[LIBRO][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 …
Stochastic modeling of uncertainties in computational structural dynamics—recent theoretical advances
C Soize - Journal of Sound and Vibration, 2013 - Elsevier
This paper deals with a short overview on stochastic modeling of uncertainties. We introduce
the types of uncertainties, the variability of real systems, the types of probabilistic …
the types of uncertainties, the variability of real systems, the types of probabilistic …
An overview of nonintrusive characterization, propagation, and sensitivity analysis of uncertainties in computational mechanics
In this paper, we offer a short overview of a number of methods that have been reported in
the computational-mechanics literature for quantifying uncertainties in engineering …
the computational-mechanics literature for quantifying uncertainties in engineering …
Stochastic models of uncertainties in computational mechanics
C Soize - 2012 - ascelibrary.org
Stochastic Models of Uncertainties in Computational Mechanics: Front Matter Page 1
Lecture Notes in Mechanics 2 Stochastic Models of Uncertainties in Computational …
Lecture Notes in Mechanics 2 Stochastic Models of Uncertainties in Computational …
Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems
We consider a high-dimensional nonlinear computational model of a dynamical system,
parameterized by a vector-valued control parameter, in the presence of uncertainties …
parameterized by a vector-valued control parameter, in the presence of uncertainties …
Uncertainty quantification in computational stochastic multiscale analysis of nonlinear elastic materials
This paper is devoted to a computational stochastic multiscale analysis of nonlinear
structures made up of heterogeneous hyperelastic materials. At the microscale level, the …
structures made up of heterogeneous hyperelastic materials. At the microscale level, the …
Polynomial chaos expansion of a multimodal random vector
C Soize - SIAM/ASA Journal on Uncertainty Quantification, 2015 - SIAM
A methodology and algorithms are proposed for constructing the polynomial chaos
expansion (PCE) of multimodal random vectors. An algorithm is developed for generating …
expansion (PCE) of multimodal random vectors. An algorithm is developed for generating …
A computational inverse method for identification of non-Gaussian random fields using the Bayesian approach in very high dimension
C Soize - Computer Methods in Applied Mechanics and …, 2011 - Elsevier
This paper is devoted to the identification of Bayesian posteriors for the random coefficients
of the high-dimension polynomial chaos expansions of non-Gaussian tensor-valued random …
of the high-dimension polynomial chaos expansions of non-Gaussian tensor-valued random …
Identification of polynomial chaos representations in high dimension from a set of realizations
This paper deals with the identification in high dimensions of a polynomial chaos expansion
of random vectors from a set of realizations. Due to numerical and memory constraints, the …
of random vectors from a set of realizations. Due to numerical and memory constraints, the …
Updating an uncertain and expensive computational model in structural dynamics based on one single target FRF using a probabilistic learning tool
The paper presents an appropriate and efficient methodology for updating the control
parameters of very large uncertain computational models, which are used for analyzing the …
parameters of very large uncertain computational models, which are used for analyzing the …