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Process simulation is a model-based representation of chemical, physical, biological, and other technical processes and unit operations in software. Basic prerequisites for the model are chemical and physical properties [ 1 ] of pure components and mixtures, of reactions, and of mathematical models which, in combination, allow the calculation ...
The mathematical model represents the physical model in virtual form, and conditions are applied that set up the experiment of interest. The simulation starts – i.e., the computer calculates the results of those conditions on the mathematical model – and outputs results in a format that is either machine- or human-readable, depending upon ...
Model validation is defined to mean "substantiation that a computerized model within its domain of applicability possesses a satisfactory range of accuracy consistent with the intended application of the model". [3] A model should be built for a specific purpose or set of objectives and its validity determined for that purpose. [3]
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.
A mathematical model of the economy, having been fitted to historical economic data, is used as a proxy for the actual economy; proposed values of government spending, taxation, open market operations, etc. are used as inputs to the simulation of the model, and various variables of interest such as the inflation rate, the unemployment rate, the ...
This problem is typically solved by bootstrapping the simulation model. Only a limited effort is made to assign realistic times to the initial set of pending events. These events, however, schedule additional events, and with time, the distribution of event times approaches its steady state. This is called bootstrapping the simulation model. In ...
A simple STELLA model of a cat population; stocks are represented as rectangles, flows as pipes to/from the stock, converters as the circles, and connectors as the curved lines with arrows. [12] STELLA's approach to modeling systems shares some similarities with a precursor, the DYNAMO simulation language.
The system usually change over time, variables of the model, then change continuously as well. Continuous simulation thereby simulates the system over time, given differential equations determining the rates of change of state variables. [16] Example of continuous system is the predator/prey model [17] or cart-pole balancing [18]