gPCE-Based Stochastic Inverse Methods: A Benchmark Study from a Civil Engineer’s Perspective

In civil and mechanical engineering, Bayesian inverse methods may serve to calibrate the uncertain input parameters of a structural model given the measurements of the outputs. Through such a Bayesian framework, a probabilistic description of parameters to be calibrated can be obtained; this approac...

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Autores principales: Filippo Landi, Francesca Marsili, Noemi Friedman, Pietro Croce
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/e26667696919492baf7d90941c77e856
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