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American Institute of Aeronautics and Astronautics

    Course Outline

    Verification and Validation in Scientific Computing

    Course Outline:

    I. Terminology and basic principles
    A. Verification and validation in science and engineering, versus software engineering
    B. Error and uncertainty in modeling, simulation, and experimental measurements
    C. Responsibilities for verification, validation, and uncertainty quantification

    II. Verification of codes
    A. Software quality assurance
    B. Order of accuracy verification
    C. Method of exact solutions
    D. Method of manufactured solutions

    III. Verification of solutions
    A. Iterative convergence error
    B. Richardson extrapolation
    C. Grid convergence index
    D. Practical aspects of grid refinement

    IV. Validation experiments
    A. Validation experiments vs. traditional experiments
    B. Validation hierarchy for complex systems
    C. Six principles for validation experiments
    D. Design and execution of validation experiments

    V. Quantitative estimation of model form uncertainty
    A. Characteristics of validation metrics
    B. Validation metrics based on mean values
    C. Validation metrics based on cumulative distribution functions

    VI. Predictive capability in scientific computing
    A. Identification and characterization of sources of uncertainty
    B. Numerical, parametric, and model form uncertainty
    C. Methods for estimating total predictive uncertainty
    D. Updating model parameters and sensitivity analyses