Main observations include dividing the workload include larger chunks reduces overhead. The use of smaller chunks reduces performance prediction errors. THMR (Tough Homogenous Multi-Round) borrows from HMR to achieve high performance and hardiness to prediction errors by increasing and then decreasing chunk sizes throughout execution.

2. RELATED WORK A number of multi-round mapping algorithms for separable loads are projected with the belief that performance predictions are absolutely correct.




Most of this work assumes that the quantity of knowledge to be sent for a chunk is proportional to the chunk size. The work in [16] presents a “multi-installment” algorithm that uses increasing chunk sizes throughout application execution to attenuate make span. Though this approach provides associate degree optimum schedule for a given range of rounds, it's the subsequent limitations: latencies related to resource utilization are not modeled; and there's no thanks to verify the optimum range of rounds. Our recent add [19, 20] addresses each these limitations. By imposing the restriction that equal sized chunks are sent to employees inside a round, the HMR formula makes it attainable to reason associate degree optimal range of rounds whereas modeling resource latencies. In this work we have a tendency to extend HMR to account for performance prediction errors. Many works aim at maximizing the steady-state performance of terribly long-running applications [4, 11]. The goal isn't to attenuate application make span however to get asymptotically optimum schedules. Note that in these works it's attainable to adapt to unsteady performance characteristics of the underlying resources as the optimum schedule is periodic and might so be modified from one amount to consecutive. Multi-round programming for separable loads has conjointly been studied presumptuous non-zero performance prediction errors. The algorithms in [13, 14] begin application execution with massive chunks and reduce chunk sizes throughout. Assuming uncertainties on task execution times, this ensures that the last chunks won't expertise massive entirely insecurity. These works assume a set network overhead to dispatch chunks of any sizes. Against this, we have a tendency to assume that the amount of knowledge to be sent for a piece is proportional to the chunk size, that is additional realistic for many applications. With this assumption, beginning by causation an oversized chunk to the first employee would cause all the remaining employees to be idle throughout that doubtless long information transfer. However, in this paper we have a tendency to use the basic ideas in [13] to increase our previous work on the HMR formula. The notion of programming applications by combining a performance-oriented and a robustness-oriented approach is not new and has been explored as an example in [9], which uses each static programming and self-mapping. Our approach is additional performance economical as a result of it achieves better overlap of computation and communication and leverage the add [13] for improved strength to uncertainty.

3. BACKGROUND 3.1 PLATFORM AND APPLICATION ORIENTATION

We take into account applications that include a unceasingly mapping work, Wtotal , and that we assume that the number of application knowledge required for process a piece is proportional to the number of computation for that chunk. As done in most previous work, we tend to solely take into account transfer of application input data. The works in [1, 5] take into consideration output knowledge transfers however use one. Overhead incurred by the master to initiate information spherical of labor allocation. Similarly, the add [4] models output however considers only steady-state performance. We assume a master-worker model with N workers processes running on N processors. We tend to assume that the master does not send chunks to staff at the same time, although some pipelining of communication will occur [1]. Although this is a standard assumption in most previous work, it may well be helpful to permit for coincident transfers for better output in some cases (e.g. WANs). We’ve got provided an initial investigation of this issue in [20] and leave a lot of complete study for future work. The effective platform topology will then be viewed as heterogeneous processors connected to a master by heterogeneous network links. Finally, we tend to assume that staff will receive data from the network and perform computation at the same time (as for the “with front-end” model in [17]).

Computation may be overlapped with communication. We tend to model the time spent for the master to send chunk units of employment to worker i, as: transfer to worker i (i.e. initiate a TCP connection). When the master finishes pushing information on the network to worker and also the time once employee receives the last computer memory unit of data. We tend to assume that this model was mentioned well in [19, 20]. The key point is that it's versatile and may be instantiated to model platforms, portion of the transfer isn't overlap able with different information transfer. Supported our expertise with actual package [7], we tend to found that the machine latency, is prime for realistic modeling. We know of only 1 work that models this latency within the context of cleavable load planning [3]. Note that for cases that the required information files area unit replicated or pre-staged on workers, we will model these cases by using an appropriately large or infinitely giant. Relevant previous works on cleavable load planning [1, 10, 16].

