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

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...

Full description

Bibliographic Details
Main Authors: Filippo Landi, Francesca Marsili, Noemi Friedman, Pietro Croce
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Infrastructures
Subjects:
bayesian inversion
gPCE
surrogate model
uncertainty quantification
non-linear filter
parameter identification
Online Access:https://www.mdpi.com/2412-3811/6/11/158

Internet

https://www.mdpi.com/2412-3811/6/11/158

Similar Items