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American Institute of Aeronautics and Astronautics

    Course Outline

    Course Outline

    1. Terminology and basic principles
      • Verification and validation in science and engineering, versus software engineering
      • Error and uncertainty in modeling, simulation, and experimental measurements
      • Responsibilities for verification, validation, and uncertainty quantification

    2. Verification of codes
      • Software quality assurance
      • Order of accuracy verification
      • Method of exact solutions
      • Method of manufactured solutions

    3. Verification of solutions
      • Iterative convergence error
      • Richardson extrapolation
      • Grid convergence index
      • Practical aspects of grid refinement

    4. Validation experiments
      • Validation experiments vs. traditional experiments
      • Validation hierarchy for complex systems
      • Six principles for validation experiments
      • Design and execution of validation experiments

    5. Quantitative estimation of model form uncertainty
      • Characteristics of validation metrics
      • Validation metrics based on mean values
      • Validation metrics based on cumulative distribution functions

    6. Predictive capability in scientific computing
      • Identification and characterization of sources of uncertainty
      • Numerical, parametric, and model form uncertainty
      • Methods for estimating total predictive uncertainty
      • Updating model parameters and sensitivity analyses