Dual order-reduced Gaussian process emulators (DORGP) for quantifying high-dimensional uncertain crack growth using limited and noisy data

Cites Work

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A phase-field model for ductile fracture at finite strains and its experimental verification
Practical application of the stochastic finite element method
A two-dimensional isogeometric boundary element method for elastostatic analysis
Recent developments in spectral stochastic methods for the numerical solution of stochastic partial differential equations
Fully automatic modelling of cohesive discrete crack propagation in concrete beams using local arc-length methods
Contact treatment in isogeometric analysis with NURBS
An extended finite element method for dislocations in complex geometries: thin films and nanotubes
Proper orthogonal decomposition and Monte Carlo based isogeometric stochastic method for material, geometric and force multi-dimensional uncertainties
Isogeometric analysis: CAD, finite elements, NURBS, exact geometry and mesh refinement
Isogeometric analysis of structural vibrations
Numerical simulations of fast crack growth in brittle solids
Meshless methods: An overview and recent developments
Robust and efficient methods for stochastic finite element analysis using Monte Carlo simulation
Computational model for discrete crack growth in plain and reinforced concrete
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
A tutorial on Gaussian process regression: modelling, exploring, and exploiting functions
Higher order B-spline collocation at the Greville abscissae
Stochastic fatigue crack growth simulation of interfacial crack in bi-layered FGMs using XIGA
Reduced order modeling for nonlinear structural analysis using Gaussian process regression
Systems of Gaussian process models for directed chains of solvers
A novel multi-grid based reanalysis approach for efficient prediction of fatigue crack propagation
Deep UQ: learning deep neural network surrogate models for high dimensional uncertainty quantification
Deep-learning-based surrogate flow modeling and geological parameterization for data assimilation in 3D subsurface flow
Uncertainty quantification of spatially uncorrelated loads with a reduced-order stochastic isogeometric method
Graph neural networks for simulating crack coalescence and propagation in brittle materials
Accelerating phase-field predictions via recurrent neural networks learning the microstructure evolution in latent space
Data-driven uncertainty quantification in computational human head models
High-order extended finite element methods for solving interface problems
Data-driven streamline stiffener path optimization (SSPO) for sparse stiffener layout design of non-uniform curved grid-stiffened composite (NCGC) structures
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
A Nitsche extended finite element method for the biharmonic interface problem
Accelerating uncertainty quantification of groundwater flow modelling using a deep neural network proxy
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian processes
Isogeometric boundary element methods for three dimensional static fracture and fatigue crack growth
Shape optimization directly from CAD: an isogeometric boundary element approach using T-splines
An isogeometric symmetric Galerkin boundary element method for two-dimensional crack problems
Accelerating Monte Carlo estimation with derivatives of high-level finite element models
Uncertainty propagation in finite deformations--A spectral stochastic Lagrangian approach
GPU-acceleration of stiffness matrix calculation and efficient initialization of EFG meshless methods
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems
Computationally efficient and effective peridynamic model for cracks and fractures in homogeneous and heterogeneous materials
A phase field model for fatigue fracture in piezoelectric solids: a residual controlled staggered scheme
Strain energy density as a Gaussian process and its utilization in stochastic finite element analysis: application to planar soft tissues
Full-field order-reduced Gaussian process emulators for nonlinear probabilistic mechanics
A double-phase field method for mixed mode crack modelling in 3D elasto-plastic solids with crack-direction-based strain energy decomposition
Introduction to Uncertainty Quantification
Principal component analysis: a review and recent developments
Reducing the Dimensionality of Data with Neural Networks
Three-dimensional crack growth simulation using BEM
Two-dimensional stress intensity factor computations using the boundary element method
10.1162/15324430152748236
The Stochastic Perturbation Method for Computational Mechanics
Solving parametric PDE problems with artificial neural networks
EXTENDING CLASSICAL SURROGATE MODELING TO HIGH DIMENSIONS THROUGH SUPERVISED DIMENSIONALITY REDUCTION: A DATA-DRIVEN APPROACH
Advanced Lectures on Machine Learning
Past, current and future trends and challenges in non-deterministic fracture mechanics: a review

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