I-FENN with temporal convolutional networks: expediting the load-history analysis of non-local gradient damage propagation (Q6497179)

scientific article; zbMATH DE number 7842822

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English	I-FENN with temporal convolutional networks: expediting the load-history analysis of non-local gradient damage propagation	scientific article; zbMATH DE number 7842822

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instance of

scholarly article

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title

I-FENN with temporal convolutional networks: expediting the load-history analysis of non-local gradient damage propagation (English)

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Computer Methods in Applied Mechanics and Engineering

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publication date

6 May 2024

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zbMATH Keywords

IFENN

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non-local damage

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neural networks

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finite element analysis

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multi-physics

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scientific computing

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MaRDI profile type

MaRDI publication profile

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cites work

Integrated finite element neural network (I-FENN) for non-local continuum damage mechanics

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Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance

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Dual length scale non-local model to represent damage and transport in porous media

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Virtual element method for phase field modeling of dynamic fracture

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Maximum principle and uniform convergence for the finite element method

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Data-driven computational mechanics

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Data-driven fracture mechanics

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Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training

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A machine learning based plasticity model using proper orthogonal decomposition

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Geometric deep learning for computational mechanics. I: Anisotropic hyperelasticity

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nPINNs: nonlocal physics-informed neural networks for a parametrized nonlocal universal Laplacian operator. Algorithms and applications

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A nonlocal physics-informed deep learning framework using the peridynamic differential operator

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Machine learning of nonlocal micro-structural defect evolutions in crystalline materials

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Stochastic nonlocal damage analysis by a machine learning approach

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Computational Mechanics with Neural Networks

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On physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling

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Estimates on the generalization error of physics-informed neural networks for approximating a class of inverse problems for PDEs

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Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks

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Hybrid FEM-NN models: combining artificial neural networks with the finite element method

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Recurrent neural networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step

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Strain-based transient-gradient damage model for failure analyses

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Gradient damage \textit{vs} phase-field approaches for fracture: similarities and differences

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GRADIENT ENHANCED DAMAGE FOR QUASI-BRITTLE MATERIALS

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A line search assisted monolithic approach for phase-field computing of brittle fracture

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A faster modified Newton-Raphson iteration

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A survey on modern trainable activation functions

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Q4558473

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Q4633077

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On the limited memory BFGS method for large scale optimization

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A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation

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Identifiers

DOI

10.1016/j.cma.2024.116940

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:6497179