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[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) …
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
Physics-informed neural networks (PINNs) have recently emerged as an alternative way of
numerically solving partial differential equations (PDEs) without the need of building …
numerically solving partial differential equations (PDEs) without the need of building …
Adversarial uncertainty quantification in physics-informed neural networks
We present a deep learning framework for quantifying and propagating uncertainty in
systems governed by non-linear differential equations using physics-informed neural …
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 …
deviation between the actual geometry and the design geometry. This geometric deviation …
Review of multi-fidelity models
Multi-fidelity models provide a framework for integrating computational models of varying
complexity, allowing for accurate predictions while optimizing computational resources …
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 …
collaborative research regarding the development and implementation of uncertainty …
Issues in deciding whether to use multifidelity surrogates
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 …
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 …
aerospace engineering, and nuclear safety, mathematical models turned into computer code …
[کتاب][B] Stochastic dynamics of structures
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 …
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 …
physical processes governing its evolution. This requires the definitions of basic variables …