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    Multiscale Validation and Uncertainty Quantification for Problems With Sparse Data 

    Source: Journal of Verification, Validation and Uncertainty Quantification:;2017:;volume( 002 ):;issue: 001:;page 11001
    Author(s): Jatale, Anchal; Smith, Philip J.; Thornock, Jeremy N.; Smith, Sean T.; Spinti, Jennifer P.; Hradisky, Michal
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Quantification of uncertainty in the simulation results becomes difficult for complex real-world systems with little or no experimental data. This paper describes a validation and uncertainty quantification (VUQ) approach ...
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    Using Bayesian Analysis to Quantify Uncertainty in Radiometer Measurements 

    Source: Journal of Verification, Validation and Uncertainty Quantification:;2021:;volume( 006 ):;issue: 001:;page 011003-1
    Author(s): Spinti, Jennifer P.; Smith, Sean T.; Smith, Philip J.; Harding, N. Stanley; Scheib, Kaitlyn; Draper, Teri S.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We apply Bayesian inference to instrument calibration and experimental-data uncertainty analysis for the specific application of measuring radiative intensity with a narrow-angle radiometer. We develop a physics-based ...
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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
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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