A simulation model is a representation of reality that is made in order to demonstrate something that can’t readily be seen or that hasn’t happened yet. The main idea is to make visible that with isn’t immediately apparent to the naked eye. Some of the simplest models are static, which means that they don’t move or change in response to stimulation or external events. Many of the most advanced examples are specifically intended to shift with certain variables, though, often as a way of predicting future events before they happen or to get a sense of possible outcomes. Models of things like weather patterns or business volume flows are good examples, and computer imaging is often really helpful in these cases. No matter what the end product looks like, the goal of any project in this realm is usually the same: namely, to bring life and vibrancy to things that are otherwise hard to conceptualize, and to allow people to plan around and understand them differently as a result.
There are typically three core elements to any simulation model. First is an identification of the basic parts of the system. Then, the modeler needs to understand the interaction between those parts. Finally the number and nature of inputs must be tabulated. A model is essentially created for each of these, with crucial aspects considered and minor aspects ignored. The model for the whole system is developed once all of these pieces start working together.
Modelers can approach the task from a couple of different angles, and there is no single form that all end products necessarily take. The overarching idea is to take something from reality — a molecule, a virus mutation lifecycle, a business distribution plan — and condense it into a format that is visual, approachable, and easily understood. Graphics are a common part of many models, as are colors. Models that move often have animation or mechanical moving parts, while those that are still may have drawn arrows or other indications of slow change.
Why It’s Useful
This sort of modeling has been done in some form or another for centuries. It’s most common today in the math and science sectors, though it can be used for almost anything. A good simulated model can save researchers a lot of time and energy by allowing them to study and take core measurements off of the model rather than out of reality. In many cases it also enables predictions about future events that can influence things like weather forecasting and logistical decision-making for big businesses.
Static and Dynamic Examples
A model can be physical or abstract, and both types can be static or dynamic — that is, something that stays the same or changes with time. An example of a static physical model is a stick model of a water molecule, with two small hydrogen “balls” representing the hydrogen atoms stuck with short sticks on either side of one oxygen "ball," creating a visual interpretation of H2O. Water molecules can be viewed under powerful microscopes, but simulated tabletop models can be more immediately useful when trying to explain the core properties.
Another physical model is that of a tank of water with sand, which shows the effect of the wind and the movement of water. In this dynamic model, the sand and water show patterns that depend on the intensity and direction of the wind with time. Most models incorporate some element of dynamism.
For example, for a simulation of a factory workflow, one machine can be modeled as an element that takes a certain amount of time to create a particular part, while another machine takes a different amount of time. The time to move parts between machines may be ignored for machines that are close together, but the number, the rate, and the time at which the raw material and the work orders come into the factory are usually modeled. Based on all these, the simulation determines whether the output of the factory meets the demand.
Role of Computer Programming
Traditionally, simulation modeling has been mathematical in nature. Raw material coming into a factory, for example, would be approximated as coming in at fixed intervals. Computers can now do more realistic simulations by using scripts and codes similar to a real situation or even an exact recording of a real situation.
Some simulations can be run with standard simulation programs, and others require special software to be written. The models for the parts, the interaction of the parts, and the inputs are fed to a program that then runs the simulation model and delivers the outputs over time, often showing those outputs graphically. With computers, simulations involving thousands or even millions of elements and spanning large time intervals can be attempted. Models of planetary evolution or advanced military maneuvers are two examples.