A general framework for data-driven uncertainty quantification under complex input dependencies using vine copulas

Probabilistic Engineering Mechanics(2019)

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摘要
Systems subject to uncertain inputs produce uncertain responses. Uncertainty quantification (UQ) deals with the estimation of statistics of the system response, given a computational model of the system and a probabilistic model of its inputs. In engineering applications it is common to assume that the inputs are mutually independent or coupled by a Gaussian or elliptical dependence structure (copula).
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关键词
Uncertainty quantification,Input dependencies,Vine copulas,Reliability analysis,Polynomial chaos expansions
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