FAKULTI SAINS DAN MATEMATIK
UNIVERSITI PENDIDIKAN SULTAN IDRIS
MODELING AND SIMULATION
SEM 1 SESI 2013/2014
IMFORMATION AND COMMUNICATION TEKNOLOGY
RAHMAH BT SOID
UPSI01 ( A131PJJ)
DR. AZMI BIN IBRAHIM
PM-3, Level 2, Block 01,
Proton City Campus
ASSIGNMENT 3 - SSI 3013
MODELING AND SIMULATION
A representation of an object, a system or an idea in some form other than of the
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 .
Designning and analyzing manufacturing system.
Evaluating a new military weapons system or tactics
Determining ordering policies for an inventory system.
Designing communications systems and message protocols for them.
Designing and operating transportation facilities such as freeways, airports
subways or ports.
Evaluating designs for servicesorganizations such as hospital, post office or
fast food restaurants.
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.
Using instructional simulations gives students concrete formats of what it
means to think like a scientist and do scientific work.
Simulation allows students to change parameter values and see what happen.
a feel for students develop what variables are important and the significance of
magnitude changes in parameters.
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
2. Animal Temperature
Explore the laws of thermodynamics with this animal temperature model. As you
3. Balloon Problem
This model illustrates how a simple interface can facilitate experimentation with a
4. Distance and Time
Experiment with different velocities and find out how they impact the solution to this typical
5. Extraverts and Introverts
This map (not a running simulation model) uses STELLA's storytelling feature to explore the
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
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
11. Non-Seperable Differential Equations
Analytically daunting or deceptively simple? The model represents a classic problem—that
12. One- dimensional diffusion
Simulates the diffusion of heat through a one meter metal bar when the ends are held at a
13. Overturned Truck
You’re driving on the highway and around the curve is an overturned truck. Can you stop in
14. Pendulum Story
Consider what happens when you connect a small ball (or bob) to the end of a string. When
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,
17.Predator Prey Dynamics
As the manager of a small but thriving natural wilderness area, would you allow a one-time
18. President & Prime Minister
Whose coffee cools faster? This question quickly becomes relevant for the president and the
Storytelling is used to present the basic structure of a reversible chemical reaction.
20. Sustainable Shrimping
This Learning Environment should help you understand some basic population dynamics and
21. Temperature Control
Conduct experiments and try to maintain a constant temperature in a house that uses a climate
22. Virtual Bungee
Virtual bungee jumpers can experiment with different body weights and bungee cord
23. Virtual Hamlet
Use this virtual laboratory to explore the plot and character development in one of
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 nonphysical 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
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
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 “
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
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
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.
Temp of house is 70.6
Or we can adjust to another reading of parameter.
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
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.
Maria A. (2002). Introduction to modelling and simulation. Retriered December 1st 2012
Weimer M. (2010). Simulation Deliver Real Benefits. Retriered December 1st 2012 from
http://home.ubalt.edu/ntsbarsh/simulation/sim.htm//introduction.Retriered on 7th
RikMin. (2012) Advantages and Disadvantages of model-Driven Computer Simulation.
Retriered on November 17.2012 from http:// projects.edte-utwente.nl/pi/papers/sim