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Computer Modeling and Simulation

​Computer simulation modeling is a discipline gaining popularity in both government and industry. Designers, program managers, analysts, and engineers use computer simulation modeling to understand and evaluate ‘what if’ case scenarios. 

Computer simulation modeling can assist in the design, creation, and evaluation of complex systems by replicating a real or proposed system using computer software when changes to the actual system are difficult to implement, involve high costs, or  are impractical. Some examples of computer simulation modeling familiar to most of us include:  weather forecasting, flight simulators used for training pilots, and car crash modeling.

For more videos of OQM Computer Modeling and Simulation Projects, visit OQM and Computer Modeling and Simulation Projects (NIH-only access)


  • Gain greater understanding of a process
  • Identify problem areas or bottlenecks in processes
  • Evaluate effect of systems or process changes such as demand, resources, supply, and constraints
  • Identify actions needed upstream or downstream relative to a given operation, organization, or activity to either improve or mitigate processes or events
  • Evaluate impact of changes in policy prior to implementation

 Types of Simulation Models:

  • Discrete Models – Changes to the system occur at specific times
    • Division of Property Management trouble calls
    • Acquisition or construction business processes
    • A manufacturing system with parts entering and leaving at specific times
  • Continuous Models – The state of the system changes continuously over time
    • A reservoir as water flows in and out
    • Chilled water or steam distribution
  • Mixed Models – Contains both discrete and continuous elements
    • A refinery with continuously changing pressure inside vessels and discreetly occurring shutdowns
    • Chilled water distribution including plant shutdowns

Types of Data/Information Needed to Develop a Simulation Model:

  • The overall process flow and its associated resources
  • What is being produced, served, or acted upon by the process (entities)
  • Frequency at which the entities arrive in the process
  • How long do individual steps in the process take
  • Probability distributions that characterize real life uncertainties and variations in the process

Examples of use in ORS/ORF include:

  • Shooter scenarios
  • Shuttles
  • Gateway Visitor Center