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contributor authorRohatgi, Upendra S.
date accessioned2022-05-08T09:08:41Z
date available2022-05-08T09:08:41Z
date copyright2/21/2022 12:00:00 AM
date issued2022
identifier issn0098-2202
identifier otherfe_144_04_040801.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4284779
description abstractEngineering problems are generally solved by analytical models or computer codes. These models, in addition to conservation equations, also include many empirical relationships and approximate numerical methods. Each of these components contributes to the uncertainty in the prediction. A systematic approach to judge the applicability of the code to the intended application is needed. It starts from verification of implementation of formulation in the code, identification of important phenomena, finding relevant tests with quantified uncertainty for these phenomena, and validation of the code by comparing predictions with the relevant test data. The relevant tests must address phenomena as expected in the intended application. In case of small size or limited condition tests, the scaling analyses are needed to assess the relevancy of the tests. Finally, a statement of uncertainty in the prediction is needed. Systematic approaches are described to aggregate uncertainties from different components of the code for intended application. In this paper, verification, validation, and uncertainty quantifications (VVUQs) are briefly described.
publisherThe American Society of Mechanical Engineers (ASME)
titleVerification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019)
typeJournal Paper
journal volume144
journal issue4
journal titleJournal of Fluids Engineering
identifier doi10.1115/1.4053718
journal fristpage40801-1
journal lastpage40801-8
page8
treeJournal of Fluids Engineering:;2022:;volume( 144 ):;issue: 004
contenttypeFulltext


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