A System exists and operates in time and space. It is understood to be an entity which maintains its existence through the interaction of its parts.
A Model is a simplified representation of the system at some particular point in time or space intended to promote understanding of the real system.
A Simulation is the manipulation of a model in such a way that it operates on time or space to compress it, thus enabling one to perceive the interactions that would not otherwise be apparent because of their separation in time or space.
Modeling and Simulation is a discipline for developing a level of understanding of the interaction of the parts of a system, and of the system as a whole. Since all models are simplifications of reality there is always a trade-off as to what level of detail is included in the model. If too abstract, the model runs the risk of missing relevant interactions and the resultant model does not promote understanding. If too much detailed are included in the model, it may become overly complicated and actually preclude the development of understanding.
After one or many simulations of the model, analysis takes place to draw conclusions, verify and validate the research, and make recommendations
based on various simulations of the model. As a way of representing data, visualization serves to interface with the model.
The actual matter is HOW TO DEVELOP A SIMULATION MODEL? An interesting dissertation can be found in this paper, written by the the State University of New York at Binghamton, where the model creation, validation and simulation is broken into the following steps:
– Step 1. Identify the problem.
– Step 2. Formulate the problem.
– Step 3. Collect and process real system data.
– Step 4. Formulate and develop a model
– Step 5. Validate the model
– Step 7. Select appropriate experimental design
– Step 8. Establish experimental conditions for runs
– Step 9. Perform simulation runs.
– Step 10. Interpret and present results.
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