A computational inverse method for identification of non-Gaussian random fields using the Bayesian approach in very high dimension
From MaRDI portal
Publication:660306
DOI10.1016/j.cma.2011.07.005zbMath1230.74241OpenAlexW2065620939MaRDI QIDQ660306
Publication date: 1 February 2012
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Full work available at URL: https://hal-upec-upem.archives-ouvertes.fr/hal-00684294/file/publi-2011-CMAME-200_45-46_3083-3099-soize-preprint.pdf
Probabilistic models, generic numerical methods in probability and statistics (65C20) Inverse problems in equilibrium solid mechanics (74G75) Stochastic and other probabilistic methods applied to problems in solid mechanics (74S60)
Related Items
Spatially-dependent material uncertainties in anisotropic nonlinear elasticity: stochastic modeling, identification, and propagation, Probabilistic learning inference of boundary value problem with uncertainties based on Kullback-Leibler divergence under implicit constraints, Bayesian uncertainty quantification of turbulence models based on high-order adjoint, Bayesian identification and model comparison for random property fields derived from material microstructure, Adaptive method for indirect identification of the statistical properties of random fields in a Bayesian framework, Tensor- and spinor-valued random fields with applications to continuum physics and cosmology, Updating an uncertain and expensive computational model in structural dynamics based on one single target FRF using a probabilistic learning tool, Inverse elastic scattering by random periodic structures, Probabilistic learning constrained by realizations using a weak formulation of Fourier transform of probability measures, An interval framework for uncertain frequency response of multi-cracked beams with application to vibration reduction via tuned mass dampers, Polynomial-chaos-based conditional statistics for probabilistic learning with heterogeneous data applied to atomic collisions of helium on graphite substrate, Unnamed Item, Convergence acceleration of polynomial chaos solutions via sequence transformation, Uncertainty quantification in computational stochastic multiscale analysis of nonlinear elastic materials, Bayesian adaptation of chaos representations using variational inference and sampling on geodesics, Compressed Principal Component Analysis of Non-Gaussian Vectors, A robust solution of a statistical inverse problem in multiscale computational mechanics using an artificial neural network, Reduced model of macro-scale stochastic plasticity identification by Bayesian inference: application to quasi-brittle failure of concrete, A patching algorithm for conditional random fields in modeling material properties, Random field representations for stochastic elliptic boundary value problems and statistical inverse problems
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A Newton method for the resolution of steady stochastic Navier-Stokes equations
- Reduced chaos decomposition with random coefficients of vector-valued random variables and random fields
- Solving elliptic problems with non-Gaussian spatially-dependent random coefficients
- Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data
- Identification of parametric models from experimental data. Transl. from an upd. French version by the authors, with the help of John Norton
- Solving elliptic boundary value problems with uncertain coefficients by the finite element method: the stochastic formulation
- Random matrix theory for modeling uncertainties in computational mechanics
- Theoretical framework and experimental procedure for modelling mesoscopic volume fraction stochastic fluctuations in fiber reinforced composites
- Stochastic spectral methods for efficient Bayesian solution of inverse problems
- A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach
- A probabilistic construction of model validation
- Identification of Bayesian posteriors for coefficients of chaos expansions
- Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems
- Identification of chaos representations of elastic properties of random media using experimental vibration tests
- Bayesian modelling strategies for spatially varying regression coefficients: a multivariate perspective for multiple outcomes
- Polynomial chaos representation of spatio-temporal random fields from experimental measurements
- Variable kernel density estimation
- Statistical and computational inverse problems.
- A Bayesian inference approach to the inverse heat conduction problem
- Non-Gaussian positive-definite matrix-valued random fields for elliptic stochastic partial differential operators
- On the construction and analysis of stochastic models: characterization and propagation of the errors associated with limited data
- An extended stochastic finite element method for solving stochastic partial differential equations on random domains
- Generalized spectral decomposition method for solving stochastic finite element equations: invariant subspace problem and dedicated algorithms
- Computational Aspects for Constructing Realizations of Polynomial Chaos in High Dimension
- Asymptotic Sampling Distribution for Polynomial Chaos Representation from Data: A Maximum Entropy and Fisher Information Approach
- Multi-Element Generalized Polynomial Chaos for Arbitrary Probability Measures
- Maximum likelihood estimation of stochastic chaos representations from experimental data
- Generalized probabilistic approach of uncertainties in computational dynamics using random matrices and polynomial chaos decompositions
- Construction of probability distributions in high dimension using the maximum entropy principle: Applications to stochastic processes, random fields and random matrices
- Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics
- An efficient Bayesian inference approach to inverse problems based on an adaptive sparse grid collocation method
- Strain and stress computations in stochastic finite element methods
- Spectral Methods for Uncertainty Quantification
- Bayesian Missing Data Problems
- Bayesian Prediction of Transformed Gaussian Random Fields
- Introduction to Stochastic Search and Optimization
- Spartan Gibbs Random Field Models for Geostatistical Applications
- Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure
- Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes
- Hierarchical Bayesian models for inverse problems in heat conduction
- Uncertainty propagation in CFD using polynomial chaos decomposition
- Extensions and Applications of the Householder Algorithm for Solving Linear Least Squares Problems
- Efficient models for correlated data via convolutions of intrinsic processes
- A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data