Simulation software is software that models a real phenomenon with a set of mathematical formulas. It allows a user to see the results of an action without actually performing that action. Simulation software is widely used to design equipment such that the final product will be as close to design specs as possible. Simulation software that runs real-time is used often in gaming, but also has important industrial applications. When the penalty for improper operation is costly, such as when piloting an airplane or operating a nuclear power plant, a mock up of the actual control panel is connected to a real-time simulation of the physical response, allowing valuable training without consequences. Advanced computer programs can simulate power system behavior, weather conditions, electronic circuits, chemical reactions, mechatronics, heat pumps, feedback control systems, atomic reactions, light, and even complex biological processes. In theory, any phenomena that can be reduced to mathematical data and equations can be simulated on a computer. Simulation can be difficult because most natural phenomena are subject to an almost infinite number of influences or unknown source of causes. Part of developing useful simulations is determing what the most important factors are that affect the simulation. In addition to imitating processes to see how they behave under different conditions, simulations are also used to test new theories. After creating a theory of causal relationships, the theorist can codify the relationships in the form of a computer program. If the program then behaves in the same way as the real process, it's likely that the proposed relationships are correct.
General simulation General simulation packages fall into two categories: discrete event and continuous simulation. Discrete event simulations are used to model statistical events such as customers arriving in queues at a bank. By properly correlating arrival probabilities with observed behavior, a model can determine optimal queue count to keep queue wait times at a specified level. Continuous simulators are used to model a wide variety of physical phenomena like ballistic trajectories, human respiration, electric motor response, radio frequency data communication, steam turbine power generation etc. Simulations are used in initial system design to optimize component selection and controller gains, as well as in Model Based Design systems to generate embedded control code. Real-time operation of continuous simulation is used for operator training and off-line controller tuning. There are four main renowned simulation approaches: Event-Scheduling method, Activity Scanning, Process- Interaction, and Three-Phase approach, in comparison, the following can be noted: The Event-Scheduling method is simpler and only has two phases so there is no Cs and Bs, this allow the program to run faster since there are no scanning for the conditional events. All these advantages also tells us something about the disadvantages of the method since there are only two phase then all events are mixed (no Bs and Cs) then the method is not parsimony, which means it is very hard to enhance (Pidd, 1998). The Activity Scanning approach is also simpler than the Three-Phase method since it has no calendar, and it support the parsimonious modeling. However this approach is much slower than Three-Phase since it treats all activities are treated as conditional. On the other hand, the executive has two phases. Usually this approach is confused with the Three-Phase method (Pidd, 1998). The Process- Interaction “share two common advantages first; they avoid programs that are slow to run. Second, they avoid the need to think through all possible logical consequences of an event” (Pidd, 1998). Yet, as (Pidd, 1998) claims this approach suffers from DEADLOCK problem, but this approach is very attractive for novice modelers. Although, (Schriber et al, 2003). Says “process interaction was understood only by an elite group of individuals and was beyond the reach of ordinary programmers”. In fact (Schriber et al, 2003).adds “. Multi- threaded applications were talked about in computer science classes, but rarely used in the broader community”. Which indicates that the implementation of Process-Interaction was very difficult to implement. The obvious contradiction, in the previous quote is due to the mix up between the Process Interaction approach and the Transaction-flow approach. To see the complete idea of the origins of Transaction-Flow best stated by (Schriber et al, 2003): This was the primordial soup out of which the Gordon Simulator arose. Gordon’s transaction flow world-view was a cleverly disguised form of process interaction that put the process interaction approach within the grasp of ordinary users. . Gordon did one of the great packaging jobs of all time. He devised a set of building blocks that could be put together to build a flowchart that graphically depicted the operation of a system. Under this modeling paradigm, the flow of elements through a system was readily visible, because that was the focus of the whole approach. The Three-Phase approach allows to “simulate parallelism, whilst avoiding deadlock” (Pidd and Cassel, 1998). Yet, Three-Phase has to scan through the schedule for bound activities, and then scans through all conditional activities which slow it down. Yet many forgo the time spent in return for solving the deadlock problem. In fact, Three-Phase is used in distributed systems whether talking about operating systems, databases, etc, under different names among them Three-Phase commit see (Tanenbaum and Steen, 2002).
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