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A simulation is an imitative representation of a process or system that could exist in the real world. [ 1 ][ 2 ][ 3 ] In this broad sense, simulation can often be used interchangeably with model. [ 2 ] Sometimes a clear distinction between the two terms is made, in which simulations require the use of models; the model represents the key ...
Modeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making. [ 1 ][ 2 ] In the computer application of modeling and simulation a computer is used ...
Simulacra and Simulation (French: Simulacres et Simulation) is a 1981 philosophical treatise by the philosopher and cultural theorist Jean Baudrillard, in which he seeks to examine the relationships between reality, symbols, and society, in particular the significations and symbolism of culture and media involved in constructing an understanding of shared existence.
Computer simulation is the running of a mathematical model on a computer, the model being designed to represent the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict.
Large eddy simulation of a turbulent gas velocity field. Large eddy simulation (LES) is a mathematical model for turbulence used in computational fluid dynamics. It was initially proposed in 1963 by Joseph Smagorinsky to simulate atmospheric air currents, [ 1 ] and first explored by Deardorff (1970). [ 2 ] LES is currently applied in a wide ...
Simulation modeling. Simulation modeling is the process of creating and analyzing a digital prototype of a physical model to predict its performance in the real world. Simulation modeling is used to help designers and engineers understand whether, under what conditions, and in which ways a part could fail and what loads it can withstand.
Synthetic data is generated to meet specific needs or certain conditions that may not be found in the original, real data. One of the hurdles in applying up-to-date machine learning approaches for complex scientific tasks is the scarcity of labeled data, a gap effectively bridged by the use of synthetic data, which closely replicates real experimental data. [3]
PhET Interactive Simulations, a project at the University of Colorado Boulder, is a non-profit [1] open educational resource project that creates and hosts explorable explanations. It was founded in 2002 by Nobel Laureate Carl Wieman. PhET began with Wieman's vision to improve the way science is taught and learned.