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    Separability of Mesh Bias and Parametric Uncertainty for a Full System Thermal Analysis

    Source: Journal of Verification, Validation and Uncertainty Quantification:;2019:;volume( 003 ):;issue: 003::page 31006
    Author:
    Schroeder, Benjamin B.
    ,
    Silva, III, Humberto
    ,
    Smith, Kyle D.
    DOI: 10.1115/1.4042815
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: When making computational simulation predictions of multiphysics engineering systems, sources of uncertainty in the prediction need to be acknowledged and included in the analysis within the current paradigm of striving for simulation credibility. A thermal analysis of an aerospace geometry was performed at Sandia National Laboratories. For this analysis, a verification, validation, and uncertainty quantification (VVUQ) workflow provided structure for the analysis, resulting in the quantification of significant uncertainty sources including spatial numerical error and material property parametric uncertainty. It was hypothesized that the parametric uncertainty and numerical errors were independent and separable for this application. This hypothesis was supported by performing uncertainty quantification (UQ) simulations at multiple mesh resolutions, while being limited by resources to minimize the number of medium and high resolution simulations. Based on this supported hypothesis, a prediction including parametric uncertainty and a systematic mesh bias is used to make a margin assessment that avoids unnecessary uncertainty obscuring the results and optimizes use of computing resources.
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      Separability of Mesh Bias and Parametric Uncertainty for a Full System Thermal Analysis

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4257779
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    contributor authorSchroeder, Benjamin B.
    contributor authorSilva, III, Humberto
    contributor authorSmith, Kyle D.
    date accessioned2019-06-08T09:29:41Z
    date available2019-06-08T09:29:41Z
    date copyright2/22/2019 12:00:00 AM
    date issued2019
    identifier issn2377-2158
    identifier othervvuq_003_03_031006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4257779
    description abstractWhen making computational simulation predictions of multiphysics engineering systems, sources of uncertainty in the prediction need to be acknowledged and included in the analysis within the current paradigm of striving for simulation credibility. A thermal analysis of an aerospace geometry was performed at Sandia National Laboratories. For this analysis, a verification, validation, and uncertainty quantification (VVUQ) workflow provided structure for the analysis, resulting in the quantification of significant uncertainty sources including spatial numerical error and material property parametric uncertainty. It was hypothesized that the parametric uncertainty and numerical errors were independent and separable for this application. This hypothesis was supported by performing uncertainty quantification (UQ) simulations at multiple mesh resolutions, while being limited by resources to minimize the number of medium and high resolution simulations. Based on this supported hypothesis, a prediction including parametric uncertainty and a systematic mesh bias is used to make a margin assessment that avoids unnecessary uncertainty obscuring the results and optimizes use of computing resources.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleSeparability of Mesh Bias and Parametric Uncertainty for a Full System Thermal Analysis
    typeJournal Paper
    journal volume3
    journal issue3
    journal titleJournal of Verification, Validation and Uncertainty Quantification
    identifier doi10.1115/1.4042815
    journal fristpage31006
    journal lastpage031006-12
    treeJournal of Verification, Validation and Uncertainty Quantification:;2019:;volume( 003 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian