ISSN 2304-7712 (Print) International Journal of … 6 No 1.pdfby CATIA V5R17 having following...

VOLUME 6 NUMBER 1 May 2017

International Journal of Advanced

Engineering and Science

ISSN 2304-7712 (Print)

ISSN 2304-7720 (Online)

International Journal of Advanced Engineering and Science, Vol. 6, No.1, 2017

ISSN 2304-7712

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International Journal of Advanced Engineering and Science

ABOUT JOURNAL

The International Journal of Advanced Engineering and Science ( Int. j. adv. eng. sci. / IJAES ) was first

published in 2012, and is published semi-annually (May and November). IJAES is indexed and abstracted

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The International Journal of Advanced Engineering and Science is an open access peer-reviewed

international journal for scientists and engineers involved in research to publish high quality and refereed

papers. Papers reporting original research or extended versions of already published conference/journal

papers are all welcome. Papers for publication are selected through peer review to ensure originality,

relevance, and readability.


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CONTENTS

1 Publisher, Editor in Chief, Managing Editor and Editorial Board

2 FINITE ELEMENT ANALYSIS & EXPERIMENTAL VALIDATION OF SHOT PEENING PROCESS

ON PMG COVER

ATUL PATHAK, KADAM MUNJADAS

3 FATIGUE LIFE PREDICTION & ENHANCEMENT OF PMG COVER AL 2024 ALLOY

ATUL PATHAK, KADAM MUNJADAS

4 WATER PURIFICATION SYSTEM BY USING MECHANICAL ENERGY

THIMMALA.CHALAPATHI

5 SYLLABUS MAPPING USING ADVANCED INTERACTIVE TECHNIQUES

PRAVIN JADHAO,VISHAL JAGTAP,LAXMIKANT MAHAJAN


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Publisher: Elite Hall Publishing House

Editor in Chief:

Dr. Wei Zhang (China) E-mail: [email protected]

Editorial Board:

Mr. K. Lenin, Assistant Professor, Jawaharlal Nehru technological university Kukatpally, India E-mail: [email protected]

Dr. Jake M. Laguador Professor, Engineering Department Lyceum of the Philippines University, Batangas City, Philippines E-mail: [email protected]

Dr. T. Subramanyam FACULTY, MS Quantitative Finance, Department of Statistics Pondicherry Central University, India Email: [email protected]

Dr. G. Rajarajan, Professor in Physics, Centre for Research & Development Mahendra Engineering College, India Email: [email protected]

Miss Gayatri D. Naik. Professor, Computer Engg Department, YTIET College of Engg, Mumbai University, India Email: [email protected]

Mr. Rudrarup Gupta Academic Researcher, Kolkata, India E-mail: [email protected]

Mr. Belay Zerga MA in Land Resources Management, Addis Ababa University, Ethiopia E-mail: [email protected]

Mrs.Sukanya Roy Asst.Professor (BADM), Seth GDSB Patwari College, Rajasthan,India E-mail: [email protected]

Mr. Nachimani Charde Department of Mechanical, Material and Manufacturing Engineering, The University of Nottingham Malaysia Campus E-mail: [email protected]

Dr. Sudhansu Sekhar Panda Assistant Professor, Department of Mechanical Engineering IIT Patna, India Email: [email protected]

Dr. G Dilli Babu Assistant Professor, Department of Mechanical Engineering, V R Siddhartha Engineering College, Andhra Pradesh, India Email: [email protected]

Mr. Jimit R Patel Research Scholar, Department of Mathematics, Sardar Patel University, India Email: [email protected]

Dr. Jumah E, Alalwani Assistant Professor, Department of Industrial Engineering, College of Engineering at Yanbu, Yanbu, Saudi Arabia Email: [email protected]

Web: http://ijaes.elitehall.com/ ISSN 2304-7712 (Print)

ISSN 2304-7720 (Online)


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FINITE ELEMENT ANALYSIS & EXPERIMENTAL VALIDATION

OF SHOT PEENING PROCESS ON PMG COVER

Mr.Atul Pathak 1, Prof Dr Kadam Munjadas

2

Department of Mechanical Engineering, Jawaharlal Nehru Engineering College, Aurangabad, India1

[email protected]

Department of Mechanical Engineering, Jawaharlal Nehru Engineering College, Aurangabad, India

[email protected], [email protected]

Abstract : Engineering components and structures are regularly subjected to cyclic loading and they

are consequently lead to fatigue damage. In most cases, fatigue damage will initiate at the surface due

to localized stress concentrations caused by machining marks, exposed inclusions or even due to the

contrasting movement of dislocations. Evidently, control over the initiation and early propagation of

surface cracks is paramount for prolonging the fatigue life of components. Shot peening is cold

working process which is extensively used in automotive and aircraft industries for the above purpose

as it produces near surface plastic deformation leading to the development of work-hardening and

high magnitude compressive residual stresses. Work hardening is expected to increase the flow

resistance of the material and thus reduce crack tip plasticity, while, the residual stresses can act as: a)

mean stress modulators in the case of the onset of crack propagation or b) closure stress in the case of

crack growth. Check the effect of shot on the part that is to be tested is calculated by using FEA

software package. 3D PMG Cover body of Aluminum 2024 alloy material is modeled by CATIA

V5R17.The FEA work is carried out with the LSDYNA solver validated the Compressive Residual

stress values with stress values of Experimental X- ray Diffraction methods.

Keywords Compressive Residual Stresses, Displacement, Finite Element Analysis, Shot

peening XRD Machine

I Finite Element Modeling Definition of FEM is hidden in its name itself. Basic theme is to make calculations at only limited

(Finite) number of points and then interpolate the results for entire domain (surface or volume).

1 3-D Numerical Study of Shot Peening Process Using Multiple Shot Impacts

LS-DYNA code was employed and validated for the numerical simulations in this work. The modeling of

Shot Peening process was accomplished by simulation of multiple shot impacts on a target plate at

different velocities. From the simulations, the compressive stress profiles were obtained and the effects of

shot diameter, velocity were investigated. The results showed that, stress distribution was highly

dependent on these parameters. A uniform state of stress was achieved at a particular number of shots.

Impact velocity significantly influences the stress profile.


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1.1 What is LS‐‐‐‐DYNA?

A code originally developed for explicit, nonlinear stress analysis of structures subjected to impact

loading. Now, multiphysics code.

i. Fluid‐structure interaction (Lagrangian/Euler/ALE)

ii. Thermal and coupled thermal‐structural analysis

iii. Implicit capabilities (static analysis, implicit dynamic analysis, eigenvalue analysis, linear

analysis)

iv. Mesh less methods (SPH, EFG)with well‐developed parallel processing capability

a. SMP (Shared Memory Parallel)

b. MPP (Massively Parallel Processing)

Fig 1 LS-DYNA Process Overview

1.2 Background

During literature review it was clear that we can use Finite Element Modeling

for Shot Peening simulation. The parameters which are considered during this

are Shot Size, Shot Velocity, Impact Angle, Shot Distance

1.2.1 FE Modeling-:

The model used for Shot Peening simulation is generated LS DYNA, consist of three

dimensional PMG Cover body of Aluminum 2024 alloy material is geometrically CAD modeled

by CATIA V5R17 having following geometrical properties and act as target in impact analysis.


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Fig 2 Drafting 2D Drawing of PMG 2024 AL Alloy Cover

Fig 3: - 3D Model View of the PMG 2024 AL Alloy Cover

1.2.2 Boundary condition

Fig 4 -Boundary Conditions

Constrained in all


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1.2.3 Target Part Mesh

The three-dimensional FE model was developed using the commercial finite element code by Lsdyna.

Fig.5 shows the FE mesh that was used to investigate multiple shot impacts on the component.

Fig. 5- Target Mesh Model with Shots

1.2.4 Shot Mesh -

So, a fully spherical surface with a mass positioned at its center was used to model a shot as shown in

Fig.6

Fig 6- Shot Mesh Model

Shot mesh model developed in this study as rigid element having material type mat 20 and mass

applied at all nodes equally.