3.2 THE HOMOGENOUS MULTI-ROUND

In this section we offer a short outline of the work and ends up in [19, 20] to line the stage for the THMR formula, which we tend to conferred in Section four. Figure 3 shows however HMR dispatches chunks of loads in multiple rounds. Whereas this is often similar in spirit to the “multi-installment” algorithm [16], HMR keeps chunk sizes fixed within each round. The chunk size is exaggerated between rounds so as to scale back the overhead of beginning communication and computation. While our work in [19, 20] addresses heterogeneous platforms, but we only discuss the same case here for simplicity.




The unknowns that HMR should verify square measure one, the quantity of rounds, and the chunk size used at each round. Our development of HMR was as follows.

We have a tendency to initial obtained a simple induction relation on the chunk sizes. Then, we have a tendency to frame the mapping drawback as a constrained improvement problem: the goal being to reduce the application execution time subject to the constraint that all the chunks total up to the entire employment. Using the Lagrange multiplier factor technique [8] we have a tendency to obtain a system of 2 equations as unknown. This method can be resolved numerically by division (requiring regarding 0.07 seconds on a 400MHz PIII). Complete details square measure provided in [17]. Our main contribution is that we have a tendency to be ready to reckon associate approximately best range of rounds whereas employing a realistic platform model incorporating resource latencies. To evaluate the effectiveness of our approach we have a tendency to used simulation and compared HMR with the multi-round rule in [16] and also the one-round rule in [1] for an intensive space of platform configurations. We initiate that:

1. HMR results in higher schedules than its competitors in an awesome majority of the cases in our experiments (95%); 2. Once HMR is outperformed, it's terribly near the competitors (on average among 2.04% with a regular deviation of zero.035); 3. Neither competition ever outperforms HMR “across the panel” (that means ranges of computation/communication ratios).

HMR is in a position to realize such improvement over previous work in spite of the uniform round restriction, because this restriction makes it doable to compute a best number of rounds.

Figure 1: EHMM dispatches the mapping into chunks in each round

Chunk j/B

Chunk j+1/B

Chunk j/S

Chunk j+1/S




This is often one in every of the most results of our previous work. We tend to additionally showed that HMR tolerates high platform heterogeneity as a result of a good resource choice.

4. EFFECTIVE HOMOGENOUS MULTI-MAPPING(EHMM)

The length of a computation or of a knowledge transfer usually cannot be foretold dead accurately in observe. Prediction errors arise owing to uncertainties of each the platform and the application. On a non-dedicated platform it's virtually application the time taken to trace through one pixel depends greatly on the quality of the scene. As a result, associate degree approach within which the complete schedule is pre calculated at the onset of the applying [16, 19] is probably going to be inefficient. All the same, this can be a regular approach in the planning literature, and specially for developing Separable employment algorithms that use increasing chunk sizes [16], together with our own work on Effective Homogenous Multi-Mapping (EHMM). On the opposite extreme, algorithms notably targeted at tolerating prediction errors don't create use of performance predictions in the least [13, 14]. They exponentially decrease chunk sizes and schedule chunks in an exceedingly greedy fashion. One issue there's the overhead for programming little chunks that is self-addressed in [14]. Additional significantly, these algorithms don't bring home the good overlap of communication and computation, which is crucial for top performance. Our basic approach is to mix each approaches: EHMM schedules the employment in 2 consecutive phases: Phase #1 uses a Good Book of EHMM to pre-calculate the initial portion of the schedule, first use little chunk sizes and step by step increasing chunk sizes; phase #2 uses the factoring approach in [13] to decrease chunk sizes. Phase #1 aims for top performance via economical communication computation overlap and overhead reduction, whereas Phase #2 limits the negative impact of performance prediction errors at the top of execution. In what follows we have a tendency to describe a model for these errors and our key style decisions for EHMM.

4.1 ENHANCEMENT OF PERFORMANCE FORECAST FAULT MODEL We assume an easy prediction error model each for information transfers and computations: the magnitude relation of expected execution time to effective execution time is often distributed with mean 1 and variance error (the distribution is truncated to avoid negative values). This model is sort of general and was employed in the relevant previous literature [13, 14]. Its simplicity makes it easy to interpret simulation results. A number of our intuitions for developing ETHMR are supported the belief of commonly distributed errors (as it absolutely was tired [13, 14]). We tend to conjointly assume that the likelihood distribution of prediction errors is stationary throughout the application run. If it's not stationary however doesn't change too quickly, our approach ought to still be effective as phase #2 doesn't use prediction errors the least bit. We also ran all the experiments beneath a uniformly distributed error model, however our results were basically similar.

