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Why do we build Models and Simulations?
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The original purpose for building models was to help us understand things we observe. For example, when Newton tried to understand gravity, he turned to a mathematical representation that has been the backbone of Newtonian Physics. For those who are interested, Newton's model which represented the relationship among velocity (v), acceleration (a) and time (t) is: vt = v0 + ½ at2 (This equation is a mathematical model). In the most general sense there are two reasons to build a model or simulation: 1) to understand how processes and/or entities work and 2) to stimulate (not simulate) human behavior. Each of these in turn supports specific activities; see figure 1.
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Decision Support - Models and simulations allow analysts to represent processes and large systems (i.e. entities) that are too complex to understand with just a static view. Analysts run the models and simulations by varying many different parameters to see how the process or system operations change as these parameters change. The results are analyzed, synopsized, and then provided to decision makers as insights that help them make decisions about potential changes to the processes and/or entities. There are two types of models that are used for decision support: 1) prescriptive models and 2) descriptive models. Prescriptive models provide a "best" solution, while descriptive models provide statistics on how processes and systems actually operate. In both cases the accuracy of the results is limited by the assumptions made in the representation and the accuracy of the data used by the models. (Prescriptive and Descriptive models are discussed in detail in a later Fact Sheet)
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Design - Models and simulations allow engineers to represent critical design parameters in systems to determine the best combination of these critical parameters. For example, an aeronautical engineer can represent different lift and drag factors for the wings and fuselage in a mathematical model of a new airplane to determine how they affect maneuverability. When systems involve human behavior, simulations can be used to stimulate people involved in operating a system to establish both performance related system parameters and human interface factors that are critical to system design. There are some similarities in this use with the decision support use; engineers use models to help make design decisions. This utilization of models and simulations is, in a way, a very specific type of decision support; the people running the models or simulations are using them to make design decisions, not summarizing results and passing them onto senior decision makers.
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Process Improvement - Similar to the Design activity, process improvement involves decision support. In this specific activity, process analysts can modify critical factors in a process model that impact business and/or system processes that are too complex to understand a "piece at a time." (For example, time to complete activities, resources needed to complete activities, frequency of interruptions, etc.) Models and simulations identify "bottlenecks," resource constraints, inefficiencies, critical dependencies, and many other key process characteristics. This use illustrates how important it is to make sure a model has a representation of all the processes and entities that are appropriate for the intended use. If, for example, someone wanted to study the impact of operator interruptions on the output of an assembly line, a simulation of the assembly line must represent the interruptions and there must be input data on the frequency and duration of the interruptions. If the simulation developers were not interested in this issue when they built the simulation and thought it was too much trouble to add this detail, then the simulation needs to be modified and new data collected. In this case the way to represent operator interruptions is well understood and getting real data would not be a problem. It may have been left out because there was no original requirement related to studying operator interruptions and the cost to include it was not warranted. In many models and simulations some key factors are left out (i.e. not modeled) because no one understands how to represent them.
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Research - Scientists are constantly trying to better understand natural process and phenomena. Many research projects include attempts to develop better representations (i.e. models) of processes and phenomena to better understand how to influence or take advantage of them. For example, biologists, based on their best understanding of the process, can represent in a model how a virus multiplies. They can modify key parameters in the model and see which parameters best match data collected in live experiments. This allows them to improve and validate their models and then use the models to identify potential interventions. Simulations are also used to research human behavior because they can easily provide logical, consistent stimuli to people involved in complex operations. Without the simulation the stimuli would be too artificial and the delivery of the stimuli would impact the validity of the human response.
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Education - Models and simulations provide artificial, yet realistic, situations and environments that can be used to instigate new ways of thinking or to reinforce theories and concepts. Teachers can be freed of the role playing needed to make educational exercises effective; models and simulations can accept input from students and provide realistic feedback that is critical in this type of pedagogical setting. Military schools make wide use of simulations to educate future leaders. Economists also use models and simulations to help students understand the complex interactions among factors that can influence economies.
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Training - There are similarities in the way models and simulations are used for education and the way they are used for training. In the latter use, the emphasis is on teaching standard procedures, training people to instinctively and predictably react in certain situations. The use of simulations in education teaches concepts and ideas that lead to independent thinking and activities. Simulations used in training can have sophisticated, realistic representations of the physical environment as part of the user interface to stimulate the human senses, (e.g. visual representation of oncoming automobiles in a driver training game). They can also be as simple as a text message screen which allows the trainee to provide input to and view output from a model or simulation. Simulations for training receive the greatest publicity because they usually have the most sophisticated graphics. Realism in the training environment is very important and good visual aids make this possible. However, good graphics do not make a training simulation good; if the underlying representations of the real world processes that are being simulated are not valid, the simulation can actually cause negative learning.
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