1.2.5 Procedure for Finite Element Modeling: The process of Finite element

Modeling of Shot Peening is explained below,

1. Create the target model & meshing:

20 Hit


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In this step, we created geometrical CAD model by CATIA V5 R17 software geometry of

required dimension. Finite element Analysis in LS-DYNA FEA solver A fine meshing of element

size of 2 mm is chosen & meshed with first order Tetrahedron elements (ELF -10).

i) Create the shot & meshing:

As per iterations need we created the ball size (0.65mm, 0.75mm and 1mm diameter) Fine

meshing (0.1mm) was done. Mass (1gm) was applied equally to each node of shot.

ii) Mesh Details:

Model size 0.65 mm - 44285 (alt-27365, shot - 16920) elements, 31120 total nodes (4560 shot

nodes)Model size 0.75 mm -89445 (alt-27365, shot - 62080) elements, 26560 total nodes, (14100

shot nodes)Model size 1 mm - 110085 (alt-27365, shot - 82720) elements, 49768 total nodes,

(17760 shot nodes)

2. Define the materials:

This is the most important step during the process. As per literature review, this step will create

huge impact on final results. So the materials were carefully selected & values are put as per

standards available (public domain) which are in table below.

Table 1 Material for Target Plate Elastic-Plastic (Mat 24) Material.

Material Yield

Strength

Tensile

strength

Young’s

modulus E

Poisson’s

ratio Density

Aluminum

2024 345 MPa 470 MPa 73 GPa 0.33 2.770Gm/ Cm3

Table 2 Material for Shot Rigid (Mat 20) Material.

Shot Type Young’s

Modulus

Poisson’s

Ratio Density

Hardness

HRC

S 320 (Steel) 2.1E5 MPa 0.29 7200 Kg / m3 45

3. Defining & Applying Section Properties:

The section properties are defined & assigned to each shot & plate.

4. Assigning the materials to Sections:


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In this stage the material properties are applied to each plate & shot.

5. Verify the properties:

The properties are verified for correct application.

6. Applying boundary conditions to plate:

The plate which is meshed & material defined is fixed at the bottom surface.

7. Applying Velocity to shot:

Shot velocity is applied during this phase. The velocity was applied as per need of iteration.

8. Contact Definition:

Contact {Contact Automatic Single Surface – (Type Automatic General)} was defined between

Cover & shot.

9. Required Set of parameters are chosen for analysis:

The required parameters like GLSTAT (Global Statistics), MATSUM (Material Energy

Summary), SLEOUT (Sliding Interface Energy), NODOUT (Node Energy) etc are kept on. The

output is taken at and interval of 5.E-4

10. Deciding the output file format:

The output file chosen is d3plot.

11. Saving the file with an extension:

The file is saved as Iteration Number. k. In this .k is the extension.

12. Analysis in LS-Dyna:

.k file is the solved by LS-Dyna for 5 ms

13. Analysis of results:

The results are then seen & analyzed by Ls- Dyna post.

1.2.6 Results of Conditions:


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Fig 7 Condition 3: Shot Size - 0.75mm Shot velocity 30 m/s Impact Angle –

45 Deg, Shot Distance-120mm

Fig 8 Condition 4: Shot Size - 0.75mm Shot velocity 45 m/s Impact Angle –

45 Deg Shot Distance-150mm

The maximum von mises stress observed at a velocity of

30 m/s with a 45 deg Impact is around 340 Mpa.

The maximum displacement is around 0.1 mm





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Fig 9 Condition 5: Shot Size - 0.75mm Shot velocity- 45 m/s Impact Angle –

45 Deg, Shot Distance-190mm

Table 3 :Summary of FEA Chapter Results

2 Experimentation

2.1 Shot Peening

Experimental Work of Shot Peening is carried out at “Rushash Engineering Cooperative Pvt. Ltd” 414111

MIDC Ahmednagar table 4 from optimization data analysis MIITAB14 software tool

FEA Inputs Displacement

in

mm

Stress

Mpa Shot Size

mm

Velocity

m/s

Impact Angle

Deg

Distance

mm

0.75 30 45 120 0.101 340

0.75 40 45 150 0.135 338

0.75 45 45 190 0.513 334





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Table 4: Response Table for Signal to Noise Ratios

Table 4- Experimentation Iterations

Shot

Size

mm

Velocity

m/ s

Impact

Angle

Deg

Distance

mm

Immediate

Stresses in

MPa

SNRA2 MEAN2

0.65 30 45 190 371.64 -51.4024 371.64

0.65 40 65 120 49.7 -33.9271 49.7

0.65 45 80 150 12.03 -21.6053 12.03

0.65 60 85 190 8.22 -18.2974 8.22

0.75 30 65 90 39.43 -31.9165 39.43

0.75 40 45 150 1149.5 -61.2102 1149.5

0.75 45 85 90 12.56 -21.9798 12.56

0.75 60 80 120 36.03 -31.1333 36.03

1 30 80 190 31.8 -30.0485 31.8

1 40 85 150 17.64 -24.93 17.64

1 45 45 120 585.64 -55.3526 585.64

1 60 65 90 338.2 -50.5835 338.2

1.25 30 85 120 26.96 -28.6144 26.96

1.25 40 80 90 64.36 -36.1723 64.36

1.25 45 65 190 339.86 -50.626 339.86

1.25 60 45 150 880.7 -58.8966 880.70

Shot Size

mm

Velocity

m/ s

Impact Angle

Deg

Distance

mm

0.75 30 45 120

0.75 40 45 150

0.75 45 45 190


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The exposure time is set constant, equal to 120 sec for all specimens as it will have 100% coverage as per

previous data in literature review.

2.1.1 Specimen Composition

The project has been carried out to improve the fatigue life PMG Cover of Al-2024 material by shot

peening method. The material composition is shown in Table 5 below

Table 5- Al 2024 Material Composition

Name of Material Concentration Limit

Copper 3.8-4.9 % max,

Magnesium 1.2-1.8 % max,

Silicon 0.50 % max,

Iron 0.50% max.

Manganese 0.3-0.9 % max.

Zinc 0.25 % max.

Titanium 0.15 % max.

Aluminum Remainder %

Chromium 0.1 %

Reminder 0.15%

Test specimen (Fig.12) used for shot peening and fatigue testing is shown below. (S B Mahagaonkar IE (I)

Journal-PR, September 2009)

Fig.10 Test Specimen for Fatigue Testing

In Fig 10 Standard unpeened specimen has been shown

R = 12Inch


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Fig 11 Standard Unpeened Specimen Fig 12 Shot Peened Specimen

2.1.2 Shot Peening Procedure-:

1) Feed the shots through hopper.

2) Adjust valve for desirable flow rate of shots.

3) Load the standard test specimen in fixture and close the door.

4) Set the air speed for desirable shot speed.

5) Set the cycle time.

6) Start the cycle.

7) Open the door after cycle completion and run same cycle for remaining half portion of specimen.

8) Repeat the procedure for another specimen.

9) Set the new shot speed and repeat the procedure.

Fig 14 Displays Shot Peened Specimen

2.1.3 Residual Stress Measurement:

Measurement of residual stress accurately is one of the critical tasks. Many of researchers used following

two methods to obtain residual stress level after shot peening. These methods are mentioned below.

a) X-Ray Diffraction Method-:

Diffraction methods (shown in Fig.13 and 14) of residual stress determination basically measure the

angles at which the maximum diffracted intensity take place when a crystalline sample is subjected to

x-rays. From these angles it is possible to obtain the inter-planar spacing of the diffraction planes using

Bragg’s law. If the residual stresses exist within the sample, then the d spacing will be different than that


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of an unstressed state. This difference is proportional to magnitude of the residual stress.