A key question is whether or not error is a known amount, i.e. whether or not THMR will use its worth to make your mind up on however to organize the schedule at the onset of the applying. Estimations of error can be obtained by past expertise with the applying and therefore the platform, by querying resource monitoring or forecasting services [12], by watching prediction errors because the application runs, or by any combination of these. In what follows we tend to discuss alternate ways whether error is known or unknown.

5. AVAILABILITY ALERT ALGORITHM USING POISSON ARRIVAL

We currently present an Availability Alert algorithm that is used in a judicious way to improve the provision of Heterogeneous systems in Multi core Architecture systems whereas maintaining sensible performance in response time. This algorithm creates a set Na of nodes, finds the expected finishing time of the entire node in the set and also calculates the availability level of each node. Then allocate the job to the node that has the least finishing time. This algorithm is implemented by using Poisson arrival.

Time Interval

Communication Time

Computation Time




1. t=0, r=0 rate λ up to time T; 2. Generate work Wj; 3. t=t+[-(1/λ) ln (work Wj)]. If t>T, then stop; 4. set r=r1 and set r=t; 5. Place the work Wj in the queue in ascending order 6. Create a set of node Na ; 7. Label the node Na 8. Assign the availability cost and response time to node Na , CA , RT 9. if (Na empty) then 10. for each node b belongs to Na, do 11. calculate the expected finish time of the work Wj 12. if the response time of the node j is less than the assigned response time, i.e RTj <RT, then 13. RT=RTj ; x j; 14. end for 15. else 16. for each node b in the system do 17. calculate the availability cost of work Wj on node b, CAj 18. if the availability cost of the work on node b is less than assigned availability cost, i.e CAj <CA then 19. CA=CAj ; RT=RTj ; x j ; 20. end for 21. end if 22. WLmin=N1 ; LImin = ; /* Assume that node 1 is lightly loaded and its load capacity is */ 23. for each node b belongs to Na do 24. calculate its work load LIb ; 25. if the load of the node b is less than minimum load index, i.e LIb <LImin then 26. set the load index of b as the minimum load index LIb and node b is the lightly loaded node 27. Allocate work Wj to node b 28. else 29. Allocate work Wj to node WLmin 30. end if 31. end for

6. SIMULATION RESULTS

The simulation results have been obtained by using the GridSim. Simulation appears to be one of the feasible ways to examine the algorithms on large scale distributed systems containing heterogeneous assets. Compared to using the real systems in nature, replication works good without making the analysis mechanism difficult. Simulation is additionally effective in operating with terribly massive hypothetic issues that may otherwise need involvement of an outsized variety of active users and resources, that is extremely onerous to coordinate and build at large-scale analysis setting for investigation purpose. The modeling and simulation of entities by using GridSim toolkit can took part in parallel and distributed computing. To design and evaluate the mapping algorithms resources, applications are used. It has a wide facility for creating classes categorized under heterogeneous resources that can be aggregated by using resource brokers. To solve data rigorous applications resources are used which can be a single processor or multi-processor, with or without shared or distributed memory. Appropriate scheduler can be used for managing which are based on instant or space.

In this section we tend to provide experimental results obtained in simulation with the goals of quantifying the impact and effectiveness of our design selections. This is for many reasons: the results are additional straightforward to know and compare; a number of the competing algorithms don't seem to be amenable to heterogeneous platforms; and also the purpose of our analysis is primarily to know the impact of performance prediction errors. Our analysis is also used to eliminate the negative impact of performance prediction errors at the end of execution.




7. CONCLUSION AND FUTURE WORK In this paper we've bestowed THMR (Tough Homogenous Multi-Round), a mapping algorithm for minimizing the makespan of dividable work applications underneath uncertainties of resource performance; our final goal is to develop a mapping strategy for dividable loads that may be employed in observe for real-world applications on real-world platforms. In our previous work [19, 20] we have a tendency to create a primary contribution by developing EHMM, a rule that outperforms antecedently planned algorithms while tolerating additional realistic latency models.

0

0.2

0.4

0.6

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0.25 0.45 0.65 0.85

Arrival Rate - (Fig. 2)

Fig. 2 shows the arrival rate of the job and the resource availability for mapping the job.

