7 research outputs found

    Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS) Code Verification and Validation Data Standards and Requirements: Fluid Dynamics Version 1.0

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    V&V and UQ are the primary means to assess the accuracy and reliability of M&S and, hence, to establish confidence in M&S. Though other industries are establishing standards and requirements for the performance of V&V and UQ, at present, the nuclear industry has not established such standards or requirements. However, the nuclear industry is beginning to recognize that such standards are needed and that the resources needed to support V&V and UQ will be very significant. In fact, no single organization has sufficient resources or expertise required to organize, conduct and maintain a comprehensive V&V and UQ program. What is needed is a systematic and standardized approach to establish and provide V&V and UQ resources at a national or even international level, with a consortium of partners from government, academia and industry. Specifically, what is needed is a structured and cost-effective knowledge base that collects, evaluates and stores verification and validation data, and shows how it can be used to perform V&V and UQ, leveraging collaboration and sharing of resources to support existing engineering and licensing procedures as well as science-based V&V and UQ processes. The Nuclear Energy Knowledge base for Advanced Modeling and Simulation (NE-KAMS) is being developed at the Idaho National Laboratory in conjunction with Bettis Laboratory, Sandia National Laboratories, Argonne National Laboratory, Utah State University and others with the objective of establishing a comprehensive and web-accessible knowledge base to provide V&V and UQ resources for M&S for nuclear reactor design, analysis and licensing. The knowledge base will serve as an important resource for technical exchange and collaboration that will enable credible and reliable computational models and simulations for application to nuclear power. NE-KAMS will serve as a valuable resource for the nuclear industry, academia, the national laboratories, the U.S. Nuclear Regulatory Commission (NRC) and the public and will help ensure the safe, economical and reliable operation of existing and future nuclear reactors

    Validating the FLASH Code: Vortex-Dominated Flows

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    As a component of the Flash Center's validation program, we compare FLASH simulation results with experimental results from Los Alamos National Laboratory. The flow of interest involves the lateral interaction between a planar Ma=1.2 shock wave with a cylinder of gaseous sulfur hexafluoride (SF_6) in air, and in particular the development of primary and secondary instabilities after the passage of the shock. While the overall evolution of the flow is comparable in the simulations and experiments, small-scale features are difficult to match. We focus on the sensitivity of numerical results to simulation parameters.Comment: 10 pages, 5 figures, presented at the 5th International Conference on High Energy Laboratory Astrophysics, Tucson, AZ, March 10-13, 200

    Sensitivity and uncertainty quantification techniques applied to systems of conservation laws

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    Uncertainty quantification techniques are increasingly important in the interpretation of data and numerical simulations. Such techniques are typically employed either on data with poorly characterized underlying dynamics or on values from highly idealized model evaluations. We examine the application of these techniques to an intermediate case, in which data are generated from coupled, nonlinear partial differential equations¿conservation laws¿that admit discontinuous solutions. The values we analyze are generated from the numerical solution of the PDEs, in which we systematically vary both (i) fundamental modeling parameters and (ii) the underlying numerical algorithms. A number of sensitivity tests will be performed in order to assess the relative importance of such different types of uncertainty and we draw preliminary conclusions and speculate on the implications for more complex simulations.JRC.DG.G.3-Econometrics and applied statistic
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