User: Guest  Login
Title:

A Generalized Probabilistic Learning Approach for Multi-Fidelity Uncertainty Propagation in Complex Physical Simulations

Document type:
Zeitschriftenaufsatz
Author(s):
Nitzler, Jonas; Biehler, Jonas; Fehn, Niklas; Koutsourelakis, Phaedon-Stelios; Wall, Wolfgang A.
Abstract:
Two of the most significant challenges in uncertainty propagation pertain to the high computational cost for the simulation of complex physical models and the high dimension of the random inputs. In applications of practical interest both of these problems are encountered and standard methods for uncertainty quantification either fail or are not feasible. To overcome the current limitations, we propose a probabilistic multi-fidelity framework that can exploit lower-fidelity model versions of the...     »
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Journal title:
Computer Methods in Applied Mechanics and Engineering
Year:
2022
Journal volume:
400
Covered by:
Scopus
Fulltext / DOI:
doi:https://doi.org/10.1016/j.cma.2022.115600
Status:
Verlagsversion / published
 BibTeX