AN point in time that is intended to

AN INTRODUCTIONModelling and Simulation (M&S) as a whole is a discipline, but before exploring what that means, we will break it down and explain each term to get a deeper understanding of this discipline. First, we look at modelling; it comes from the word model. The latter is a simplified representation of a system at a certain point in time that is intended to promote understanding of the real system. Now this “system” can be explained as something that exists and operates in time and space.Secondly, we look at simulation.

It is usually used to manipulate the model defined above in such a way that it operates on time or space to compress it which allows one to see the interactions that would otherwise not be visible because of their separation in time or space. Now with knowledge of the explained terms, we can now deduce a better explanation of what Modelling and Simulation is. As a discipline, M&S can be seen as a tool for developing some level of understanding of how the parts of a system interact and of the system as a whole. This kind of understanding is hard to get from any other field other than Modelling and Simulation.Now, how did M&S come about? This is better answerable by exploring the history of simulation.HISTORY AND BACKGROUNDThe history of simulation can be traced back as far as 1940, through a method called Monte Carlo, which was developed by Jonn von Neumann, Stanislaw Ulan, Hermann Kahn and some physicists who worked on the Manhattan project to study neutron scattering. This was a huge mark for simulation as it was during the mid-1940 that the construction of the first general – purpose electronics computers such as ENIAC was done. With this and the Monte Carlo method, some ground breaking realisation was made.

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By 1960, special – purpose simulation languages were developed. One example is SIMSCRIPT which was developed by Harry Markowitz at RAND Corporation. With this kind of development, in the 1970’s, these language were used in research on mathematical foundations of simulation. This then developed into PC- based simulation software which led to development of graphical user interface and object – oriented programming in the 1980’s.

By the 1990’s, things got more “fancy” and sophisticated. Web – based simulation, animated graphics, and simulation – based optimization, Markov – chain Monte Carlo methods were developed.With all these developments throughout the years, it was possible to model systems and actually see how the systems will work before doing final production.IMPORTANCE OF M mentioned above, M has marked itself as very crucial in understanding systems and models prior production or implementation without working on real – time systems. Furthermore, testing is fairly easy.

One can make changes into the system and their effect on the output and it is easy to upgrade, that is, M allows one to determine the system requirements by applying different configurations. In identifying constraints, Modelling and Simulation comes in handy as corrections can be made before real –time analysis. In practice, certain systems are so complex that it is not easy to understand their interaction at a time. However, M allows the understanding of these interactions and analyse their effect. In addition, new policies, operations and procedures can be explored without affecting the real system.

An example of why M is important traffic congestion. For a transportation engineer, it may be difficult to evaluate complex traffic situations that cannot be analysed directly with other means. As thus, traffic models play vital role in allowing easy analysis.Another vitality of M is in a business management curriculum. Business decision are mostly made in uncertain dynamic environment where input variables keep changing. As thus, it is very risky for businesses to go straight into real – time system analysis as they might waste money and time on systems that have many constraints.

It is thus, much more efficient to use M, and in this case, spreadsheets can be used when dealing with businesses for modelling and simulating future risks, trends and financial analysis of a business.APPLICATIONS OF M are many possible applications of Modelling and Simulation. These include military applications, robotics and automation, designing semiconductors, telecommunications, civil engineering designs and presentations and E – business designs. It can also be used to study the internal structure of a complex system such as a biological system.i. Military applicationsIn the military, different kinds of weapons and ammunition are used, which may be dangerous to operate. As thus, it is imperative that these are tested and any constraints found and corrected before they could be used in real –time.

M comes in handy as models of these equipment can be tested and analysed before being used. For example, missiles require great precision and accuracy, now if there was some error in calculation and the missile is put to use in real – time, it may cause a lot of damage and deaths. But if it is modelled and simulated in a computer to see how it works first, this error could be found and dealt with.ii. Robotics and AutomationIn robotics and automation, a lot of mathematical models are needed in order to understand the dynamics of the system, hence M is very important.

Robots or humanoids cannot just be built from scratch without first simulating in the virtual world how exactly they will perform. Software such as ROS, Gazebo and Solid Works help in modelling and simulating robotic system before they can be built. There is no way these systems can be made without M as the work is tedious and complex, especially with the mathematics and physics behind these systems.iii. Biological SystemsBiological systems are very complex but vital in understanding how the human body works.

For example, in surgery, doctors need to know how the human body works before they can perform the surgery. As thus, models are needed in medical schools were these doctors can learn the anatomy of a human before practicing. 


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