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Microstructure Models and Material Response by Extreme Value Theory
4 references·3 citing·32 second hop
Microstructure Models and Material Response by Extreme Value Theory (2016)Microstructure Models and Material Respon…Uncertainty quantification in computational stochastic multiscale analysis of nonlinear elastic materials (2012)Uncertainty quantification in…Probabilistic models for stochastic elliptic partial differential equations (2010)Probabilistic models for stoc…Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data (2010)Identification of high-dimens…Non-Gaussian positive-definite matrix-valued random fields for elliptic stochastic partial differential operators (2005)Non-Gaussian positive-definit…Stochastic modelling of symmetric positive definite material tensors (2024)Stochastic modelling of symme…Multiscale simulation of fiber composites with spatially varying uncertainties (2020)Multiscale simulation of fibe…Modeling non-Gaussian random fields of material properties in multiscale mechanics of materials (2020)Modeling non-Gaussian random …Stochastic Finite Elements: A Spectral Approach (1991)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)A computational inverse method for identification of non-Gaussian random fields using the Bayesian approach in very high dimension (2011)Stochastic Model and Generator for Random Fields with Symmetry Properties: Application to the Mesoscopic Modeling of Elastic Random Media (2013)Polynomial Chaos Expansion of a Multimodal Random Vector (2015)Stochastic Differential Equations and Diffusion Processes (1983)Construction of probability distributions in high dimension using the maximum entropy principle: Applications to stochastic processes, random fields and random matrices (2008)Recent Developments in Spectral Stochastic Methods for the Numerical Solution of Stochastic Partial Differential Equations (2009)Stochastic modeling of uncertainties in computational structural dynamics—Recent theoretical advances (2011)Numerical solution of stochastic differential equations (2016)Extremes and related properties of random sequences and processes (1984)Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations (2004)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2007)A method for solving stochastic equations by reduced order models and local approximations (2012)Bayesian identification and model comparison for random property fields derived from material microstructure (2020)A spectral surrogate model for stochastic simulators computed from trajectory samples (2023)Uncertainty propagation using Wiener–Haar expansions (2004)Spectral methods for uncertainty quantification : with applications to computational fluid dynamics (2010)Uncertainty quantification through the Monte Carlo method in a cloud computing setting (2014)A review on stochastic multiscale analysis for FRP composite structures (2022)An overview on uncertainty quantification and probabilistic learning on manifolds in multiscale mechanics of materials (2023)An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (2011)Estimation of spatial uncertainty in material property distributions within heterogeneous structures using optimized convolutional neural networks (2022)Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization (2024)Multiscale simulation of spatially correlated microstructure via a latent space representation (2024)Design and Analysis of Computer Experiments (1989)Use of Kriging Models to Approximate Deterministic Computer Models (2005)Practical Bayesian Optimization of Machine Learning Algorithms (2012)STATISTICS FOR SPATIAL DATA (1992)Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations (2004)An Introduction to Computational Stochastic PDEs (2014)
this work references cited by second hop

References

  • 2005Non-Gaussian positive-definite matrix-valued random fields for elliptic stochastic partial differential operators183 cited
  • 2012Uncertainty quantification in computational stochastic multiscale analysis of nonlinear elastic materials98 cited
  • 2010Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data87 cited
  • 2010Probabilistic models for stochastic elliptic partial differential equations37 cited

Cited by

  • 2020Modeling non-Gaussian random fields of material properties in multiscale mechanics of materials19 cited
  • 2024Stochastic modelling of symmetric positive definite material tensors12 cited
  • 2020Multiscale simulation of fiber composites with spatially varying uncertainties10 cited

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