Editing Simulation (section)

== Power systems ==
{{main|Power system simulation}}

===Project management===
{{main|Project management simulation}}
{{Unreferenced section|date=September 2021}}
Project management simulation is simulation used for project management training and analysis. It is often used as a training simulation for project managers. In other cases, it is used for what-if analysis and for supporting decision-making in real projects. Frequently the simulation is conducted using software tools.

===Robotics===
{{main|Robotics simulator}}
{{Unreferenced section|date=September 2021}}
A robotics simulator is used to create embedded applications for a specific (or not) robot without being dependent on the 'real' robot. In some cases, these applications can be transferred to the real robot (or rebuilt) without modifications. Robotics simulators allow reproducing situations that cannot be 'created' in the real world because of cost, time, or the 'uniqueness' of a resource. A simulator also allows fast robot prototyping. Many robot simulators feature [[physics engine]]s to simulate a robot's dynamics.

===Production===
'''Simulation of production systems'''<!--boldface per [[R#PLA]]--> is used mainly to examine the effect of improvements or investments in a [[Operations management#Production systems|production system]]. Most often this is done using a static spreadsheet with process times and transportation times. For more sophisticated simulations [[Discrete Event Simulation]] (DES) is used with the advantages to simulate dynamics in the production system. A production system is very much dynamic depending on variations in manufacturing processes, assembly times, machine set-ups, breaks, breakdowns and small stoppages.<ref>{{cite book|last=Ulf|first=Eriksson|title=Diffusion of Discrete Event Simulation in Swedish Industry|year=2005|publisher=Doktorsavhandlingar vid Chalmers tekniska högskola|location=Gothenburg|isbn=978-91-7291-577-0}}</ref> There is much [[List of discrete event simulation software|software]] commonly used for discrete event simulation. They differ in usability and markets but do often share the same foundation.

===Sales process===
{{main|Sales process engineering}}
Simulations are useful in modeling the flow of transactions through business processes, such as in the field of [[sales process engineering]], to study and improve the flow of customer orders through various stages of completion (say, from an initial proposal for providing goods/services through order acceptance and installation). Such simulations can help predict the impact of how improvements in methods might impact variability, cost, labor time, and the number of transactions at various stages in the process. A full-featured computerized process simulator can be used to depict such models, as can simpler educational demonstrations using spreadsheet software, pennies being transferred between cups based on the roll of a die, or dipping into a tub of colored beads with a scoop.<ref name="Selden 1997">{{cite book|title=Sales Process Engineering: A Personal Workshop|author = Paul H. Selden|publisher=ASQ Quality Press|location = Milwaukee, WI|year=1997|isbn=978-0-87389-418-0}}</ref>

===Sports===
In sports, [[computer simulation]]s are often done to predict the outcome of events and the performance of individual sportspeople. They attempt to recreate the event through models built from statistics. The increase in technology has allowed anyone with knowledge of programming the ability to run simulations of their models. The simulations are built from a series of mathematical [[algorithms]], or models, and can vary with accuracy. Accuscore, which is licensed by companies such as [[ESPN]], is a well-known simulation program for all major [[sports]]. It offers a detailed analysis of games through simulated betting lines, projected point totals and overall probabilities.

With the increased interest in [[fantasy sports]] simulation models that predict individual player performance have gained popularity. Companies like What If Sports and StatFox specialize in not only using their simulations for predicting game results but how well individual players will do as well. Many people use models to determine whom to start in their fantasy leagues.

Another way simulations are helping the sports field is in the use of [[biomechanics]]. Models are derived and simulations are run from data received from sensors attached to athletes and video equipment. [[Sports biomechanics]] aided by simulation models answer questions regarding training techniques such as the effect of fatigue on throwing performance (height of throw) and biomechanical factors of the upper limbs (reactive strength index; hand contact time).<ref>{{cite journal |doi=10.1080/14763141.2011.592544 |pmid=21936288 |author=Harrison, Andrew J |title=Throwing and catching movements exhibit post-activation potentiation effects following fatigue |journal=Sports Biomechanics |volume=10 |issue=3 |pages=185–196 |year=2011 |s2cid=38009979 }}</ref>

Computer simulations allow their users to take models which before were too complex to run, and give them answers. Simulations have proven to be some of the best insights into both play performance and team predictability.

