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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]
Simulation modeling follows a process much like this: Use a 2D or 3D CAD tool to develop a virtual model, also known as a digital prototype, to represent a design. Generate a 2D or 3D mesh for analysis calculations. Automatic algorithms can create finite element meshes, or users can create structured meshes to maintain control over element quality.
Such models are often used in simulating physical systems, as a simpler modeling case before dynamic simulation is attempted. Dynamic simulations attempt to capture changes in a system in response to (usually changing) input signals. Stochastic models use random number generators to model chance or random events;
Human-in-the-loop simulation of outer space Visualization of a direct numerical simulation model. 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.
A simulation is a way to implement the model, often employed when the model is too complex for the analytical solution. A steady-state simulation provides information about the system at a specific instant in time (usually at equilibrium, if such a state exists). A dynamic simulation provides information over time.
Gekko - simulation software in Python with machine learning and optimization; GNU Octave - an open-source mathematical modeling and simulation software very similar to using the same language as MATLAB and Freemat. JModelica.org is a free and open source software platform based on the Modelica modeling language.