0

100

200

300

400

0.25 0.45 0.65 0.85

Arrival Rate - (Fig. 3)

Fig. 3 shows the arrival mapping rate of the job and the average mapping finishing time for the job.

In this Research work, we have taken subsequent step and self-addressed the problem of performance prediction errors that arise thanks to uncertainties about platforms and applications. EHMM leverages EHMM attain each high performance and robustness to prediction errors: it uses two consecutive phases for application execution, with increasing and decreasing work chunk sizes. We have evaluated our approach with in depth simulation experiments. We've got that EHMM outperforms previously proposed algorithms each in terms of performance and robustness. We have implemented Availability-Alert Algorithm using Poisson arrival for providing the resources at the right time for carrying out processing in Heterogeneous systems in Multi core Architecture systems while maintaining good performance in response time. Performance prediction errors can be minimized by using this approach. Future work can be carried out by providing priority for the application based on the mapping available in each application.

8. REFERENCES [1] I.Foster, C. Kesselman, and S. Tuecke, “The Anatomy of the Grid: Enabling Scalable Virtual Organizations,” Int’l Journal

Super computer Applications, vol. 15, no. 3, pp. 200-222, Aug. 2001. [2] R. Ranjan, A. Harwood, and R. Buyya, “A Study on Peer-to-Peer Based Discovery of Grid Resource Information,” IEEE

Comm. Surveys and Tutorials, vol. 10, no. 2, pp. 1-42, Apr.-June 2008. [3] D. Abramson, J. Giddy, and L. Kotler, “High Performance Parametric Modeling with Nimrod/G: Killer Application for the

Global Grid?,” Proc. 14th Int’l Parallel and Distributed Processing (IPDPS ’00), pp. 520-528, May 2000.

Avai

labi

litty

Aver

age

Resp

onse

Ti

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[4] D.P. da Silva, W. Cirne, and F.V. Brasileiro, “Trading Cycles for Information: Using Replication to Schedule Bag-of-tasks Applications on Computational Grids,” Proc. Int’l Conf. Parallel and Distributed Computing, Euro-Par ’03, pp. 169-180, Aug. 2003.

[5] I. Chlamtac and A. Farago, “Making Transmission Schedules Immune to Topology Changes in Multi-Hop Packet Radio Networks,” IEEE/ACM Trans. Networking, vol. 2, no. 1, pp. 23-29, Feb. 1994. 1630 IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 22, NO. 10, OCTOBER 2011

[6] Altilar and Y. Paker. Optimal Mapping algorithms for Communication Constrained Parallel Processing. In Proceedings of Europar’02, pages 197 206, 2002.

[7] Altilar and Y. Paker. An Optimal Mapping Algorithm for Parallel Video Processing. In Proceedings of the IEEE International Conference on Multimedia Computing and Systems, 1998.

[8] H. Casanova and F. Berman. Parameter Sweeps on the Grid with APST, chapter 26. Wiley Publisher, Inc., 2002. F. Berman, G. Fox, and T. Hey, editors.

[9] L. Rosenberg. Sharing Partitionable Loads in Heterogeneous NOWs: Greedier Is Not Better. In Proceedings of the 3rd IEEE International Conference on Cluster Computing (Cluster 2001), pages 124–131, 2001.

[10] O. Beaumont, A. Legrand, and Y. Robert. The Master- Slave Paradigm with Heterogeneous Processors. In Proceedings of Cluster’2001, pages 419–426. IEEE Press, 2001.

[11] O. Beaumont, A. Legrand, and Y. Robert. Optimal algorithms for mapping Separable loads on Heterogeneous systems in Multi core Architecture systems. Technical Report RR-2002-36, Laboratoire de l’Informatique du Parall´elism, ́ Ecole Normale Sup´erieure de Lyon, France, October 2002.

[12] T. Hagerup. Allocating Independent Tasks to Parallel Processors: An Experimental Study. Journal of Parallel and Distributed Computing, 47:185–197, 1997.

[13] T. Xie and X. Qin, “A Security-Oriented Task Scheduler for Heterogeneous Distributed Systems,” Proc. 13th IEEE Int’l Conf. High Performance Computing (HiPC ’06), Dec. 2006.

