JABATAN BIOLOGI

FAKULTI SAINS DAN MATEMATIK

UNIVERSITI PENDIDIKAN SULTAN IDRIS

TUGASAN 3

MODELING AND SIMULATION

SEM 1 SESI 2013/2014

KURSUS : IMFORMATION AND COMMUNICATION TEKNOLOGY

IN SCIENCE

KOD KURSUS : SSI 3013

Nama : RAHMAH BT SOID

No. Matrik : D20112052298

Kumpulan : UPSI01 ( A131PJJ)

Nama Pensyarah : DR. AZMI BIN IBRAHIM

PM-3, Level 2, Block 01,

Proton City Campus

ASSIGNMENT 3 - SSI 3013

MODELING AND SIMULATION

MODEL

A representation of an object, a system or an idea in some form other than of the entity itself.

( Shannom)

SIMULATION

A Simulation of a system is the operation of a model, which is a representation of that system. The model is amenable to manipulation which would be impossible, too expensive or too impractical to perform on the system which it portrays. The operation of the model can be studied and from this properties concerning the behaviour of the actual system can be inferred .

APPLICATIONS :-

a. Designning and analyzing manufacturing system.

b. Evaluating a new military weapons system or tactics

c. Determining ordering policies for an inventory system.

d. Designing communications systems and message protocols for them.

e. Designing and operating transportation facilities such as freeways, airports

subways or ports.

f. Evaluating designs for servicesorganizations such as hospital, post office or fast food restaurants.

g. Analyzing financial or economic system.

THE IMPORTANT OF SIMULATION IN EDUCATION :-

a. Intructional simulations have the potential to engage students in “deep learning” that empowers understanding as opposed to “surface learning” that requires only memorization.

b. Using instructional simulations gives students concrete formats of what it means to think like a scientist and do scientific work.

c. Simulation allows students to change parameter values and see what happen.

d. a feel for students develop what variables are important and the significance of magnitude changes in parameters.

e. Simulations help students understand that scientific knowledge rests on the foundation of testable hypothesis.

WHAT IS STELLA?

STELLA stands for System Thinking for Education and Research. STELLA offers a practical way to dynamically visualize and communicate how complex the system and ideas really work.STELLA is used to stimulate a system over the time, jump the gap between theory and the real world and also it enable students to creatively change the system. STELLA teach students to look for a reletionships and also it create a clear communication system inputs and outputs to demonstrate the outcomes.

There are many topics that’s can be contruct by using STELLA. For examples below :-

1. Amalgamated Industries

Think through the consequences associated with the development of a widget plant upstream from th..

2. Animal Temperature

Explore the laws of thermodynamics with this animal temperature model. As you experiment, t..

3. Balloon Problem

This model illustrates how a simple interface can facilitate experimentation with a mathematics m..

4. Distance and Time

Experiment with different velocities and find out how they impact the solution to this typical di..

5. Extraverts and Introverts

This map (not a running simulation model) uses STELLA's storytelling feature to explore the conce..

6. H1H1 Flu Outbreak

What is most effective in controlling the outbreak of a flu virus in schools? Is it better to vac..

7. Limits to Growth

Growth processes have inherent limits to growth. Identifying these limits can help avoid pr..

8. Michaelis-Menten Dynamics

The Michaelis-Menten equations are taught in virtually any unit on enzyme kinetics. The problem, ..

9. Mystery on the Island of Borneo

What do the bubonic plague, falling roof beams and dead fish have in common? Read this story and ..

10. Natural Selection Pressure

In this model, a rabbit population comes under a natural selective pressure from a fox population..

11. Non-Seperable Differential Equations

Analytically daunting or deceptively simple? The model represents a classic problem—that of mixin..

12. One- dimensional diffusion

Simulates the diffusion of heat through a one meter metal bar when the ends are held at a constan..

13. Overturned Truck

You’re driving on the highway and around the curve is an overturned truck. Can you stop in time? ..

14. Pendulum Story

Consider what happens when you connect a small ball (or bob) to the end of a string. When t..

15. Pharmacokinetics

Play the role of physician, trying to keep the drug level in a virtual patient’s bloodstream in t..

16. Plant Succesion Dynamics

See how plants in the ecosystems move through the successional stages of forb, grass, shrub, pine..

17.Predator Prey Dynamics

As the manager of a small but thriving natural wilderness area, would you allow a one-time harves..

18. President & Prime Minister

Whose coffee cools faster? This question quickly becomes relevant for the president and the prime..

19.Reversible Reactions

Storytelling is used to present the basic structure of a reversible chemical reaction. Experiment..

20. Sustainable Shrimping

This Learning Environment should help you understand some basic population dynamics and their rel..

21. Temperature Control

Conduct experiments and try to maintain a constant temperature in a house that uses a climate con..

22. Virtual Bungee

Virtual bungee jumpers can experiment with different body weights and bungee cord strengths. Then..

