Modeling: a model definition
A computer model, as used in modeling and simulation science, is a mathematical representation of something—a person, a building, a vehicle, a tree—any object. A model also can be a representation of a process—a weather pattern, traffic flow, air flowing over a wing.
Models are created from a mass of data, equations and computations that mimic the actions of things represented. Models usually include a graphical display that translates all this number crunching into an animation that you can see on a computer screen or by means of some other visual device.
Models can be simple images of things—the outer shell, so to speak—or they can be complex, carrying all the characteristics of the object or process they represent. A complex model will simulate the actions and reactions of the real thing. To make these models behave the way they would in real life, accurate, real-time simulations require fast computers with lots of number crunching power.
In its broadest sense, simulation is imitation. We've used it for thousands of years to train, explain and entertain. Thanks to the computer age, we're really getting good at using simulation for all three.
Simulations (and models, too) are abstractions of reality. Often they deliberately emphasize one part of reality at the expense of other parts. Sometimes this is necessary due to computer power limitations. Sometimes it's done to focus your attention on an important aspect of the simulation. Whereas models are mathematical, logical, or some other structured representation of reality, simulations are the specific application of models to arrive at some outcome.
Three types of simulations
Simulations generally come in three styles: live, virtual and constructive. A simulation also may be a combination of two or more styles. Within these styles, simulations can be science-based (where, for example, interactions of things are observed or measured), or involve interactions with humans. Our primary focus at IST is on the latter — human-in-the-loop — simulations.
Live simulations typically involve humans and/or equipment and activity in a setting where they would operate for real. Think war games with soldiers out in the field or manning command posts. Time is continuous, as in the real world. Another example of live simulation is testing a car battery using an electrical tester.
Virtual simulations typically involve humans and/or equipment in a computer-controlled setting. Time is in discrete steps, allowing users to concentrate on the important stuff, so to speak. A flight simulator falls into this category.
Constructive simulations typically do not involve humans or equipment as participants. Rather than by time, they are driven more by the proper sequencing of events. The anticipated path of a hurricane might be "constructed" through application of temperatures, pressures, wind currents and other weather factors. Science-based simulations are typically constructive in nature.
A simulator is a device that may use any combination of sound, sight, motion and smell to make you feel that you are experiencing an actual situation. Some video games are good examples of low-end simulators. For example, you have probably seen or played race car arcade games.
The booths containing these games have a steering wheel, stick shift, gas and brake pedals and a display monitor. You use these devices to "drive" your "race car" along the track and through changing scenery displayed on the monitor. As you drive, you hear the engine rumble, the brakes squeal and the metal crunch if you crash. Some booths use movement to create sensations of acceleration, deceleration and turning. The sights, sounds and feel of the game booth combine to create, or simulate, the experience of driving a car in a race.
Most people first think of "flight simulators" or "driving simulators" when they hear the term "simulation." But simulation is much more.
Because they can recreate experiences, simulations hold great potential for training people for almost any situation. Education researchers have, in fact, determined that people, especially adults, learn better by experience than through reading or lectures. Simulated experiences can be just as valuable a training tool as the real thing.
Simulations are complex, computer-driven re-creations of the real thing. When used for training, they must recreate "reality" accurately, otherwise you may not learn the right way to do a task.
For example, if you try to practice how to fly in a flight simulator game that does not accurately model the flight characteristics of an airplane, you will not learn how a real aircraft responds to your control.
Building simulator games is not easy, but creating simulations that accurately answer such questions as "If I do this, what happens then?" is even more demanding.
Over the years, government and industry, working independently with new technologies and hardware, developed a wide range of products and related applications to improve simulation science. This independence, however, often led to sporadic or redundant research efforts.
To benefit from each other's latest advances, researchers from across the country needed better communication and, ideally, a common source of supporting academic studies. The State of Florida recognized these needs and in 1982 established the Institute for Simulation and Training at the University of Central Florida.
What we do at IST
IST's mission is to advance the state of the art and science of human-centered modeling and simulation by:
- Performing basic and applied simulation research
- Supporting education in modeling and simulation and related fields
- Serving public and private simulation communities
We don't produce simulator hardware. That's a job for industry. But we've successfully developed working prototype hardware that provides new uses for simulations. We'll also help develop new applications for existing hardware, and scientifically test the results using human factors and other criteria for effective human-machine interface and learning. Too often overlooked, human factors testing is crucial to ultimate simulation effectiveness. We're fortunate to be closely connected through joint faculty appointments and working relationships with one of the top, if not the leading, human factors departments in the nation—right here at UCF.
We also explore the frontiers of simulation science, expanding our knowledge of ways to stimulate the human senses with advanced optical, audio and haptic technologies.
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