Fig 13 Diffractometer Scheme Fig. 14Diffraction at Tilted Position

The incident beam diffracts X-rays of wavelength λ from planes which satisfy Bragg’s law. If the surface

is in compression then the planes are further apart than in the stress-free state because of Poisson’s ratio.

The inter planar spacing “d” is obtained from the peak in intensity versus scattering angle and Bragg’s law,

assume that the detector is turned over a range of angles, 2θ, to find the angle, θ, of the diffraction from

grains which satisfy Bragg’s law. In other words the grains that have planes of atoms with inter planar

spacing “d” such that λ =2dsinθ. The grains that have planes with this spacing that are parallel to the

surface will diffract as in Fig. 14 This diffraction occurs from a thin surface layer which is about 20 µm.

If the surface is in compression, then the inter-planar spacing “d” is larger than in the stress free state as a

result of Poisson’s effect. When the specimen is tilted with respect to the incoming beam new grains will

diffract and the orientation of the diffraction planes is more nearly perpendicular to the stress direction.

Fig 15 X- RAY Diffraction Machine

analytical Make X-Ray Diffractomer X’PERT PRO.Kα Radiation: Chromium source, wavelength

2.289760 Å Parallel beam geometry with poly-capillary lens and parallel plate collimator’s X-Ray elastic

constant: 5.85 x 10-6 MPa (Reference: I.C. Noyan and J.B. Cohen, Residual stress, 1987, Springer- Verlag,


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New York) Bragg angle: 155.843 º for Cr source The amount of Residual stresses is measured by

Diffractometer using X-ray diffraction method. (XRD).The

Graph1: Component XRD before Shot Peen Graph2: Component XRD after Shot Peen

Measurement of residual stress by X-ray diffraction (XRD) relies on the fundamental Interactions

between the wave front of the X-ray beam, and the crystal lattice. For further information regarding these

interactions the reader is referred to Huygens principle and Young’s double slit experiments nλ = 2dsinθ

This is now commonly known as Bragg’s Law and it forms the fundamental basis of X-ray diffraction

theory. The Instrument used is X-ray diffractometer- Analytical Make X-Ray Diffractomer X’PERT

PRO.Kα Radiation: Chromium source, wavelength 2.289760 Å, Parallel beam geometry with

poly-capillary lens and parallel plate collimator.

As a result of the tilt, the d spacing decreases and the angle 2θ increases, as seen in the figures. In this

case the d spacing acts as a strain gauge. Because of the fact that the inter planar spacing is so small, both

micro and macro stresses will effect it. The XRD measures sum of all these stresses.

Table 6 Residual Stress & FEM Calculated Stress

3. Conclusions

1.17005

1.17010

1.17015

1.17020

1.17025

1.17030

0.0 0.1 0.2 0.3 0.4

d-sp

acin

g (Å

)

sin² (Psi)

Normal stress: 53.2 ± 10.6 MPaShear stress: 2.8 ± 1.5 MPa

Psi >= 0Psi < 0

Phi = 0.00°

151 152 153 154 155 156 157 158 159 160 1612Theta-Omega (°)

0

200

400

600

800

Inte

ns

ity (

co

un

ts)

1.1698

1.1699

1.1700

1.1701

1.1702

1.1703

0.0 0.1 0.2 0.3 0.4

d-sp

acing

(Å)

sin² (Psi)


Psi >= 0Psi < 0

Phi = 0.00°

151 152 153 154 155 156 157 158 159 160 161

2Theta-Omega (°)

0

200

400

600

800

Inte

nsity (counts

)

Test Specimen Residual Stresses By

FEM (Mpa)

Residual Stresses by XRD Method

(Mpa)

Error

%

1 340.00 288.32 15.20%

2 338.00 302.91 10.38%

3 334.00 293.42 12.15%


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[1] Impact velocity significantly influences the stress profile. The increase of velocity improves the

stress distribution up to a particular point. Further increase in the velocity may reduce the

maximum stress.

[2] For the particular given set of values of parameters Shot Size 0.75 mm, Shot Velocity 40m/s,

Impact angle 45˚ and Shot Distance 150 mm is the optimum parameter set. The deflection for this

was 135.0 microns. Residual stress is 338.0 MPa for this.

[3] Single impact modeling of shot peening showed good agreement with experimental results. When

the actual peened parts were check maximum error was of 15.2%

[4] The optimum solution for maximizing the residual stress is Shot Size 0.75 mm, Shot Velocity

40m/s, Impact angle 45˚ and Shot Distance 150 mm. Residual stress at this iteration is 338.00

MPa.

[5] Maximum deflection is of 135.0 microns Shot Size 0.75 mm, Shot Velocity 45m/s, Impact angle

45˚ and Shot Distance 150 mm iteration.

[6] Maximum residual stress was of 338.0 MPa at Shot Size 0.75 mm, Shot Velocity

40m/s, Impact angle 45˚ and Shot Distance 150 mm iteration.

[7] It is seen that there is very less effect of shot peening on residual stresses below 1 mm

from peened surface.

[8] The measurement of residual stress was done by XRD measurement method. The

actual results are in range of 84.80% to 89.62% of Finite Element Modeling

Iterations which checked by physical experimentation.

[9] The results of Finite element analysis using LSDYNA FEA Solver found in good

agreement with the experimental results and hence the work is validated.

3 References

[1] Deslaef D, Rouhaud E, Rasouli-Yazdi S. “3D finite element models of shot peening processes”, Mater Science forum

2000

[2] Tao Wang and Jim Platts,” Finite Element Impact modeling for Shot Peen Forming” ,Conf Proc:

ICSP-8 ,Garmisch-Partenkirchen, Germany,2002


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[3] Daniel B. Barrios, Edvaldo Angelo, Edison Goncalves, “Finite element shot peening simulation for residual stress

analysis and comparison with experimental results”,MECOM 2005 – VIII, Congreso Argentino de Mecánica

Computacional

[4] N Hirai, K Tosha, E Rouhaud,” Finite Element Analysis of shot peening-On the form of a single dent”, Conf Proc:

ICSP-9 , Paris, France ,2005

[5] S.A.Meguid, G.Shagal, “Development and validation of novel FE model for 3D analysis of peening of strain rate

sensitive materials.” Journal of engineering materials and technology, 2007

[6] Miao, Perron, Levesque,” Finite element simulation of shot peening and stress peen forming”, Conf Proc: ICSP-10,

Tokyo, Japan ,2008

[7] B. Bhuvaraghan, S. M. Srinivasan, B. Maffeo, R. McClain, Y.Potdar, Om Praksh,” Shot Peening Simulation using

Discrete and Finite Element Methods”, Conf Proc: ICSP-11 , South Bend,Indiana, USA ,2010

[8] S.M.H-Gangaraj, Y.Alvandi-Tabrizi, G.H.Farrahi, G.H.Majzoobi , H.Ghadbeigi,” Finite element analysis of

shot-peening effect on fretting fatigue parameters”, Tribology International, 2011

[9] Gangaraj, Guaglio, Farrahi,” An Approach to relate the shot peening element simulation to actual coverage”, Surface &

Coatings Technology, 2012

[10] Bagherifard, Ghelichi, Guagliano, “On the shot peening surface coverage and its assessment by means of finite element

simulation: A critical review and some original developements”, Applied Surface Science, 2012

[11] Guagliano M, Vergani L, Bandini M, Gili F. “An approach to relate the shot peening parameters to the induced residual

stresses”, Conf Proc: ICSP-7, Warsaw, Poland, 1999.