===Space shuttle countdown===
[[File:KSCFiringroom1.jpg|right|thumb|Firing Room 1 configured for [[Space Shuttle]] launches]]
Simulation was used at [[Kennedy Space Center]] (KSC) to train and certify [[Space Shuttle]] engineers during simulated launch countdown operations. The Space Shuttle engineering community would participate in a launch countdown integrated simulation before each Shuttle flight. This simulation is a virtual simulation where real people interact with simulated Space Shuttle vehicle and Ground Support Equipment (GSE) hardware. The Shuttle Final Countdown Phase Simulation, also known as S0044, involved countdown processes that would integrate many of the Space Shuttle vehicle and GSE systems. Some of the Shuttle systems integrated in the simulation are the main propulsion system, [[RS-25]], [[Space Shuttle Solid Rocket Booster|solid rocket boosters]], ground liquid hydrogen and liquid oxygen, [[external tank]], flight controls, navigation, and avionics.<ref>Sikora, E.A. (27 July 2010). Space Shuttle Main Propulsion System expert, John F. Kennedy Space Center. Interview.</ref> The high-level objectives of the Shuttle Final Countdown Phase Simulation are:
* To demonstrate [[Firing room#Firing room|firing room]] final countdown phase operations.
* To provide training for system engineers in recognizing, reporting and evaluating system problems in a time critical environment.
* To exercise the launch team's ability to evaluate, prioritize and respond to problems in an integrated manner within a time critical environment.
* To provide procedures to be used in performing failure/recovery testing of the operations performed in the final countdown phase.<ref>Shuttle Final Countdown Phase Simulation. National Aeronautics and Space Administration KSC Document # RTOMI S0044, Revision AF05, 2009.</ref>

The Shuttle Final Countdown Phase Simulation took place at the [[Kennedy Space Center]] [[Launch Control Center]] [[Firing room#Firing room|firing rooms]]. The firing room used during the simulation is the same control room where real launch countdown operations are executed. As a result, equipment used for real launch countdown operations is engaged. Command and control computers, application software, engineering plotting and trending tools, launch countdown procedure documents, launch commit criteria documents, hardware requirement documents, and any other items used by the engineering launch countdown teams during real launch countdown operations are used during the simulation.

The Space Shuttle vehicle hardware and related GSE hardware is simulated by [[mathematical models]] (written in Shuttle Ground Operations Simulator (SGOS) modeling language<ref>Shuttle Ground Operations Simulator (SGOS) Summary Description Manual. National Aeronautics and Space Administration KSC Document # KSC-LPS-SGOS-1000, Revision 3 CHG-A, 1995.</ref>) that behave and react like real hardware. During the Shuttle Final Countdown Phase Simulation, engineers command and control hardware via real application software executing in the control consoles – just as if they were commanding real vehicle hardware. However, these real software applications do not interface with real Shuttle hardware during simulations. Instead, the applications interface with mathematical model representations of the vehicle and GSE hardware. Consequently, the simulations bypass sensitive and even dangerous mechanisms while providing engineering measurements detailing how the hardware would have reacted. Since these math models interact with the command and control application software, models and simulations are also used to debug and verify the functionality of application software.<ref>Math Model Main Propulsion System (MPS) Requirements Document, National Aeronautics and Space Administration KSC Document # KSCL-1100-0522, Revision 9, June 2009.</ref>

===Satellite navigation===
{{Unreferenced section|date=September 2021}}
The only true way to test [[GNSS]] receivers (commonly known as Sat-Nav's in the commercial world) is by using an RF Constellation Simulator. A receiver that may, for example, be used on an aircraft, can be tested under dynamic conditions without the need to take it on a real flight. The test conditions can be repeated exactly, and there is full control over all the test parameters. this is not possible in the 'real-world' using the actual signals. For testing receivers that will use the new [[Galileo (satellite navigation)]] there is no alternative, as the real signals do not yet exist.

=== Trains ===
{{main|Train simulator}}

===Weather===
{{Unreferenced section|date=September 2021}}
{{main|Numerical weather prediction|Atmospheric model}}
Predicting weather conditions by extrapolating/interpolating previous data is one of the real use of simulation. Most of the weather forecasts use this information published by Weather bureaus. This kind of simulations helps in predicting and forewarning about extreme weather conditions like the path of an active hurricane/cyclone. [[Numerical weather prediction]] for forecasting involves complicated numeric computer models to predict weather accurately by taking many parameters into account.