In the past decades, training by means of simulated situations has experienced an enormous growth, mainly due to progress in enabling technologies such as computer systems, chemistry, etc. However, the basic aspects that define any good simulation still remain intact. As a designer of macros, scenery and software for flight simulators, as well as the Nanotyrannus Weapons System, I have noticed during these past years that in essence, for any simulation to be effective, you have to solve two problems:
1)- Reproducing situations which require practice, but with lesser costs and danger involved.
2)- Avoid the introduction of spurious factors into the simulation, which could likely come from the characteristics of the simulator or simulation process.
As you may imagine, to achieve these objectives it is no simple task, and it varies depending on what is the object of your simulation efforts. Nevertheless, there are common points to consider in all cases, such as the effects that each simulation has, which can be easily classified. The main four effects of any simulation are:
1)-To provide a framework in which to analyse human responses as well as the functioning of all kinds of equipment.
2)-To train humans to perform dangerous tasks, but in a safe and relatively inexpensive manner.
3)-To induce behavioural changes in humans as a result of that training process.
4)-To change the design of machines applied to real-life situations.
It is easy to see that all these are interdependent. Therefore, changes in equipment have influence on humans and vice-versa. Simulators as well as simulation processes are essentially simplifications of reality in order to provide a better classroom or test lab in which to work. Therefore, participants and instructors should bear in mind that some limitations exists and that they cannot expect absolute fidelity in the simulated scenarios. In other words, while you can certainly expect to be better prepared to confront a real emergency or danger after you have simulated it and analysed your mistakes, you cannot take for granted that you will react in the same way during the real event, and the key to any effective simulation is to minimise those differences to a minimum.
Moreover, simulators have their own peculiarities as well, and these characteristics - with no real-life counterparts - could induce behavioural changes as well. Such - mostly - undesirably training treats are known as side-effects or vices. Therefore simulation designers as well as instructors should keep a constant eye on the elements that could likely induce unrealistic behaviours in the participants of the different sessions run in their simulated environments. There are basically two ways to minimise the impact of these undesirable traits acquired thorough the use of simulators and simulated environments:
1)-To change the design of the simulator: in a flight simulator, the design of simulated joysticks provide a good example. A joystick applied to simulation is only good if it reproduces not only the response of the aircraft to its movements, but its weight, hydraulic or mechanical resistance, and other aspects as well.
2)- To change some rules of the simulation process: the perfect example of this is provided by the adaptation of paintball games, rules and equipment for real combat training. As is, paintball equipment provides a fairly good simulation of a real firefight, however, some key aspects of such a situation cannot be reproduced unless certain aspects of paintball competition are modified.
Diminishing the interference of such vices or undesirable traits is a very important part of the simulation process and it is directly related to the simulator's efficiency. In other words, fidelity in the reproduction of a given environment is translated into quality training. The main problem that simulator designers face is to reproduce faithfully any foreseeable situation regarding the piece of equipment or machinery that they intend to simulate. The best approach to provide good simulators is to design them along their real life counterparts, or to use as many common components as possible in order to grant the best possible reproduction. For example, a truck-driving simulation may be built up around a real truck cabin, using a genuine steering wheel, genuine seats, etc.
A combat flight simulator that uses a section of the fuselage and cockpit of the real aeroplane that is being simulated is invariably of more quality that the same piece of machinery provided with a simple box that pretends to act like a cockpit. Designers should bear in mind that simulators are here to trick the minds of the trainees and give them the illusion of being in a real situation, and as any pilot will tell you, every aircraft is different and feels different. They actually feel the aircraft, its response, noises and even the way the transparent bubble or windows around them look like, how they distort the view from the outside, etc.
Thus, if you pretend to simulate such an environment with something that, for starters, does not look like the real thing, then, deep in their minds, their pilots will "know" that they are in a simulator instead of a real cockpit. Some systems can be designed from the ground-up to be both simulators as well as real life applications. Such dual systems are not common due to the fact that it is not always possible to develop them, and because the importance given to simulation is fairly recent and not deeply ingrained in the minds of both engineers as well as users. In some cases, adaptations might prove to be relatively easy, such as in the case of the truck. In others, however, it could become much harder.
Another key ingredient for effective simulation is to design simulators as open systems. MS Flight Simulator is a perfect example of an open system that does not depend just on one source for maintenance, upgrading and repair works. Such systems, albeit costlier if only due to the required documentation for third-party research and development, have proved to be highly successful. Open systems hold a competitive advantage in this regard because by not being limited as to whom, when and how they are upgraded or modified, chances are that better ideas will come along sooner, and positive changes will be implemented more frequently. To work as such, open systems must be scalable as well as modular.
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Please review further information and references at Andinia.com. You can also get in touch with the author of this article, Don Pablo Edronkin directly to learn more and exchange views about these topics.
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