[14] V. Bharadwaj, D. Ghose, V. Mani, and T. G. Robertazzi. Mapping Divisible Loads in Parallel and Distributed Systems, chapter 10. IEEE Computer Society Press, 1996.

[15] V. Bharadwaj, D. Ghose, V. Mani, and T. G. Robertazzi. Mapping Divisible Loads in Parallel and Distributed Systems. IEEE Computer Society Press, 1996.

[16] Xiao Qin, Tao Xie, “ An Availability- Aware Task Mapping Strategy for Heterogeneous systems in Multi core Architecture systems”, IEEE Transactions on computers, vol. 57,no. 2,pp. 188-198, Feb. 2008.


_________________________________________________________________________________________________ IJIRAE: Impact Factor Value - ISRAJIF: 1.857 | PIF: 2.469 | Jour Info: 4.085 | Index Copernicus 2014 = 6.57


Performance Study of Silicone Rubber Polymer was Filled Fly Ash as Insulator Material on High Voltage

Transmission Tower Ikhlas Kitta1)* Salama Manjang2) Wihardi Tjaronge3) Rita Irmawaty4) 1)Doctoral Program , 2)Electrical Engineering, 3)Civil Engineering, 4)Civil Engineering, Civil Engineering, Hasanuddin University, Hasanuddin University, Hasanuddin University, Faculty of Engineering, Makassar, Makassar, Makassar, Hasanuddin University, Indonesia Indonesia Indonesia Makassar, Indonesia Abstract— Silicone rubber has emerged as an alternative material for porcelain insulators and glass insulators on a high voltage transmission because it is lightweight, so it helps in planning the structure of the transmission tower. However, due to the cost of production of silicone rubber insulators are expensive and it is less resistant to climate change, it has not been used extensively as in Indonesia. One method to get silicone rubber insulator that is cheap is to mix it with other materials in the form filler that is inexpensive and easy to obtain as fly ash of coal because this material has a particle size that is very fine and its contents are materials that have been and are being investigated as filler of silicone rubber. This paper describe about the research that has proven the feasibility of fly ash as filler for silicone rubber. The results of this study is the tensile strength of silicone rubber increased proportional to the increase of fly ash content on silicone rubber, but lowers elongation-to-break of the silicone rubber. Furthermore, the electrical properties, namely the dielectric strength of silicone rubber will increase with the addition of filler (fly ash), where the greatest dielectric strength on the composition of the filler (fly ash) 40%. As for the relative permittivity is increased with the addition of filler (fly ash) to silicone rubber by 50%. And the silicone rubber surface resistance will increase with the addition of filler (fly ash).

Keywords—silicone rubber, fly ash, filler, high voltage insulator, transmission tower

I. INTRODUCTION

Electrical energy is channeled through a network of transmission and distribution of electricity. For the transmission of electrical energy by a considerable distance required high working voltages so that power losses can be reduced. Currently applied voltage on the transmission in Indonesia is 70 kV up to 500 kV, while the distribution voltage is 20 kV. High voltage transmission require particular insulating material that have high reliability as equipment separating between parts voltage with no voltage as well as retaining and supporting line transmission [1] [2].

Until now, porcelain insulators and glass insulators are still widely used in the Indonesia power system. Use of type

the insulators this in high voltage transmission that the higher is less profitable because required more mass of the insulator so require transmission tower construction more robust and higher, thus requiring greater investment costs. Porcelain insulators and glass insulators require special handling because it is easily broken, especially in the transport and installation process [3].

Since the last few years polymer material has emerged gradually and was developed as an alternative to porcelain

materials and glass materials. Advantages of polymer material in this case silicone rubber is dielectric properties, volume resistivity, thermal properties, and mechanical strength [4] [5] [6] [7]. The weight ratio of the various types of insulators made of polymer is 36.7% up to 93% lighter than porcelain insulators [3]. Although various advantages, to date the use of silicone rubber in several countries are still limited as in Indonesia due to the high production cost of silicone rubber insulators, so many researchers who conducted the optimization of material that can be mixed with silicone rubber, especially in terms of the material filler concentrated on silica (SiO2) [8] [10], alumina (Al2O3) [11], titanium dioxide (TiO2) [9], and magnesium oxide (MgO) [10].

