page_title: Simulation
section_title: Classification and terminology
hierarchical_section_title: Simulation / Classification and terminology
caption_attribution_description: JSC2003-00011 (7 January 2003) --- Astronaut Christer Fuglesang, STS-116 mission specialist, wearing a training version of the Extravehicular Mobility Unit (EMU) spacesuit, participates in an underwater simulation of extravehicular activity (EVA) scheduled for the 19th shuttle mission to the International Space Station (ISS). Fuglesang was joined by astronaut Robert L. Curbeam, Jr. (out of frame), mission specialist, for the simulation, conducted in the Neutral Buoyancy Laboratory (NBL) near the Johnson Space Center. Fuglesang represents the European Space Agency (ESA).
context_page_description: A simulation is an approximate imitation of the operation of a process or system; that represents its operation over time.
  Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games. Often, computer experiments are used to study simulation models. Simulation is also used with scientific modelling of natural systems or human systems to gain insight into their functioning, as in economics. Simulation can be used to show the eventual real effects of alternative conditions and courses of action. Simulation is also used when the real system cannot be engaged, because it may not be accessible, or it may be dangerous or unacceptable to engage, or it is being designed but not yet built, or it may simply not exist.
  Key issues in simulation include the acquisition of valid sources of information about the relevant selection of key characteristics and behaviors, the use of simplifying approximations and assumptions within the simulation, and fidelity and validity of the simulation outcomes.
context_section_description: Historically, simulations used in different fields developed largely independently, but 20th-century studies of systems theory and cybernetics combined with spreading use of computers across all those fields have led to some unification and a more systematic view of the concept.
  Physical simulation refers to simulation in which physical objects are substituted for the real thing (some circles use the term for computer simulations modelling selected laws of physics, but this article does not). These physical objects are often chosen because they are smaller or cheaper than the actual object or system.
  Interactive simulation is a special kind of physical simulation, often referred to as a human in the loop simulation, in which physical simulations include human operators, such as in a flight simulator, sailing simulator, or driving simulator.
  Continuous simulation is a simulation based on continuous time, rather than discrete time steps, using numerical integration of differential equations.
  Discrete-event simulation studies systems whose states change their values only at discrete times.
  For example, a simulation of an epidemic could change the number of infected people at  time instants when susceptible individuals get infected or when infected individuals recover.
  Stochastic simulation is a simulation where some variable or process is subject to random variations and is projected using Monte Carlo techniques using pseudo-random numbers. Thus replicated runs with the same boundary conditions will each produce different results within a specific confidence band.
  Deterministic simulation is a simulation which is not stochastic: thus the variables are regulated by deterministic algorithms. So replicated runs from the same boundary conditions always produce identical results.
  Hybrid Simulation (sometime Combined Simulation) corresponds to a mix between Continuous and Discrete Event Simulation and results in integrating numerically the differential equations between two sequential events to reduce the number of discontinuities.
  A stand alone simulation is a simulation running on a single workstation by itself.
  A distributed simulation is one which uses more than one computer simultaneously, in order to guarantee access from/to different resources (e.g. multi-users operating different systems, or distributed data sets); a classical example is Distributed Interactive Simulation (DIS).
  Parallel Simulation speeds up a simulation's execution by concurrently distributing its workload over multiple processors, as in High-Performance Computing.
  Interoperable Simulation where multiple models, simulators (often defined as Federates) interoperate locally, distributed over a network; a classical example is High-Level Architecture.
  Modeling & Simulation as a Service where simulation is accessed as a service over the web.
  Modeling, interoperable Simulation and Serious Games where Serious Games Approaches (e.g. Game Engines and Engagement Methods) are integrated with Interoperable Simulation.
  Simulation Fidelity is used to describe the accuracy of a simulation and how closely it imitates the real-life counterpart. Fidelity is broadly classified as one of three categories: low, medium, and high. Specific descriptions of fidelity levels are subject to interpretation, but the following generalizations can be made:
  Low – the minimum simulation required for a system to respond to accept inputs and provide outputs
  Medium – responds automatically to stimuli, with limited accuracy
  High – nearly indistinguishable or as close as possible to the real system
  Human in the loop simulations can include a computer simulation as a so-called synthetic environment.
  Simulation in failure analysis refers to simulation in which we create environment/conditions to identify the cause of equipment failure. This was the best and fastest method to identify the failure cause.
caption: Human-in-the-loop simulation of outer space
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