System Modeling and Simulation: An Introduction
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Simulation and modeling applications range from nuclear reactions to transport systems. Hence, there are two types of simulation approaches: discrete simulation approaches and continuous simulation approaches.
Process interaction approach, event scheduling approach, activity scanning approach, stock and flow approach, and three-phase approach all belong to the first family. In process interaction approach, the computer program emulates the flow of an object through the system. Transaction flow approach is a simpler version of process interaction approach.
Event scheduling approach advances time to the moment when something happens next. The third approach, activity scanning approach, is based on two phases: the first phase is the execution after a fixed amount of time, and the second phase is the execution after the satisfaction of some condition. The third approach is a three-phase approach; as the name is suggesting, it has three phases: A, B, and C.
Cyber-Physical Systems: Modeling and Simulation
To better understand the simulation approaches, Figure 1 reflects the flow charts of each of them. To handle concurrent discrete event dynamic systems, Petri nets were developed by Carl Adam in the beginning of the s, a theory for discrete parallel system. Simulation and modeling needs imagination and innovations to be developed from scratch. Simulation allows time control where the user can compress and expand time element.
Simulation allows the user to explore different possibilities while identifying constrains and predict obstacles. Playing with what-if scenarios, simulation is used to train pilots as well as medical professionals in the case of new technology.
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Simulation is used to train people in a number of arenas for many reasons: either the training situation is too dangerous to conduct or too delicate or too expensive. A study by Abu-Taieh and Abutayeh [ 2 ], they listed 12 areas where simulation is used for vocational training: to train pilots, many simulators are used. Rather than using the real plane to teach the pilot to fly, a simulator is used to train the pilot. Another use is to conduct chemical experiments by simulating the experiments. As such, the experimenter is in a safe environment while knowledge is transferred on handling chemical materials.
Another training arena is physics experiments. Simulators are used to conduct physics experiments. To teach things like motion, energy, power, sound, heat, electricity, magnets, circuits, light, and radiation, a simulator is used to teach their attributes and to visualize the experiments as seen in [ 3 ].
Mathematics, algebra, number theory, mathematical functions, trigonometry, data analysis, graphs, trees, networks, enumerative combinations, iteration, and recursion are hard topics to understand and visualize. Simulation is used as an explanatory tool and a visualizing method. Nelson [ 4 ] listed five reasons to use simulation in mathematics. Simulation is used to study environmental and ecological systems.
Theory of Modeling and Simulation - 2nd Edition
Since such arena is overwhelmed with variables that no mathematical formula can solve, simulation is used to study, visualize, understand, and explain environmental phenomena. To study, understand, and explain cosmology and astrophysics, many computer-based simulators are used. Simulation in this case enhances the understanding of cosmology and astrophysics by visualization. Simulators are also used to train medical students in surgery training. Such concept is used to train novice surgeons to gain expertise and self-confidence before conducting the real surgery.
Simulators are also used in civil engineering, interior design, and architectural engineering designs. Since real-life experimentation is lengthy and expensive, simulators in such arena save time, money, and effort by delivering virtual product which can be altered rather than delivering real-life product. Other uses of simulation are to design, understand, test, and visualize computers and communication networks as seen in [ 6 , 7 ]. To learn financial planning and to model marketing simulation is used, namely, in Crystal Ball and Analytica, among others.
Simulators like mission rehearsal exercise MRE. This section is an answer to the second distinguishing feature of simulation. There is no point in simulating the wrong model and no point in simulating the model incorrectly. Credibility can be claimed only for the prescribed conditions for which the model or simulation is verified, validated, and accredited. Successfully testing each submodel module does not imply overall model credibility.
Simulation model validity does not guarantee the credibility and acceptability of simulation results. The dynamic subcategory included 50 techniques.
The formal subcategory included eight techniques. The adaptive subcategory included 15 techniques, while the specific subcategory included 31 techniques. In total, Balci listed more than validation and verification techniques; as such, this only reflects the importance of validation and verification in simulation.
File Extensions and File Formats
Some published work like [ 8 , 9 , 11 , 12 ] discussed the validation and verification quest. Playing the virtual world with time element is a joy and challenge. Hence, simulation to simulators is an open-ended question. This chapter showed the importance of simulation from academic and scientific point of view and then the distinguishing elements of simulation. Two distinguishing features stood out: time element and the correctness of the simulation program. Time element handling is reflected in Section 4. Correctness of the simulation program is discussed in Section 7.
In the overall picture, simulation and modeling is like an addictive game that one can never get tired of. Auhood Alfaries and the University of Jordan for their moral support and encouragement.
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Also, I would to acknowledge the Publisher intechopen. Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.
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NO YES. System Modeling and Simulation: An Introduction. Selected type: E-Book. Added to Your Shopping Cart. This is a dummy description. This text teaches, by example, how to create models, simulate performance simulations and analyse results. It takes a quantitative approach and covers a range of event driven and time driven models. In addition it is software independent - to make implementations as generic as possible, which allows for experimentation with different implementations.
In addition to being an unrepentant teacher, he plays viola in the University Symphony Orchestra and directs muscials for the Charlotte Community Theater.