One source of filler material is coal fly ash that contains chemical elements, among others, silica (SiO2), alumina (Al2O3), ferrous oxide (Fe2O3) and calcium oxide (CaO), also contains elements of other enhancements that magnesium oxide (MgO), titanium oxide (TiO2), alkaline (Na2O and K2O), sulfur trioxide (SO3), phosphorus oxide (P2O5) and carbon [12]. Thus allowing the coal fly ash can be used as an alternative filler of silicone rubber polymers. Therefore, to determine whether the coal fly ash can be used as filler material to high voltage insulators, will be done testing on the material of silicone rubber that filled with coal fly ash to be used as a high voltage insulator material in an effort to reduce the burden of transmission tower.




II. EXPERIMENTAL PROCEDURE This test follows the procedure as shown in flowchart in Fig. 1.

Fig. 1 . Experimental Procedure Flowchart

A. Preparation Material Type of RTV silicone rubber used is 683 [13]. Fly ash material taken from Coal fire Power Plant in South Sulawesi

province (Indonesia). Fly ash compounds have been examined using XRF is SiO2 = 40,16%; Al2O3 = 19,48%; CaO = 8,35%; Na2O = 2,4%; MgO = 3,8%; P2O5 = 0,15%; SO3 = 1,33%; K2O = 1,75%; TiO2 = 1,3%; Cr2O3 = 0,05%; MnO = 0,29%; Fe2O3 = 20,22%; CoO = 0,06%; SrO = 0,12%; ZrO2 = 0,06%; BaO = 0,19%; Pr6O11 = 0,05%; Nd2O3 = 0,08%.

Beginning of the experiment is silicone rubber and fly ash mixed with manual mixing technique, then the mixture is inserted into a vacuum chamber to remove trapped air bubbles. The mixture is poured into a mold of 2 mm to obtain a test material with a uniform thickness and to facilitate the testing of dielectric breakdown strength without reducing the ease of measuring other parameters. In the process of curing, the material was placed in a room with a humidity of 80% which runs for 24 hours. The test material was made in the number of different contents of fly ash coal. The composition of the fly ash and the silicone rubber is 0% Fly Ash, 5% fly ash, 10% fly ash, 15% fly ash, 20% fly ash, 25% fly ash, 30% fly ash, 35% fly ash, 40% fly ash, 45% fly ash and 50% Fly ash.

B. Laboratory Test Conducted

Tensile Strength test was conducted to determine the mechanical properties of silicon rubber before and after is filled with fly ash. The tensile tests using ASTM 638. The next test is the test of elongation-to-break is one type of deformation which is the size of the change that occurred when the test material was given style.

The other is testing the dielectric strength test conducted in accordance with ASTM D149. Electrodes used in the

measurement is a needle electrode on the top plate and the electrode at the bottom. Voltage frequency of 60 Hz is used in this test. Tests were carried out under room temperature 27 °C and a humidity of 80%.

Relative permittivity is obtained by measuring the capacitance of the capacitance meter test materials. Material placed between the parallel circular plate and measurements were performed with a frequency of 800 Hz. Capacitance measurements performed below room temperature 26 °C and humidity around 85%. Capacitance value obtained is then converted into relative permittivity. The testing procedure is based on ASTM standard D257. Furthermore test voltage of 5670 V DC instrument for the measurement of the volume resistivity and the test voltage is 2730 V DC is used for measurement of surface resistivity.

III. RESULT AND DISCUSSION Here in Table 1 show the results of testing of the test material.

TABLE I

RESULTS OF TESTING THE TEST MATERIALS

Fly ash content 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% Tensile Strength (kgf/mm2) 0.13 0.13 0.14 0.15 0.20 0.20 0.21 0.18 0.16 0.16 0.15

Elongation at break (mm) 345.0 227.4 158.9 147.4 140.4 132.7 114.7 101.9 94.2 94.0 93.6 Breakdown Voltage (kV/mm) 9.80 10.10 10.21 12.20 14.91 15.50 16.15 16.30 16.77 16.05 14.15

Relative Permitivity 2.70 2.83 2.99 3.56 3.79 3.73 3.68 3.69 3.71 3.77 3.84 Surface resistivity (GOhm/sq) 5.37 5.53 5.74 6.12 6.71 7.90 8.37 8.67 9.12 9.89 11.38

Explanation of the tables of test results in Table 1 will be shown in the next section.




A. Tensile strength Fig. 2 shows about mechanical properties such as tensile strength of silicone rubber increased when filled with coal fly

ash.

