A general framework for data-driven uncertainty quantification under complex input dependencies using vine copulas
Probabilistic Engineering Mechanics(2019)
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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