[PDF][PDF] Uncertainty analysis for fluid mechanics with applications

RW Walters, L Huyse - 2002‏ - academia.edu
This paper reviews uncertainty analysis methods and their application to fundamental
problems in fluid dynamics. Probabilistic(Monte-Carlo, Moment methods, Polynomial Chaos) …

Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems

D Zhang, L Lu, L Guo, GE Karniadakis - Journal of Computational Physics, 2019‏ - Elsevier
Physics-informed neural networks (PINNs) have recently emerged as an alternative way of
numerically solving partial differential equations (PDEs) without the need of building …

Adversarial uncertainty quantification in physics-informed neural networks

Y Yang, P Perdikaris - Journal of Computational Physics, 2019‏ - Elsevier
We present a deep learning framework for quantifying and propagating uncertainty in
systems governed by non-linear differential equations using physics-informed neural …

Review of geometric uncertainty quantification in gas turbines

J Wang, X Zheng - Journal of Engineering for Gas …, 2020‏ - asmedigitalcollection.asme.org
Due to the manufacturing error and in-service degradation of gas turbines, there is always a
deviation between the actual geometry and the design geometry. This geometric deviation …

Review of multi-fidelity models

MG Fernández-Godino - arxiv preprint arxiv:1609.07196, 2016‏ - arxiv.org
Multi-fidelity models provide a framework for integrating computational models of varying
complexity, allowing for accurate predictions while optimizing computational resources …

[کتاب][B] Uncertainty quantification

C Soize - 2017‏ - Springer
This book results from a course developed by the author and reflects both his own and
collaborative research regarding the development and implementation of uncertainty …

Issues in deciding whether to use multifidelity surrogates

M Giselle Fernández-Godino, C Park, NH Kim… - Aiaa Journal, 2019‏ - arc.aiaa.org
Multifidelity surrogates are essential in cases where it is not affordable to have more than a
few high-fidelity samples, but it is affordable to have as many low-fidelity samples as …

[کتاب][B] Basics and trends in sensitivity analysis: Theory and practice in R

S Da Veiga, F Gamboa, B Iooss, C Prieur - 2021‏ - SIAM
In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …

[کتاب][B] Stochastic dynamics of structures

J Li, J Chen - 2009‏ - books.google.com
In Stochastic Dynamics of Structures, Li and Chen present a unified view of the theory and
techniques for stochastic dynamics analysis, prediction of reliability, and system control of …

[کتاب][B] Stochastic finite element methods and reliability: a state-of-the-art report

B Sudret, A Der Kiureghian - 2000‏ - researchgate.net
Modeling a mechanical system can be defined as the mathematical idealization of the
physical processes governing its evolution. This requires the definitions of basic variables …