0

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0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

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gf/m

m2)

Fly ash content (%)

Fig. 2 Effect of fly ash content on tensile strength of fly ash filled silicone rubber

The test material with the amount of 5% fly ash up to 50% fly ash has a value greater tensile strength than the test material which has no fly ash (0%). The tensile strength of the test material has a maximum value on 30% fly ash content that is equal to 0.21 kgf/mm2, which increased by more than 62% of silicone rubber with no fillers. The tensile strength of the test material is influenced by the strength of the bond between the particles of coal fly ash and silicone rubber. Another factor that can influence the tensile strength is a cure rate of the test material.

B. Elongation-to-break Test Likewise for testing elongation-to-break has been tested and magnitude of the value illustrated in Fig. 3 which shows

the length of the elongation-to-break of the test material which describes the test material to different sizes of fly ash is added to the silicone rubber has a value elongation- to-break declining rather than silicone rubber with no fillers. This shows that the composition of fly ash affecting the nature of elongation-to-break silicone rubber. The decline of the value of elongation-to-break also affected by the size of the fly ash, where the test materials are particles that have a larger size than the particles of silicon rubber, thereby reducing the extension properties of the test material [14].

0

50

100

150

200

250

300

350

400

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Elo

ngat

ion

at b

reak

(mm

)

Fly ash content (%)

Fig. 3 Effect of fly ash content on elongation at break of fly ash filled silicone rubber

C. Dielectric Strength

Dielectric strength measurements carried out by the breakdown voltage test and the results can be seen in Fig. 4 which shows the dielectric strength of silicone rubber filled with fly ash increased with the addition of fly ash in the test material. Maximum of breakdown voltage is achieved in 40% fly ash in a silicone rubber or an increase of 71% compared with silicone rubber without fly ash.

Breakdown voltage of the test material can be influenced by the intrinsic and extrinsic properties of the test material such as the type of the applied voltage. The presence of air bubbles in the material being tested can be one of the intrinsic factors that lead to a decrease in the dielectric strength of the material. Another factor that can affect the dielectric strength of the test material is resistance volume. If the resistance volume is low, electrical currents in the test material will increase, which will trigger material damage [15].




0.02.04.06.08.0

10.012.014.016.018.0

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Bre

akdo

wn

Vol

tage

(kV

/mm

)

Fly ash content (%)

Fig. 4 Effect of fly ash content on dielectric strength of fly ash filled silicone rubber

D. Relative Permittivity The relative permittivity of the material with a variety of fly ash content has been researched and shown in Fig. 5,

where the figures show a relative permittivity of the test material were increased until the filler content of 50% fly ash. Increasing the value of the permittivity of the filler content of 50% fly ash is 44% compared with silicone rubber without filler (0% fly ash). Fly ash make silicone rubber composite has a value of permittivity increased, causing the dielectric loss or dissipation material will increase as well.

0.00.51.01.52.02.53.03.54.04.5

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Rel

ativ

e Per

miti

vity

Fly ash content (%)

Fig. 5 Effect of fly ash content on relative permittivity of silicone rubber composite

E. Surface Resistivity Fig. 6 shows that increased levels of fly ash in the silicone rubber will make the surface resistivity of the test material

becomes higher. Value of the surface resistance on the composition of the content of fly ash 50% is of 11.38 GOhm/sq increased 42% compared with silicone rubber without filler (0% fly ash). Measurement value determined by thickness of test materials. Surface resistivity also affected by surface recovery.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

surf

ace

resi

stiv

ity (G

Ohm

/sq)

Fly ash Content (%)

Fig. 6 Effect of fly ash content on surface resistivity of fly ash filled silicone rubber




IV. CONCLUSION Silicone rubber containing coal fly ash is possible use as insulator material of high voltage, which it is proved in

research that has been done. The results showed that the fly ash feasible for use as a filler to silicone rubber for its ability to increase the tensile strength, dielectric strength, relative permittivity, and the surface resistivity. The content of fly ash as filler for silicone rubber most excellent is 30% fly ash because it provides better improvement for electrical and mechanical properties of silicone rubber. The tensile strength of the test material is increased by the increase in fly ash on silicone rubber, where the largest increase of the filler content of 30%. But the increasing impact of fly ash composition on the silicone rubber decrease elongation-to-break of silicon rubber. Furthermore, the dielectric strength test materials that will increase with the addition of filler (fly ash), where the greatest dielectric strength is at 40% filler composition. As for the relative permittivity is increased with the addition of filler (fly ash) in the silicone rubber by 50%. And the surface resistance of test materials increased with the addition of filler (fly ash) to 50%.

