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Simulation is the imitation of the operation of a real-world process or system over time, typically using computer software. It allows for the verification of analytic solutions, providing a means to validate theoretical models against real-world scenarios.
A simulation is model is designed to arrive at a single specific numerical answer to a given problem. false. simulation typically requires a familiarity with statistics to evaluate the results. true. the verification process involves making sure that. the model is internally consistent and logical. the validation process involves making sure that.
Subject provides an introduction to modeling and simulation. Scientists and engineers have long used models to better understand the system they study, for analysis and quantification, performance prediction and design.
Lecture 2 - Modeling and Simulation • Model types: ODE, PDE, State Machines, Hybrid • Modeling approaches: – physics based (white box) – input-output models (black box) • Linear systems • Simulation • Modeling uncertainty
A mathematical-logical form of an existing or proposed system, called a simulation model, is constructed (art). Experiments are conducted with the model that generates numerical results (science). The model and experimental results are interpreted to draw conclusions about the system (art).
In analysis, abstract models are built inductively from observations of a real system. In design, models deductively derived from a priori knowledge are used to build a system, satisfying certain design goals. Often, an iterative combination of analysis and design is needed to solve real problems.
