Tugasan3 simulasi ssi 3013

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Tugasan3 simulasi ssi 3013

  1. 1. 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
  2. 2. 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.
  3. 3. 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..
  4. 4. 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..
  5. 5. 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..
  6. 6. 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..
  7. 7. 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..
  8. 8. 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..
  9. 9. 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 values.
  10. 10. 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.
  11. 11. 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.
  12. 12. 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)
  13. 13. 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.
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  15. 15. 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.
  16. 16. 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

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