ACKNOWLEDGMENT

This writing is presented to Rizki Pratama Putra alumni Magister of Engineering Faculty at Hasanuddin University on the assistance during the data provision.

REFERENCES [1] Mustamin, S. Manjang, 2010, Characteristics of high voltage polymer insulators under pressure aging accelerated

artificial tropical climate, Jurnal Media Elektrik, Volume 5, No. 2, December, 2010. [2] Venkatesulu B. and M. Joy Thomas, Erosion Resistance of Alumina-filled Silicone Rubber Nanocomposites, IEEE

Transactions on Dielectrics and Electrical Insulation Vol. 17, No. 2; April, 2010. [3] S. Manjang, The performance review as a silicone elastomer material high voltage insulator in the tropics,

Dissertation, Institut Teknologi Bandung, Bandung, 2000. [4] M. T. Gençoğlu, The Comparison Of Ceramic And Non-Ceramic Insulators, ISSN:1306-3111, e-Journal of New

World Sciences Academy, Volume: 2, Number: 4, Article Number: A0038, 2007. [5] S. Y. Jung, and Byung-Kyu Kim, Preparation and Characteristics of High Voltage Liquid Silicone Rubber by

Modified Cross-linking Agent, Transactions On Electrical And Electronic Materials Vol. 10, No. 1, February 25, 2009.

[6] Fernando M. A. R. M., and S. M. Gubanski, Ageing of Silicone Rubber Insulators in Coastal and Inland Tropical Environment, IEEE Transactions on Dielectrics and Electrical Insulation Vol. 17, No. 2; April, 2010.

[7] Lau, K.Y., M. A. M. Piah, Polymer Nanocomposites in High Voltage Electrical Insulation Perspective: A Review, Malaysian Polymer Journal, Vol. 6, No. 1, p 58-69, 2011.

[8] Stevenson I., L. David, C. Gauthier, L. Arambourg, J. Davenas, G. Vigier, Influence of SiO2 fillers on the irradiation ageing of silicone rubbers, Polymer 42 (2001) 9287-9292, Elsevier, 2001.

[9] Madidi F., G.Momen and M. Farzaneh, Effect of filler concentration on dielectric properties of RTV silicone rubber / TiO2 nanocomposite, 2013 Electrical Insulation Conference, Ottawa, Ontario, Canada, 2 to 5 JUNE, IEEE, 2013.

[10] Jeong In-Bum, Joung-Sik Kim, Jong-Yong Lee, Jin-Woong Hong, Jong-Yeol Shin, Electrical Insulation Properties of Nanocomposites with SiO2 and MgO Filler, Transactions On Electrical And Electronic Materials, Vol. 11, No. 6, pp. 261-265, December 25, 2010.

[11] Jun-Wei Zha, Zhi-Min Dang, Wei-Kang Li, Yan-Hui Zhu, George Chen, Effect of Micro-Si3N4–nano-Al2O3 Co-filled Particles on Thermal Conductivity, Dielectric and Mechanical Properties of Silicone Rubber Composites, IEEE Transactions on Dielectrics and Electrical Insulation Vol. 21, No. 4; August, 2014.

[12] Munir, Misbachul, Utilization of coal ash (fly ash) for hollow block-quality and safe for the environment, Thesis, Universitas Diponegoro Semarang, 2008.

[13] A. Jaya, Hamzah Berahim, Tumiran, Rochmadi, The Performance of High Voltage Insulator Based on Epoxy-Polysiloxane and Rice Husk Ash Compound in Tropical Climate Area, Electrical and Electronic Engineering 2012, 2(4): 208-216, 2012.

[14] J. Gummadi, G.Vijay Kumar, Gunti Rajesh, Evaluation of Flexural Properties of Fly Ash Filled Polypropylene Composites, International Journal of Modern Engineering Research (IJMER), Vol.2, Issue.4, July-Aug, pp-2584-2590, 2012.

[15] Solymar, Laszlo, Donald Walsh, and Richard RA Syms. Electrical properties of materials. Oxford University Press, 2014.

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