23. Virtual Hamlet

Use this virtual laboratory to explore the plot and character development in one of Shakespeare's..

STELLA present four model building blocks that are used in the modelling process: Stocks, flows,connectors and converter.SSSSSSSSS.

Stocks: The basic building block is the stock that is used to represent anything that

accumulates (populations, biomass, nutrients, water). These are tangible, countable,

physical accumulations. You can also use stocks to represent the degree of non-

physical accumulations such as knowledge or fear.

Flows : Flows are used to represent activities that lead to inputs and outputs to stocks. Flows

include births, migration and nutrient or biomass transport. These activities will

change the magnitude of stocks in the system.

Connectors: Connectors transmit information to regulate flows. Connectors can connect into

flows or converters but never into stocks. Only flows affect the magnitude of stocks.

However, connectors can affect both input and output flows.

Converters: Converters contain equations that generate an output value during each time

interval of a simulation. Converters often take in information and transform it for

use by another variable in the model. They are also handy for storing constant

values.

EXAMPLE :

TEMPERATURE CONTROL

How we can control the temperature in a house.

Find out in this simulation by exploring the dynamics of maintaining the desired temperature in a house, using a climate control system.

EXPLORE THE MODEL

Based on the diagram below.

The model of this system consists of several balancing feedback loops linked to the temperature of the house.

TOUR THE MODEL

1. The house temperature can go up or down depending on the outside temperature. If the outside temperature is warmer the house will “gain” temperature. If the outside temperature is colder, there will be a heat “loss”.

2. According to Newton’s Law of cooling this heat exchange is proportional to the difference between the house temperature and the outside temperature.

3. The rate of heat exchange is determined by the insulation of the house. This constant measures the time it takes for heat to transferbetween the house and it surrounding. The greater the value of this constant , the better the insulation of the house.

4. As the house gain of loses heat to the outside its temperature move away from the thermostat setting or target temperature.

5. That is when the heating and cooling system kick in. The house heating/cooling system uses a controller with two types of mechanisms for determining when to turn on the hearter or air conditioner.

6. The first type is a “ proportional” controller. It reacts proportionally to the difference between the house temperature and the thermostat. In this model we call that difference an “ error signal”.

7. The second type of mechanism is an “ intergral” controller. It operation is base on the cumulative sum of errors over time. A fancier way to say the same thing is the intergral controller operates according to the “ intergration of errors”. The resulting sum can be either positive or negative.

8. Response time also plays a factor in the intergral controller as it does with the time it takes the system to change the temperature of the house. A smaller time constant means the heating / cooling system is capable of changing the temperature.

NEXT FOR SIMULATE

In order to run the simulation based on the graph below,

Firstly, we have to set ( based on graph number 1)

- thermostat setting reading is 68- ambient temperature reading is 32

- Temp loss time constant is 5

Resulting

- Temp of house is 39

Next, based on the graph number 2

We adjust the reading of the number of

- Thermostat setting is 53- Ambient temperature is 32

- Temp loss time constant is 7

Resulting

- Temp of house is 48.2 ( temp is increase)

Lastly, based on the graph number 3.

When we adjust the parameter to maximum reading, the temp of house is very hot.

Resulting

- Temp of house is 70.6

Or we can adjust to another reading of parameter.

n

CONCLUSION

Simulation can be a powerful learning experiment. Using simulation in teaching and learning have the potential to engage students in deep learning that will empowers understanding about the whole topics. Since simulation required the students to be the researchers and conduct the simulation by them this will engage students to their learning. Simulation allow students to change parameter value and see what happen.

Therefore they will see clearly the relationship among variables. Simulation offer students the opportunity to manipulate content knowledge and this will engages a variety of learning styles. With simulation, we can use model to predict outcomes. It is easier for the students to learn using simulation because as they change the parameter, they can predict what will happen.

Furthermore, simulation help students understanding scientific knowledge by testing hypothesis. This is due to the fact that simulation are very good at making clear the complexities involved in issues. Also STELLA can increase the students motivation. I would recommend others to use STELLA as well.

REFERENCES

Maria A. (2002). Introduction to modelling and simulation. Retriered December 1st 2012

From http://www-inf.utsfm.cl-hallende/download/

Weimer M. (2010). Simulation Deliver Real Benefits. Retriered December 1st 2012 from

http://www.teachingprofessor.com/articles/teaching-and-learning/simulation

http://www1.union.edu/rices/stella/stella_intro.html

http://home.ubalt.edu/ntsbarsh/simulation/sim.htm//introduction.Retriered on 7th

November.

RikMin. (2012) Advantages and Disadvantages of model-Driven Computer Simulation.

Retriered on November 17.2012 from http:// projects.edte-utwente.nl/pi/papers/sim

Adv.html

http://www.iseesystem.com/XMILE/index.php?-route=product

http://www.scientificsoftware-solution,com>simulation>visualization