[BUKU][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 …
An overview on uncertainty quantification and probabilistic learning on manifolds in multiscale mechanics of materials
C Soize - Mathematics and Mechanics of Complex Systems, 2023 - msp.org
An overview of the author's works, many of which were carried out in collaboration, is
presented. The first part concerns the quantification of uncertainties for complex engineering …
presented. The first part concerns the quantification of uncertainties for complex 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 …
Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach
Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for
its environmental disposal. To reduce the number of laboratory experiments, this study …
its environmental disposal. To reduce the number of laboratory experiments, this study …
Uncertainty quantification of microstructures: a perspective on forward and inverse problems for mechanical properties of aerospace materials
In this review, state‐of‐the‐art studies on the uncertainty quantification (UQ) of
microstructures in aerospace materials is examined, addressing both forward and inverse …
microstructures in aerospace materials is examined, addressing both forward and inverse …
On the statistical dependence for the components of random elasticity tensors exhibiting material symmetry properties
This work is concerned with the characterization of the statistical dependence between the
components of random elasticity tensors that exhibit some given material symmetries. Such …
components of random elasticity tensors that exhibit some given material symmetries. Such …
Computational nonlinear stochastic homogenization using a nonconcurrent multiscale approach for hyperelastic heterogeneous microstructures analysis
This paper is devoted to the computational nonlinear stochastic homogenization of a
hyperelastic heterogeneous microstructure using a nonconcurrent multiscale approach. The …
hyperelastic heterogeneous microstructure using a nonconcurrent multiscale approach. The …
Optimization of neural network parameters in improvement of particulate matter concentration prediction of open-pit mining
The prediction of particulate matter (PM) concentration around open-pit mining is crucial for
its control. To achieve this, machine learning (ML) techniques have been attempted in PM …
its control. To achieve this, machine learning (ML) techniques have been attempted in PM …
Stochastic model and generator for random fields with symmetry properties: application to the mesoscopic modeling of elastic random media
This paper is concerned with the construction of a new class of generalized nonparametric
probabilistic models for matrix-valued non-Gaussian random fields. More specifically, we …
probabilistic models for matrix-valued non-Gaussian random fields. More specifically, we …
From SEM images to elastic responses: A stochastic multiscale analysis of UD fiber reinforced composites
In this work, the elastic response of unidirectional fiber (UD) reinforced composites is studied
in a stochastic multiscale way. First, the micro-structure of UD carbon fiber reinforced …
in a stochastic multiscale way. First, the micro-structure of UD carbon fiber reinforced …