[12] Meguid S.A, Shagal G, Stranart JC, Daly J. “Three-dimensional dynamic finite element analysis of shot-peening

induced residual stresses”, Finite Element Analysis. ,1999

[13] S. Curtis, E.R. de los Rios, C.A. Rodopoulos, A. Levers,” Analysis of the effects of controlled shot peening on

fatigue damage of high strength aluminum alloys”, International Journal of Fatigue, 2003

[14] Gariepy, Bridier, Hoseini, Bocher, Perron, Levesque,” Experimental and numerical investigation of material

heterogeneity in shot peened aluminum alloy AA2024-T351”, Surface & Coatings Technology, 2013


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FATIGUE LIFE PREDICTION &ENHANCEMENT OF PMG COVER

AL 2024 ALLOY

Mr.Atul Pathak 1, Prof Dr Kadam Munjadas

2

Department of Mechanical Engineering, Jawaharlal Nehru Engineering College, Aurangabad, India1

[email protected]

Department of Mechanical Engineering, Jawaharlal Nehru Engineering College, Aurangabad, India

[email protected], [email protected]

Abstract : Engineering components and structures are regularly subjected to cyclic loading and they are

consequently lead to fatigue damage. In most cases, fatigue damage will initiate at the surface due to

localized stress concentrations caused by machining marks, exposed inclusions or even due to the

contrasting movement of dislocations. Evidently, control over the initiation and early propagation of

surface cracks is paramount for prolonging the fatigue life of components. Shot peening is cold working

process which is extensively used in automotive and aircraft industries for the above purpose as it

produces near surface plastic deformation leading to the development of work-hardening and high

magnitude compressive residual stresses. Work hardening is expected to increase the flow resistance of

the material and thus reduce crack tip plasticity, while, the residual stresses can act as: a) mean stress

modulators in the case of the onset of crack propagation or b) closure stress in the case of crack growth.

Compressive residual stress values found by Experimental X- ray Diffraction methods. The investigate

the improvement in fatigue strength of the ASTM standard specimen by performed experimentation work

on “Rotating Bending Testing Machine” calculate Enhancement in the fatigue life of the component by

comparing with No. of cycle values between predicted and with & without Shot Peening Component.

Keywords ASTM standard, Compressive Residual Stresses, Displacement, Shot peening

XRD Machine.

Fatigue life prediction has been studied and proposed for PMG Cover Al 2024 alloy material.

1 Introduction:

Fatigue is an important parameter to be considered in the behavior of components subjected to constant

and variable amplitude loading. Fatigue is of great concern for components subject to cyclic stresses. It

has long been recognized that fatigue cracks generally initiate from free surfaces and that performance is

therefore reliant on the surface topology/integrity produced by surface finishing. It is well known that, in

service, many more components and structures fail by cyclic than by static loading. The failure by

fracture depends on a large number of parameters and vary often develops from particular surface areas of

engineering components. Therefore, it is possible to improve the fatigue strength of fatigue components

by the application of suitable surface treatments. Nowadays, manufacturers are utilizing different surface

treatments in order to enhance the surface properties of engineering materials. So far, there are various

methods which have been employed to improve the fatigue strength. The principal surface treatments


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such as carburizing or carbonitriding, carried out on many mechanical components before their delivery,

are aimed to differentiate the response of surface and core to external loading by changing the surface

material properties and by introducing appropriate residual stress distribution in order to improve their

fatigue and wear behavior. Among the different treatments that can be carried out to locally improve the

material response and to modify the stress field, this is a combination of case hardening followed with

other surface treatments. Due to the case hardening, the nitriding, shot peening improvement of the

residual stress profile make impact on fatigue life (F.S. Silva Engineering Failure Analysis, 2006). Shot

peening followed by case hardening is capable of improving both the microstructure and the residual

stress distribution of the components. Usually residual stresses are introduced by shot peening because of

the intense plastic deformation in the surface region.

1.2 Fatigue Life Prediction:

The parts under fatigue loadings are considered to fail much below the yield strength of the material. In

critical applications like aeronautics, engines or where part failure means losing of human lives; we can’t

take any chances of any possible mistak. As discussed earlier fatigue life is affected by many factors at a

time. Many times it’s not in hand of designer to guaranty of exact fatigue life as many working conditions

are not in his hand. But many years the research has been carried out to predict fatigue life. In this

particular chapter, we will try to study fatigue life prediction & to predict fatigue life range for our

specimen.

1.2.1 Research on Fatigue Life Prediction:

Liu et.al. (2012) gave fatigue life prediction of AISI 4340 steel. In this paper authors proposed an

analytical method & then it was integrate with Findley model for prediction of fatigue life. The residual

stresses can be predicted or simulated by FEA, which can be used to calculate the fatigue life. But stress

relaxation is the problem for error in calculation. This paper also throws light on over peening will reduce

the fatigue life rather than increasing it. Commercial code ABAQUS is used as FEA tool with 8-Node

bi-quadratic axi-symmetric element. The proposed model shows good agreement with experimental

results.

Xiang and Liu (2010) gave fatigue life prediction in very detailed way. They gave a new model to predict

fatigue life of mechanical model. The proposed methodology based on the crack growth analysis of shot

peened specimens, which are affected by the interaction of surface roughness and residual stress produced

during the shot peening process. An asymptotic stress intensity factor solution was used to include the

surface roughness effect and a time varying residual stress function was used to change the crack tip

stress ratio during the crack propagation. Parametric studies were performed to investigate the effects of

surface roughness and the residual stress relaxation rate. Following this, a simplified effective residual

stress model was proposed based on the developed mechanism modeling. A wide range of

experimentation was performed to check validation of model. They studied Al 2024 material for their

study.

Cláudio et al. (2008) studied fatigue life prediction of nickel based super alloy. They studied research in

past & after that they put forth their own method for prediction using FEA. The Finite Element Method

was used to determine the stress, strain and strain energy due to shot peening. Fatigue life calculated


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using total fatigue life predictive methods which are normally used for notched geometries, gave

conservative results for almost all of the situations. The strain life method gave the most conservative

results. In their case, fatigue life predictions with and without shot peening is almost the same, which was

not in agreement with the experimental results. The strain energy density life prediction approach

provides results quite close to the experimental observations for all cases studied without shot peening.

However if residual stress is considered, this method did not provide reliable life predictions.

Guechichi et al.(2005) also gave fatigue life prediction for shot peening process. According to authors,

cold work done during the shot peening gives more impact on fatigue life than residual stresses does.

They studied Nickel-Chromium alloy. The shot peening was carried out by using steel shot S 230 of 0.57

mm of diameter, an Almen intensity of 0.30 - 0.35 mm A, and coverage of 200%. They gave an analytical

model on prediction. For experimentation they studied torsion fatigue, Torsion-Compression fatigue &

rotary bending fatigue. Stress gradient and topography effects were not induced in this analysis. Predicted

fatigue limits were generally slightly lower than those measured ones.Graph 01 Shows Aggrawal et

al.(2006) S/N curve for EN45 Spring steel

Graph 1: Spring Steel EN45A S/N Curves

1.3 Fatigue Life Prediction for Al-2024 alloy:

Xiange and Liu (2010) & Mehmood (2007) studied fatigue life of Al-2024. Xiange studied detailed

Fatigue life predictions. Mehmood studied fatigue behavior of Al 2024. Both are explained below.

1.3.1 Xiange and Liu model:

For Xiange and Liu, they gave model as in Graph 2 for their fatigue life of induced residual stresses of

180 MPa and 150 MPa resp.

Graph 2:- Fatigue Life Prediction by Xiange and Liu

Left fig has induced compressive residual stress of 180 MPa with mean peak valley height 30 microns.

The right fig has induced compressive residual stress of 150 MPa with mean peak valley height 25

microns. For 215 MPa applied stress range will give following number of cycles & gain% as shown in


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Table 1

Table 1: Xiang and Liu Model

Specimen Fatigue Life Gain (%)

Unpeened 5.88×105 -

180 MPa 30.9×105 425.55

150 MPa 41.6×105 607.48

1.3.2 Mehmood Study:

Mehmood Studied shot peening behavior of Al-2024.He studied 2 applied stresses on 242 MPa induced

stress. The results are as shown in table 2

Table 2: Mehmood Research

Applied Stress Fatigue Life(Unpeened) Fatigue Life(Peened) Gain (%)

250 1.8×104 5.06×104 166

150 2.25×105 8.3×105 484

1.3.3 Fatigue Life Prediction:

1. The higher gain like Xiang model is not possible in our case since the displacement is predicted by FEM

is from 100 microns to 153 microns for the iteration sets.

