Modeling and simulation can either be a direct engineering product or a development tool used to design other complex systems. It provides a representation of the physical world for purposes such as operator training, development trade studies, component development, prototype testing, and test and evaluation where full-scale live testing is impractical, dangerous or cost-prohibitive.

How can the features of the real world be practically simulated to provide accurate insight into physical interactions and behaviors in order to design physical systems for specific purposes? What level of detail is required for accurate portrayal of the systems behavior?

The information upon which simulation and modeling depends includes math models for the interaction of simulated systems, plus specific
attributes of physical systems provided by analysis, physical testing, legacy designs, or systems identification.

Simulation conclusions include design decisions as well as training and educational practices.

Concepts span all domains of engineering, but also notably include concepts such as numerical methods, equations of motion, man-the-loop and hardware-in-the-loop testing, batch simulation, virtual reality, display latency, systems identification and computational throughput.

Simulation depends upon simplifying assumptions; real world detail remains beyond our reach. Simple simulations entail lengthy lists of assumptions. Improving simulation fidelity entails adding details to physical models that are assumed negligible in more simple models. Enhancing fidelity to the real physical world means removing assumptions, and consequently building complexity.

• When using modeling and simulation, engineers assume that they can design models that accurately represent the physical world to a sufficient level of detail.

• Simulation and modeling typically assumes that a relationship exists between cost and complexity, value and fidelity.

• Engineers assume that there are situations in which modeling and simulation provides vital insight (note that simulation may be employed throughout the product life, from conception to operation), while simultaneously recognizing that unmodeled phenomena may indeed be significant (limiting the simulations value).

Simulation can reduce the risk or expense of engineering development and testing, or provide insight into a system’s response to conditions which cannot practically or safely be tested in realistic conditions (e.g., failure states or emergency conditions). However, if a simulation product or process is flawed, negative implications might exist for the use of the actual product when used in the real world.

Simulation and modeling takes the point of view that the physical world submits to mathematical and computational modeling to such an extent that the behaviors observed in simulation reliably imitate or predict a system’s performance in the real world.