What Is Computer Simulation?

Computer simulation is the use of computational models to imitate the behavior of real-world systems or processes over time, allowing analysts to study dynamics, test hypotheses, or evaluate designs that would be impractical or impossible to examine directly. A simulation encodes the relationships among system components as mathematical or logical rules, then executes those rules iteratively to produce a trajectory of system states. The output can represent physical phenomena, such as fluid flow or electromagnetic transients, or abstract processes, such as queuing networks or financial markets.

The discipline draws on applied mathematics, computer science, and domain-specific engineering or science. Model validity, the degree to which a simulation faithfully represents the system of interest, is a central concern. Validation involves comparing simulation outputs to measured data from the actual system, while verification confirms that the model has been implemented correctly in software. Both steps are required before simulation results can be used to support engineering decisions or scientific conclusions, and standards bodies including the American Institute of Aeronautics and Astronautics have published guidelines for verification and validation in computational modeling.

Simulation Methods and Fidelity

Several major computational paradigms underlie practical simulation systems. Discrete-event simulation advances system state only at the moments when events occur, making it efficient for modeling queuing systems, logistics networks, and telecommunications infrastructure. Continuous simulation integrates differential equations over time and is the foundation for physics-based models in structural analysis, thermodynamics, and circuit design. Monte Carlo methods apply repeated random sampling to systems governed by probabilistic rules, producing statistical distributions of outcomes rather than single deterministic trajectories; the INFORMS simulation community provides educational resources and practice standards across these methods. The IEEE Transactions on Simulation publishes research on new algorithms for numerical integration, parallel simulation, and real-time execution.

Human-in-the-Loop Simulation

Human-in-the-loop (HITL) simulation incorporates a human operator as an active participant in the simulation environment rather than treating the system as fully automated. Flight simulators, surgical training systems, and military command-post exercises are all HITL applications in which the validity of the simulation depends on correctly modeling the interface between the human and the simulated environment. HITL designs are used to evaluate human performance under conditions that would be dangerous or expensive to replicate in reality, as well as to train operators on procedures for complex systems. The fidelity requirements for HITL simulations are typically higher than for automated analysis, because human responses are sensitive to latency, visual realism, and motion cueing that matter less when no operator is present.

Electromagnetic Transients and Power Systems Simulation

The Electromagnetic Transients Program (EMTP) and its successors represent a specialized class of computer simulation developed for power engineering. EMTP, originally developed at Bonneville Power Administration in the 1960s and 1970s, models the time-domain behavior of electrical networks including transmission lines, transformers, and switching devices during transient events such as lightning strikes, fault conditions, and switching surges. Power system simulation using EMTP-type tools informs the design of protective relaying, surge arresters, and insulation coordination. Modern derivatives of the original program operate in real time on dedicated hardware platforms and are used in power hardware-in-the-loop testing, where physical equipment is connected to a simulated network.

Applications

Computer simulation has applications in a wide range of fields, including:

• Aerospace engineering, modeling aerodynamics, structural loads, and flight dynamics during vehicle design
• Healthcare and medicine, simulating physiological systems for drug development and surgical training
• Power systems engineering, analyzing electrical transients and grid stability under fault conditions
• Military and emergency management, training operators and planners on large-scale scenarios
• Climate and environmental science, modeling atmospheric circulation, ocean dynamics, and ecosystem responses