2. We can predict by residual stress effect only as per scope & experimentation limitations.

3. 224 MPa induced stress is near to Iterations like 338,334 & 340 MPa. But they not exact to our iterations.

Also Mehmood used different shot peening conditions, so the results cannot be applied as it is.

4. Also applied range of stress is different (250 MPa) than we are going to apply.

5. So we can Predict following things

i. No high gain as Xiang is possible

ii. The gain(%) predicted in 50% range

1.5 Discussion As per table 3 The Fatigue Life Prediction is done

Table 3: Fatigue Life Prediction

Residual Stress(Actual)(MPa) Applied Stress Range(MPa) Predicted Gain (%)

334 250 160 to 210

338 250 150 to 200

340 250 140 to 190


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2 Experimentation

2.1 Shot Peening

Experimental Work of Shot Peening is carried out at “Rushash Engineering Cooperative Pvt. Ltd” 414111

MIDC Ahmednagar table 4 get from the MINITAB 14 software

Table 4: Response Table for Signal to Noise Ratios

Shot

Size mm

Velocity

m/ s

Impact

Angle

Deg

Distance

mm

Immediate

Stresses in

MPa

SNRA2 MEAN2

0.65 30 45 190 371.64 -51.4024 371.64

0.65 40 65 120 49.7 -33.9271 49.7

0.65 45 80 150 12.03 -21.6053 12.03

0.65 60 85 190 8.22 -18.2974 8.22

0.75 30 65 90 39.43 -31.9165 39.43

0.75 40 45 150 1149.5 -61.2102 1149.5

0.75 45 85 90 12.56 -21.9798 12.56

0.75 60 80 120 36.03 -31.1333 36.03

1 30 80 190 31.8 -30.0485 31.8

1 40 85 150 17.64 -24.93 17.64

1 45 45 120 585.64 -55.3526 585.64

1 60 65 90 338.2 -50.5835 338.2

1.25 30 85 120 26.96 -28.6144 26.96

1.25 40 80 90 64.36 -36.1723 64.36

1.25 45 65 190 339.86 -50.626 339.86

1.25 60 45 150 880.7 -58.8966 880.70


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Table 5- Experimentation Iterations

The exposure time is set constant, equal to 120 sec for all specimens as it will have 100% coverage as per

previous data in literature review.

2.1.1 Specimen Composition

The project has been carried out to improve the fatigue life PMG Cover of Al-2024 material by shot

peening method. The material composition is shown in Table 6 below

Table 6- Al 2024 Material Composition

Test specimen (Fig.1) used for shot peening and fatigue testing is shown below. (S B Mahagaonkar IE (I)

Journal-PR, September 2009)

Shot Size

mm

Velocity

m/ s

Impact Angle

Deg

Distance

mm

0.75 30 45 120

0.75 40 45 150

0.75 45 45 190

Name of Material Concentration Limit

Copper 3.8-4.9 % max,

Magnesium 1.2-1.8 % max,

Silicon 0.50 % max,

Iron 0.50% max.

Manganese 0.3-0.9 % max.

Zinc 0.25 % max.

Titanium 0.15 % max.

Aluminum Remainder %

Chromium 0.1 %

Reminder 0.15%


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Fig.1 Test Specimen for Fatigue Testing

In Fig 2 Standard unpeened specimen has been shown

Fig 2 Standard Unpeened Specimen Fig 3 Shot Peened Specimen

2.1.2 Shot Peening Procedure-:

1) Feed the shots through hopper.

2) Adjust valve for desirable flow rate of shots.

3) Load the standard test specimen in fixture and close the door.

4) Set the air speed for desirable shot speed.

5) Set the cycle time.

6) Start the cycle.

7) Open the door after cycle completion and run same cycle for remaining half portion of specimen.

8) Repeat the procedure for another specimen.

9) Set the new shot speed and repeat the procedure.

2.1.3 Residual Stress Measurement:

Measurement of residual stress accurately is one of the critical tasks. Many of researchers used following

two methods to obtain residual stress level after shot peening. This one method is mentioned below.

a) X-Ray Diffraction Method-:

Diffraction methods (shown in Fig.4 and 5) of residual stress determination basically measure the angles

at which the maximum diffracted intensity take place when a crystalline sample is subjected to x-rays.

From these angles it is possible to obtain the inter-planar spacing of the diffraction planes using Bragg’s

law. If the residual stresses exist within the sample, then the d spacing will be different than that of an

unstressed state. This difference is proportional to magnitude of the residual stress.

R = 12 Inch


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Fig 4 Diffractometer Scheme Fig. 5 Diffraction at Tilted Position

The incident beam diffracts X-rays of wavelength λ from planes which satisfy Bragg’s law. If the surface

is in compression then the planes are further apart than in the stress-free state because of Poisson’s ratio.

The inter planar spacing “d” is obtained from the peak in intensity versus scattering angle and Bragg’s law,

assume that the detector is turned over a range of angles, 2θ, to find the angle, θ, of the diffraction from

grains which satisfy Bragg’s law. In other words the grains that have planes of atoms with inter planar

spacing “d” such that λ =2dsinθ. The grains that have planes with this spacing that are parallel to the

surface will diffract as in Fig. 8.4. This diffraction occurs from a thin surface layer which is about 20 µm.

If the surface is in compression, then the inter-planar spacing “d” is larger than in the stress free state as a

result of Poisson’s effect. When the specimen is tilted with respect to the incoming beam new grains will

diffract and the orientation of the diffraction planes is more nearly perpendicular to the stress direction.

Fig 6 X- RAY Diffraction Machine

analytical Make X-Ray Diffractomer X’PERT PRO.Kα Radiation: Chromium source, wavelength

2.289760 Å Parallel beam geometry with poly-capillary lens and parallel plate collimator’s X-Ray elastic

constant: 5.85 x 10-6 MPa (Reference: I.C. Noyan and J.B. Cohen, Residual stress, 1987, Springer- Verlag,

New York) Bragg angle: 155.843 º for Cr source The amount of Residual stresses is measured by

Diffractometer using X-ray diffraction method. (XRD).The measurement of residual stress by X-ray

diffraction (XRD) relies on the fundamental Interactions between the wave front of the X-ray beam, and

the crystal lattice. For further information regarding these interactions the reader is referred to Huygens

principle and Young’s double slit experiments nλ = 2dsinθ this is now commonly known as Bragg’s Law

and it forms the fundamental basis of X-ray diffraction theory. The Instrument used is X-ray

diffractometer- Analytical Make X-Ray Diffractomer X’PERT PRO.Kα Radiation: Chromium source,

wavelength 2.289760 Å, Parallel beam geometry with poly-capillary lens and parallel plate collimator.


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Graph 3: XRD of Component before Shot

Peening Graph 4: XRD of Component after Shot Peening

As a result of the tilt, the d spacing decreases and the angle 2θ increases, as seen in the figures5In this

case the d spacing acts as a strain gauge. Because of the fact that the inter planar spacing is so small, both

micro and macro stresses will effect it. The XRD measures sum of all these stresses.

