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Many analysts consider modeling a simulation to be an infrastructure discipline necessary to support integration of the partial knowledge of other disciplines needed in applications with its robust theory based on dynamic systems, computer science and an ontology of the domain.   

The conduct of a simulation study results in the generation of system performance data, most often in large quantities.

These data are stored in a computer system as large arrays of numbers. The process of converting the data into meaningful information that describes the behavior of the system is called analysis.

There are numerous techniques and approaches to conducting analysis. The development and use of these techniques and approaches are a function of the branch of mathematics and systems engineering called operations research.

M&S – based analysis has a simulation output that typically represents a dynamic response of the modeled system for a given set of conditions and inputs. Analysis is performed to transform these data when seeking answers to questions that motivated the simulation study.

 The simulation study can include a number of functions:

  • Design of experiments — the design of a set of simulation experiments suitable for addressing a specific system performance question
  •  Performance evaluation — the evaluation of system performance, measurement of how it approaches a desired performance level
  • Sensitivity analysis — system sensitivity to a set of input parameters
  • System comparison — comparison of two or more system alternatives to derive best system performance with given conditions
  • Constrained optimization — determination of optimum parameters to derive system performance objective

Want to learn more? Tonex offers Fundamentals of Modeling and Simulation Training Workshop, a 2-day course that introduces the key Modeling & Simulation (M&S) concepts, terminology of modern modeling and simulation technology, use cases and applications in operations research and systems engineering, verification and validation of critical functions, failure analysis, modeling and simulating crucial requirements such as performance, reliability, safety, security, threats. 

Participants will  gain a broad knowledge of M&S concepts, use cases, applications, methods, procedures, schemes, natural languages, numerical data, and important mathematical topics.

For more information, questions, comments, contact us.

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