Multifidelity Reliability Estimation. Issue 1 (18th November 2019) - Proppe, Carsten
Abstract: Multi‐fidelity estimation combines the output of simulation models of different approximation quality and from different sources in order to obtain efficient estimators for a quantity of interest. It relies on a model hierarchy that is established either by means of an approximation parameter or the Pearson correlation of the model outputs. Here, alternative measures based on the copula or on information theory are introduced in order to order models. To combine the results from the model hierarchy, information fusion methods based on differences of the quantity of interest and on conditional probabilities are introduced. They are combined with the moving particles method in order to yield efficient estimators for the probability of failure.