2.1.4 Fatigue Testing

A material testing to obtain S-Nf Curves is common; several ASTM standards address stress-based

fatigue testing. The "Rotating Bending Testing Machine" is similar to the original railroad axle-type

Wohler used where the bending moment is constant along the beam length. Each point on the Surface of

the Rotating Bend Specimen is subjected to fully-reversed cycling (σm = 0) and the tests are generally

constant amplitude. In this machine surfaces of machine are alternately transferred from compressive

stress state to tensile stress state. Following Fig.7.4 shows rotating bending testing machine set up. This

machine have two chuck , one chuck joint to the motor with the help of flexible coupling, and another

chuck is rigidly fixed. We fix component in these two chucks which have facility to apply required load

vertically threw link attached to bearing housing as shown in Fig.7

Fig 7: Rotating Bending Testing Machine Fig 8: Job Mounted Fatigue Testing Machine

After fixing component in chuck we can apply load on it threw link provided. Due to this load initially

upper surface of specimen goes in compression and bottom surface is in tension. When we rotate this

1.1698

1.1699

1.1700

1.1701

1.1702

1.1703

0.0 0.1 0.2 0.3 0.4

d-sp

acin

g (Å

)

sin² (Psi)


Psi >= 0Psi < 0

Phi = 0.00°

151 152 153 154 155 156 157 158 159 160 1612Theta-Omega (°)

0

200

400

600

800

Inte

ns

ity

(c

ou

nts

)

1.17005

1.17010

1.17015

1.17020

1.17025

1.17030

0.0 0.1 0.2 0.3 0.4

d-sp

acin

g (Å

)

sin² (Psi)


Psi >= 0Psi < 0

Phi = 0.00°

151 152 153 154 155 156 157 158 159 160 1612Theta-Omega (°)

0

200

400

600

800

Inte

ns

ity

(c

ou

nts

)


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specimen using electric motor nature of stress on surface of component is altered continuously .This will

simulate fatigue environment. Out of these two chucks one is fixed and other is flexible in up and down

direction to allow the bending in specimen. In this way each surface is placed tension and compression.

This fatigue loading breaks the component after some time by using the time required to breaks the

component we can calculate no. of revolution before failure. This procedure is repeated for no. of

components. Fig 7 shows fatigue testing machine Model: 550LE Force: Six actuators rated from 2.6kN

(580 lb) to 55 KN (12,400 lb) Speed: Speeds to 40 in/s (1m/s); Rated for high cycle fatigue applications

up to 15 Hz.

2.1.5 Fatigue Testing Procedure-:

1) Fix the standard test specimen in machine chuck.

2) Apply load through weight hanger.

3) Run the machine till specimen gets fractured.

4) Record the reading from cycle counter.

5) Repeat the procedure for next specimen.

Fig 9: Fatigue Testing Failure of Specimen

2.1.6 Fatigue Testing Results.

The fatigue testing results are as shown in Table 7

Table 7: Results of Fatigue Testing

Specimen Type Fatigue Life Predicted Gain (%) Actual Gain (%)

Unpeened 1.60×105 - -

Peened 1 4.35×105 160 to 210 175.0

Peened 2 4.48×105 150 to 200 188.0

Peened 3 4.30×105 140 to 190 170.1

3. Conclusions:

Conclusions from the study are stated below on PMG Cover of Al 2024 Alloy.

1. The measurement of residual stress was done by XRD measurement method. The actual results

are in range of 84.80% to 89.62% of Finite Element Modeling iterations which checked by

physical experimentation.

2. The fatigue life was checked by rotating beam bending machine. The fatigue life gain was

170.10%, 175.00% & 188.00% for the specific peened components.

3. It is seen that there is very less effect of shot peening on residual stresses below 1 mm from

peened surface.


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4. Fatigue life prediction was carried out for PMG Cover of Al 2024 by past data available for the

material and present peening condition in 50% Gain Accuracy. The fatigue life’s predicted gain

was from 150% to 200%.

5. The fatigue life gain was varied from 170.0% to 188.00% for the peened specimens.

4. References

1. Rahman M.M., Ariffin A.K., Jamaludin N., Haron H.C.,” Influence of surface treatments on fatigue life a two stroke

free piston linear engine component using random loading”, Journal of Zhejiang Unviversity,2006

2. M.L. Aggarwal, V.P. Agrawal , R.A. Khan, “A stress approach model for predictions of fatigue life by shot peening of

EN45A spring steel.”, International journal of fatigue, 2006

3. Arshad Mehmood and M.M.I. Hammouda,” Effect of Shot Peening on the Fatigue Life of 2024 Aluminum

Alloy”,Failure of Engineering Materials & Structures,2007

4. A.Inoue, T.Sekigawa, K.Oguri,” Fatigue property enhancement by fine particle shot peening for aircraft aluminum

parts”, Conf Proc: ICSP-10, Tokyo, Japan, 2008.

5. S.B.Mahagaonkar, Dr.P.K.Brahmankar, C.Y.Seemikeri, “Influence of shot peening parameters on fatigue life and

surface hardness of AISI 1045 materials”, IE journal-PR, 2009.

6. Zhou Wang, Chuanhai Jiang, Xiaoyan Gan, Yanhua Chen, Vincent Ji,” Influence of shot peening on the fatigue life of

laser hardened 17-4PH steel”,International Journal of Fatigue,2011.

7. Gariepy, Bridier, Hoseini, Bocher, Perron, Levesque,” Experimental and numerical investigation of material

heterogeneity in shot peened aluminum alloy AA2024-T351”, Surface & Coatings Technology, 2013

8. Jinxiang Liu, Ming Pang, “Fatigue life prediction of shot-peened steel”, International Journal of Fatigue, 2012.


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WATER PURIFICATION SYSTEM BY USING MECHANICAL

ENERGY

THIMMALA.CHALAPATHI

SRI VASAVI ENGINEERING COLLEGE, INDIA,

ABSTRACT

The aim of this paper is to discover whether human powered reverse osmosis is a viable option for

producing potable water for developing countries. The matters at hand are to determine whether human

power is enough to operate such a system, how much clean drinking water it will produce, and if it

produces a reasonable amount for the work put in.

A device was designed to test the practicality of this idea through a numerical analysis. The device uses a

bicycle to harness human motion to convert it into usable power to run a reverse osmosis filtration system.

The flow rate was determined according to give information from the reverse osmosis manufacturer. This

was used to calculate the power needed to power such a design and was then compared with researched

data of available power from humans. It indicated that a human could easily provide enough power to run

a reverse osmosis system such as this. The flow rate was then used to determine how useful this power

was by considering how fast it could produce clean drinking water and how much water a person needs to

drink daily. Ultimately from all of the research and results, it was determined that human powered reverse

osmosis is not only a viable option, but an incredibly economical and effective means for providing

potable water for remote and sea basin areas.

The device uses a pedal to harness human motion to convert it into useable power to run a

reverse osmosis 5 stage filtration system. This was used to calculate the power needed to power such a

design and was then compared with researched data of available power from humans. It indicated that a

human could easily provide enough power to run a reverse osmosis system.

KEY WORDS: Water purification system, reverse osmosis, human motion,pedalpower.

INTRODUCTION


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The Human Powered Water Purification System is designed to address the difficulty of accessing clean,

safe water in isolated regions such as off-grid residences, camp grounds, summer cottages, etc. In many

cases, these remote residences have limited access to electricity and/or fuel. The Human Powered Water

Purification System is designed to reduce pathogenic contaminants as well as dissolved salts from source

water through the use of a reverse osmosis membrane process

Water is a common chemical substance essential for the survival of almost all known living

organisms. Water covers 71% of the earth’s surface, but 97% of this water exists as salt water in oceans.

Of all surface water, glaciers and icecaps hold approximately 2%, and freshwater rivers and lakes contain

only 1%. Yet many societies around the world do not give consideration and attention to preserving this

vital commodity that is in limited supply.

The Earth is covered by 75% water, yet one of the world’s greatest issues is a lack of drinking water.

Every Year,

almost four million people die from water-related diseases and 98% of those occur in the developing

World. In response to such a need, this idea is proposed to produce clean drinking water by reverse

osmosis Filtration by means of human power. There are several means to purify water; however, because

of its incredible Thoroughness, a reverse osmosis system has been preferentially selected for this design.

According to a 2007 World Health Organization (WHO) report, 1.1 billion people lack access to

an improved Drinking water supply, 88 percent of the 4 billion annual cases of diarrheal disease are

attributed to unsafe water And inadequate sanitation and hygiene, and 1.8 million people die from

diarrheal diseases each year. The WHO (world health organization) reports says almost two-billion people

in the world, (approximately 25% of the world's population) do not have access to safe drinking water.

