Editing Computer simulation (section)

== In science ==
[[File:Osmosis computer simulation.jpg|250px|thumb|Computer simulation of the process of [[osmosis]] ]]

Generic examples of types of computer simulations in science, which are derived from an underlying mathematical description:
* a numerical simulation of [[differential equation]]s that cannot be solved analytically, theories that involve continuous systems such as phenomena in [[physical cosmology]], [[fluid dynamics]] (e.g., [[climate model]]s, [[roadway noise]] models, [[roadway air dispersion model]]s), [[continuum mechanics]] and [[chemical kinetics]] fall into this category.
* a [[stochastic]] simulation, typically used for discrete systems where events occur [[probabilistic]]ally and which cannot be described directly with differential equations (this is a ''discrete'' simulation in the above sense). Phenomena in this category include [[genetic drift]], [[biochemical]]<ref name=":0">{{Cite journal|last1=Gupta|first1=Ankur|last2=Rawlings|first2=James B.|date=April 2014|title=Comparison of Parameter Estimation Methods in Stochastic Chemical Kinetic Models: Examples in Systems Biology|journal=AIChE Journal |volume=60|issue=4|pages=1253–1268|doi=10.1002/aic.14409|issn=0001-1541|pmc=4946376|pmid=27429455|bibcode=2014AIChE..60.1253G }}</ref> or [[gene regulatory network]]s with small numbers of molecules. (see also: [[Monte Carlo method]]).
* multiparticle simulation of the response of nanomaterials at multiple scales to an applied force for the purpose of modeling their thermoelastic and thermodynamic properties. Techniques used for such simulations are [[Molecular dynamics]], [[Molecular mechanics]], [[Monte Carlo method]], and [[Multiscale Green's function]].

Specific examples of computer simulations include:
* statistical simulations based upon an agglomeration of a large number of input profiles, such as the forecasting of equilibrium [[temperature]] of receiving waters, allowing the gamut of [[meteorological]] data to be input for a specific locale. This technique was developed for [[thermal pollution]] forecasting.
* agent based simulation has been used effectively in [[ecology]], where it is often called "individual based modeling" and is used in situations for which individual variability in the agents cannot be neglected, such as [[population dynamics]] of [[salmon]] and [[trout]] (most purely mathematical models assume all trout behave identically).
* time stepped dynamic model. In hydrology there are several such [[hydrology transport model]]s such as the [[SWMM]] and [[DSSAM Model]]s developed by the [[U.S. Environmental Protection Agency]] for river water quality forecasting.
* computer simulations have also been used to formally [[Computational cognition|model theories of human cognition]] and performance, e.g., [[ACT-R]].
* computer simulation using [[molecular modeling]] for [[drug discovery]].<ref>{{cite journal | pmid = 26281720 | doi=10.1016/j.biotechadv.2015.08.001 | volume=33 | issue=8 | title=Discovery and resupply of pharmacologically active plant-derived natural products: A review | pmc=4748402 | year=2015 | journal=Biotechnol Adv | pages=1582–614  | last1 = Atanasov | first1 = AG | last2 = Waltenberger | first2 = B | last3 = Pferschy-Wenzig | first3 = EM | last4 = Linder | first4 = T | last5 = Wawrosch | first5 = C | last6 = Uhrin | first6 = P | last7 = Temml | first7 = V | last8 = Wang | first8 = L | last9 = Schwaiger | first9 = S | last10 = Heiss | first10 = EH | last11 = Rollinger | first11 = JM | last12 = Schuster | first12 = D | last13 = Breuss | first13 = JM | last14 = Bochkov | first14 = V | last15 = Mihovilovic | first15 = MD | last16 = Kopp | first16 = B | last17 = Bauer | first17 = R | last18 = Dirsch | first18 = VM | last19 = Stuppner | first19 = H}}</ref>
* computer simulation to model viral infection in mammalian cells.<ref name=":0" />
* computer simulation for studying the selective sensitivity of bonds by mechanochemistry during grinding of organic molecules.<ref>Mizukami, Koichi; Saito, Fumio; Baron, Michel. [http://pem.utbm.fr/materiaux_2002/file/pdf/AF01078.PDF Study on grinding of pharmaceutical products with an aid of computer simulation] {{webarchive|url=https://web.archive.org/web/20110721023918/http://pem.utbm.fr/materiaux_2002/file/pdf/AF01078.PDF |date=2011-07-21 }}</ref>
* [[Computational fluid dynamics]] simulations are used to simulate the behaviour of flowing air, water and other fluids. One-, two- and three-dimensional models are used. A one-dimensional model might simulate the effects of [[water hammer]] in a pipe. A two-dimensional model might be used to simulate the drag forces on the cross-section of an aeroplane wing. A three-dimensional simulation might estimate the heating and cooling requirements of a large building.
* An understanding of statistical thermodynamic molecular theory is fundamental to the appreciation of molecular solutions. Development of the Potential Distribution Theorem (PDT) allows this complex subject to be simplified to down-to-earth presentations of molecular theory.

Notable, and sometimes controversial, computer simulations used in science include: [[Donella Meadows]]' [[World3]] used in the ''[[Limits to Growth]]'', [[James Lovelock|James Lovelock's]] [[Daisyworld]] and Thomas Ray's [[Tierra (computer simulation)|Tierra]].

In social sciences, computer simulation is an integral component of the five angles of analysis fostered by the data percolation methodology,<ref>Mesly, Olivier
(2015). ''Creating Models in Psychological Research.'' United States: Springer Psychology: 126 pages. {{ISBN|978-3-319-15752-8}}</ref> which also includes qualitative and quantitative methods, reviews of the literature (including scholarly), and interviews with experts, and which forms an extension of data triangulation. Of course, similar to any other scientific method, [[Replication (scientific method)|replication]] is an important part of computational modeling <ref>{{cite journal | last1 = Wilensky | first1 = Uri | last2 = Rand | first2 = William | year = 2007 | title = Making Models Match: Replicating an Agent-Based Model | url = http://jasss.soc.surrey.ac.uk/10/4/2.html | journal = Journal of Artificial Societies and Social Simulation | volume = 10 | issue = 4| pages = 2 }}</ref>