To characterize simulation, it is useful to compare it with other fields such as computer graphics/animation and virtual reality (VR), since these fields have much in common with simulation. Computer graphics is the computational study of light and its effect on geometric objects --- the focus on graphics is to produce meaningful rendered images of real world or hypothetical objects. Animation is the use of computer graphics to generate a sequence of frames which, when passed before your eyes very quickly, produce the illusion of continuous motion. VR is primarily focused on immersive human-computer interaction as found in devices such as head-mounted displays (HMDs), position sensors and data gloves. Think of simulation as the ``engine" which drives the graphics and VR technologies. That is, by doing simulation (creating a model, executing the model, and analyzing the output), you build the infrastructure necessary for other fields. The ultimate test of a computer anmation is that ``it looks good" to the viewer. Most computer simulationists, however, regard this as only one component of validation (called face validation). As long as you are not doing engineering or science, creating a geometric model that looks good, as it undergoes motion, is satisfactory. However, if you are trying to validate a mathematical model with real world data (often of a non-visual nature), we must be concerned with more than mere ``looks." Most VR researchers are concerned with the human-machine interaction and not with the mathematical models which actually create the artificial reality. For such models, we require computer graphics (for representing the geometry) and computer simulation (for representing the dynamics).
Working closely with people of other technical disciplines is one
of the things that makes simulation fascinating. If you take a
moment to talk with faculty and students in different departments
spread throughout a typical university's colleges, you will
find simulation being used everywhere. The person in a specific
department is usually interested in simulation to satisfy a
class of problem. For instance, someone doing work in Ecology
and Wetlands Restoration will be doing simulation for hydrology
and population growth and decay for wildlife species in a
given geographic region. Someone in Astronomy will want to simulate
the collision of galaxies and the formation of dark matter.
Simulation provides these workers with a tool to let them
explore their worlds without having to run extensive physical,
on site, experiments which tend to be expensive both in
time and money
. As a simulationist, your responsibility is
to understand the common vocabulary of systems, modeling
terminology and algorithmic procedures which form the
simulation foundation. You will often find yourself
seeing relationships between someone's problem, for instance,
in astrophysics and someone else's problem in molecular
dynamics. It is this synergy which creates a great
deal of satisfaction for the simulation discipline.