Consequently, water consumption-related deaths (ranging from five to seven million deaths per year) are

probably the largest single cause of deaths in the world. It is estimated that in 2020, at the current rate, 75

million people will die each year of preventable water-related deaths .Most of these deaths are caused by

infectious diseases. However, a large number of deaths occur secondary to consuming non-pathogen

water pollutants.

Governments in many countries continue to neglect the most vulnerable people who do not

have easy access to clean water. This caused, at least in part, by the lack of adequate resources, lack of

priority, and/or disregard for the plight of people who do not have a voice, and the lack safe water and

sanitary facilities. To bridge this need, many charitable organizations have stepped in to provide this

essential live-saving commodity. During the past two decades, several methodologies were developed to

convert contaminated water and brackish water to clean potable water.

1.1 UNEP –REPORT:


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1.2.WORLD RESOURCE INSTITUTE –OVER ALL WATER RISK AREAS :

water purification system by using 5-stage RO –system

Descriptionlayout:

The salt water is stored in the water tank. The salt water is taken to purifier arrangement by the help of

pedal pump. The pedal is operated so that the pump operates. The pump wills the salt water from the tank

to the first filter. Then the filtered water will be sent through the second filter automatically because of

gravitational force. The first filter is the sedimentation filter and the second filter is the salt filter in

which salt from the water is removed and purified. After the filtering process takes place the filtered water

is collected in the collecting tank. Here we use a pedal and chain drive to operate the pump to pump the

water from low level to the high level for the filtering process. It is operated and human controlled. The

purifier removes the dust and unwanted particles in water. The purification process is completed after the

water is collected in a separate tank. The collected water may be used for further applications.

Block diagram


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Power source:

To run an RO system, there needs to be a form of energy applied to force pressure through it. The issue is

whether human power is actually enough to run an RO system and whether the potable water that is

produced from it is effective enough for the work put in. A pedal pump was chosen to harness human

power effectively because of its simplicity, widespread use, and relatively great power potential from

human leg strength.

Process:

The entire process of the design begins by adding salt water into the tank. All of the heavy sediment is

immediately removed as the water passes through several layered mesh micron filters. The initial filtering

step is crucial because the RO filter would quickly clog if it had to filter heavier sediments. The tank lid

must then be sealed securely so that pressure can be built in the tank. To set the purification system in

motion we need to begin pedaling the pedal. The water then enters the 5 stages of filters in the RO

system.

There are three stages of carbon pre-filters to improve taste, remove sediment, organic and inorganic

compounds. The first stage removes any very heavy Sediment down to five microns still left in the water

that the first set of filters did not catch. The second stage removes any unwanted color, taste, and odor.

This fourth stage is the heart of the system as it removes all particles down to 0.0001 micron in size. And

produce completely pure drinking water. In the fifth stage water passes through an anti-microbial filter

cartridge to prevent unpleasant odors, tastes and microorganisms.

From here, the water exits the system as potable water and rinse water. It is important to Note that only

the purest water is used for drinking and that alone. The rinse water however can be used in many ways

other than drinking, such as cooking, cleaning, or irrigation so that it never gets wasted.

Main parts &description:

In this project mainly these parts are plays unique role.


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Figure: 3.1 main parts

5 -STAGE FILTERATION PROCESS:

The water enters the 5 stages of filters in the RO system purification system. These are main stages

involved in this process

Stage: 1

In this stage sediment filter plays main role, and it removes sediments particles and improve taste and this

filter removes the impurities in size greater than 5 micron.

Stage: 2

In this stage granular activated carbon filter plays main role and it removes organic and in organic materials

with in size greater than 5micron.

Stage: 3

In this stage carbon block filter is mainly used for remove the chloride and organic compounds .it is the end

of the pre filter stage it is also removes the impurities which are greater than 5 micron

Stage: 4

Stage 4 is the heart of the purification process. In this stage RO membranes main role, by using micro

filtration it removes all particles down to 0.0001 micron in size. And produce completely pure drinking

water.

Stage: 5


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. In the fifth stage water passes through an anti-microbial filter cartridge to prevent unpleasant odors,

tastes and micro organisms.

water sample tests:

In this project we are take different water samples like sea

water, college bore water, TPG municipal water. These tests

are performed by our project team with help of district

public health laboratory, Eluru,INDIA. In the below table

contains results of water samples.

Graph- TDS vs Type of water sample

TYPES OF

ENERGY

PERFORMANCE

ELECTRICAL

ENERGY

(USING

MOTOR)

MECHANICAL

ENERGY

(USING

PEDAL

POWER

INPUT

5000 ml

5000 ml

OUTPUT 800 ml 520 ml

PURIFIED TIME

(sec)

5 .25 min

5 .25 min

RECOVERY (%)

16.2 %

10.4 %

Water

samples

TDS PH

Before After Before After

Sea

College

bore

TPG

municipal

30000

460

200

180

50

0.005

7.5

7.8

7.0

7

6.8

6.8


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Graph-PH vs type of water sample

Certificate from Government Authority:

It is the certificate given by Government of Andhra Pradesh ,INDIA and it indicates the results of water

sample (sea water) like fluoride, chloride, iron, total hardness of water sample etc..,


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MERITS& DEMERITS

Merits:

1. Pure Water on Demand – No holding tank or storage unit, just fresh flowing water when you need it

2. More Water, Less Waste – Runs at 75% efficiency, for every 10 gallons treated, 7.5 gallons of pure

water are achieved, produces up to 300 gallons of purified water per day

3. Smart System – Provides alerts for water quality, pressure leakage, filter capacity and replacement

4. Energy Efficient – Consumes very little power


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35

5. Low Maintenance – Automated valves, pumps and cleaning, easy-to-read, user-friendly LCD panel,

measures and reports Total Dissolved Solids (TDS)

6. Eco-Friendly Design – Housing and filters are recyclable & biodegradable

Health benefits:

� 1.prevents kidney and gall stones

� 2.prevents stomach cancer

� 3.prevents rheumatism and arthritis

Demerits:

1. The water is de mineralized. Since most mineral particles (including sodium, calcium, magnesium,

magnesium, and iron) are larger than water molecules, they are removed by the semi-permeable

membrane of the R.O. system.

2. The drinking water is acidic. One of the primary reasons R.O. water is unhealthy is because removing the

minerals makes the water acidic (often well below 7.0 pH). Drinking acidic water will not help maintain a

healthy pH balance in the blood, which should be slightly alkaline.

CONCLUSION:

The project carried out by us made an initiative step-in the field of water purification method. This project

has also reduced the cost involved in the water purification system. Project has been designed to perform

the entire requirement task which has also been provided.

Considering other water purification systems, a human powered reverse osmosis system is

not only feasible, but quite an economical and effective means for providing potable water for developing

nations.

FUTURE SCOPE

� Even RO system is more advantageous then other filtration process, this RO system removes

minute minerals that are required for human body.

� So a good purification system, must be developed that have combined usage of RO and retain

those minute minerals that are helpful for human body.

� REFERENCES

•••• SUNIL.J WINLASON

(Water purification by using reverse osmosis)

(INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGY &ADVANCEDENGINEERING)(IJETAE)

ISSN-2250-2459 ISO 9000:2008 ,VOL-3 ISSUE 12 DEC-2013


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36

•••• MICHAEL E.WILLIAMS

(A Brief review of reverse osmosis membrane technology)

Copyright @ EET Corporation and Williams engineering Services Company.


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SYLLABUS MAPPING USING ADVANCED INTERACTIVE

TECHNIQUES

Pravin Jadhao,Vishal Jagtap,Laxmikant Mahajan.

Author Details

PravinJadhao -computer engineering, Pune University, India. E-mail: [email protected]

Vishal Jagtap - computer engineering in Pune University, India. E-mail: [email protected]

Laxmikant Mahajan - computer engineering in Pune University, India. E-mail: [email protected]

KeyWords

OCR,TOC,SNI,Pattern Matching

ABSTRACT

In today's world, the amount of stored information has been enormously increasing day by day which is

generally in the unstructured form and cannot be used for any processing to extract useful information, so

several techniques such as summarization, classification, clustering, information extraction and

visualization are available for the same which comes under the category of text mining. Text Mining can

be defined as a technique which is used to extract interesting information or knowledge from the text

documents. In this work, a discussion over framework of text mining with the techniques as above with

their pros and cons and also applications of Text Mining is done. In addition, brief discussion of Text

Mining benefits and limitations has been presented. Students likes to do things digitally rather than paper

work so many software industries came forward to make syllabus digitally. To make things digitally they

requires syllabus of universities and to compare two different syllabus or with industries database. So

now this work is done manually and it takes lots of time to compare or map them.

Mapping means we have to map year, semester, subject, unit, chapter, topics of one file with

another file. It's difficult to map them manually so we make it easy by use of optical character

recognition(OCR) for image files and pattern matching for any document files. It will make the existing

technique efficient by approximately 50 percent or more in terms of cost and time.

1.0 INTRODUCTION


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The advancement in the technology, the techniques of teaching changes as time goes on. Now a days the

use of internet, mobile phones, personal systems is increasing tremendously. All work in educational

system going to be digital. So many software organization making it the syllabus in digital format. So

organization requires the syllabus of university to make it in digital format. But syllabus of any changes

in some period. All E-Teaching organization done syllabus mapping manually and it takes human

resources as well as lot of time to syllabus mapping with organization database. And each new university

has different syllabus with compared to other one. So always organization has to do syllabus mapping for

each university syllabus. Some universities may provides the syllabus in .pdf, .doc or sometimes in image

format(Hand written,snap etc.). To map the syllabus in image format with organizational database creates

some problem due to broken words in image. So here we are going to design a software which will be

map the syllabus efficiently without human efforts.

Text Mining is the process of extracting interesting information or knowledge or patterns from the

unstructured text that are from different sources. As the text is in unstructured form, it is quite difficult to

deal with it. Finding nuggets of interesting information from the natural language text is the purpose of

text mining[1].

2.0 RELATED WORK

In earlier days, syllabus mapping done by seeing each and every point in syllabus file, it requires lots of

efforts. To do this task it requires person and its very complicated task. So, to do this we use text mining

and optical character recognition technique.The basic form of information is data which is to be managed

and mined in order to create the knowledge. Data mining emerged in the 1980's to resolve the above

problem [1]. The goal of data mining is to discover the implicit, previously unknown trend and patterns

from the databases. And optical character recognition technique is implemented for conversion of image

files into any document file.

Text Mining [2] is the discovery by computer of new, previously unknown information, by

automatically extracting information from different written resources. A key element is the linking

together of the extracted information together to form new facts or new hypotheses to be explored further

by more conventional means of experimentation. Text mining is different from what are familiar with in

web search. In search, the user is typically looking for something that is already known and has been

written by someone else. The problem is pushing aside all the material that currently is not relevant to

your needs in order to find the relevant information. In text mining, the goal is to discover unknown

information, something that no one yet knows and so could not have yet written down.

Text mining is a variation on a field called data mining [3],that tries to find interesting patterns from

large databases. Text mining, also known as Intelligent Text Analysis, Text Data Mining or

Knowledge-Discovery in Text (KDT), refers generally to the process of extracting interesting and

non-trivial information and knowledge from unstructured text. Text mining is a young interdisciplinary

field which draws on information retrieval, data mining, machine learning, statistics and computational


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linguistics. As most information (over 80 percent) is stored as text, text mining is believed to have a high

commercial potential value. Knowledge may be discovered from many sources of information, yet,

unstructured texts remain the largest readily available source of knowledge.

3.0 SYSTEM WORKING

Method for mapping of syllabus of different university.

Designing of syllabus mapping system uses the methods as pattern matching which is used for matching

the words in two different files given as input from user. The pattern matching technique uses matching

algorithm. And optical character recognition technique uses Optimization algorithm to convert input

image file into text file for mapping purpose.

• Pattern Matching

Pattern matching is to find a pattern, which is relatively small, in a text, which is supposed to be very

large. Patterns and texts can be one-dimensional, or two dimensional. In the case of one-dimensional,

examples can be text editor and DNA analysis. In the text editor, we have 26 characters and some special

symbols, whereas in the DNA case, we have four characters of A, C, G, and T. In the text editor, a pattern

is often a word, whose length is around 10, and the length of the text is a few hundred up to one million.

• Optical character Recognition(OCR)

OCR is the acronym for Optical Character Recognition.This technology allows to automatically

recognizing characters through an optical mechanism. In case of human beings, our eyes are optical

mechanism. The image seen by eyes is input for 6 brain. The ability to understand these inputs varies in

each person according to many factors [4]. OCR is technology that functions like human ability of

reading.


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Figure3.1: system Architecture (working)

4.0 APPLICATION FEATURES

This application include some features collect-lively the major feature which makes this app-location

much productive than any other application is any person can handle this application just that person

know knowledge about English.

5.0 ADVANTAGES

1.Reduce time of matching mapping syllabus.

2Useful for teachers, students also for book publisher.

3.Client server application.


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4.Can post the result on SNI accounts.

6.0 Future direction

Mobile devices are becoming ever more important due in main to their ubiquity.The number of mobile

phone subscribers will increase to 8 billion in 2013. Because of the growth of smart phones in developed

nations and mobile services in poor nations. The learning techniques in education system also changed as

the mobile technology growing very rapidly. Students like digital things more than paper work. Now a

days, universities also provides syllabus in digital format and as students like digital things more many

software industries come forward to make syllabus digitally. As every university has some di_erent

syllabus than other university, so they re- quire the comparison between the syllabus with them. Also

some time industries requires some sort of comparison between two di_erent universities. Now a days it

will done manually by some human being. So, the process of mapping the syllabus takes lots of time.

Conclusion

The syllabus mapping system helps to map the two different files. It also compares two different format

file and capable of convert image files into text or any other format as per user requirement. Hence by use

of syllabus mapping system time of user saved too much for mapping syllabus of two different

universities. User also post the result of mapped syllabus on social sites like Facebook, Twitter, G+.

Image files are also converted into text and are mapped with text file or with any type of file. It can be

done efficiently. It will make the existing technique efficient by approximately 50 percent or more in

terms of cost an time.

Acknowledgment

Every work is source which requires support from many people and areas. It gives us proud privilege to

work on the project on “Syllabus Mapping Using Advanced Interactive Techniques" under valuable

guidance and encouragement of our guide Dr. D. V. Patil. We are also extremely grateful to our respected

H.O.D Dr. M. U. Kharat for providing all facilities and every help for smooth progress of our project. We

are also extremely grateful to our respected project co-ordinator Prof. ArchanaUgale providing all project

related guidance and every help for smooth progress of our project. I am also very thankful to Dr. V. P.

Wani, Principal for their continues support, guidance and motivation. At last we would like to thank all

the staff members and our Colleagues who directly or indirectly supported us without which the Project

work would not have been completed successfully


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References

[1] Martin Porter,\An Algorithm for Su_x Stripping.",1980

[2] Berry Michael W., (2004),\Automatic Discovery of Similar Words, in \Survey of Text Mining: Clustering, Classi_cation

and Retrieval, Springer Verlag, New York, LLC, 24-43.

[3] Navathe, Shamkant B., and Elmasri Ramez, (2000),\Data Warehousing And Data Mining in Fundamentals of Database

Systems, Pearson Education pvt Inc, Singa-pore, 841-872.

[4] Pranob K Charles, V.Harish, \A Review on the Various Techniques used for Optical Character Recognition", Jan-Feb 2012.

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