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Deep learning for topology optimization of 2D metamaterials

Materials & design, 2020-11, Vol.196, p.109098, Article 109098

2020

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Evaluation of parallel direct sparse linear solvers in electromagnetic geophysical problems

Computers & geosciences, 2016-04, Vol.89, p.79-87

2016

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Deep Learning Sequence Methods in Multiphysics Modeling of Steel Solidification

Metals (Basel ), 2021-03, Vol.11 (3), p.494

2021

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Topology optimization for three‐dimensional elastoplastic architected materials using a path‐dependent adjoint method

International journal for numerical methods in engineering, 2021-04, Vol.122 (8), p.1889-1910

2021

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Data-driven and physics-informed deep learning operators for solution of heat conduction equation with parametric heat source

International journal of heat and mass transfer, 2023-04, Vol.203, p.123809, Article 123809

2023

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Thermo-mechanical models of steel solidification based on two elastic visco-plastic constitutive laws

Journal of materials processing technology, 2008-02, Vol.197 (1), p.408-418

2008

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Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure

Journal of big data, 2020-10, Vol.7 (1), p.1-12, Article 88

2020

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Forecasting mechanical failure and the 26 June 2018 eruption of Sierra Negra Volcano, Galápagos, Ecuador

Science advances, 2022-06, Vol.8 (22), p.eabm4261-eabm4261

2022

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Designing a TPMS metamaterial via deep learning and topology optimization

Frontiers in mechanical engineering, 2024-08, Vol.10

2024

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Explicit coupled thermo-mechanical finite element model of steel solidification

International journal for numerical methods in engineering, 2009-04, Vol.78 (1), p.1-31

2009

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Meshless physics‐informed deep learning method for three‐dimensional solid mechanics

International journal for numerical methods in engineering, 2021-12, Vol.122 (23), p.7182-7201

2021

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Deep learning for plasticity and thermo-viscoplasticity

International journal of plasticity, 2021-01, Vol.136, p.102852, Article 102852

2021

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Topology optimization of 2D structures with nonlinearities using deep learning

Computers & structures, 2020-09, Vol.237, p.106283, Article 106283

2020

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On the use of graph neural networks and shape‐function‐based gradient computation in the deep energy method

International journal for numerical methods in engineering, 2023-02, Vol.124 (4), p.864-879

2023

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Geom-DeepONet: A point-cloud-based deep operator network for field predictions on 3D parameterized geometries

Computer methods in applied mechanics and engineering, 2024-09, Vol.429, p.117130, Article 117130

2024

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Influence of pore structure on the strength behavior of particle- and fiber-reinforced metakaolin-based geopolymer composites

Cement & concrete composites, 2019-11, Vol.104, p.103361, Article 103361

2019

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Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads

Computer methods in applied mechanics and engineering, 2023-10, Vol.415, p.116277, Article 116277

2023

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A deep learning energy-based method for classical elastoplasticity

International journal of plasticity, 2023-03, Vol.162, p.103531, Article 103531

2023

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Sparse matrix factorization in the implicit finite element method on petascale architecture

Computer methods in applied mechanics and engineering, 2016-04, Vol.302, p.281-292

2016

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Additional Cover

International journal for numerical methods in engineering, 2023-02, Vol.124 (4), p.ii-ii

2023

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Fracture analysis of multi-osteon cortical bone using XFEM

Computational mechanics, 2018-08, Vol.62 (2), p.171-184

2018

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Enhanced physics‐informed neural networks for hyperelasticity

International journal for numerical methods in engineering, 2023-04, Vol.124 (7), p.1585-1601

2023

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Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene

The journal of physical chemistry. B, 2024-02, Vol.128 (5), p.1220-1230

2024

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Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads

Engineering applications of artificial intelligence, 2024-01, Vol.127, p.107258, Article 107258

2024

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Deep energy method in topology optimization applications

Acta mechanica, 2023-04, Vol.234 (4), p.1365-1379

2023

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Deep learning for topology optimization of 2D metamaterials

Evaluation of parallel direct sparse linear solvers in electromagnetic geophysical problems

Deep Learning Sequence Methods in Multiphysics Modeling of Steel Solidification

Topology optimization for three‐dimensional elastoplastic architected materials using a path‐dependent adjoint method

Data-driven and physics-informed deep learning operators for solution of heat conduction equation with parametric heat source

Thermo-mechanical models of steel solidification based on two elastic visco-plastic constitutive laws

Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure

Forecasting mechanical failure and the 26 June 2018 eruption of Sierra Negra Volcano, Galápagos, Ecuador

Designing a TPMS metamaterial via deep learning and topology optimization

Explicit coupled thermo-mechanical finite element model of steel solidification

Meshless physics‐informed deep learning method for three‐dimensional solid mechanics

Deep learning for plasticity and thermo-viscoplasticity

Topology optimization of 2D structures with nonlinearities using deep learning

On the use of graph neural networks and shape‐function‐based gradient computation in the deep energy method

Geom-DeepONet: A point-cloud-based deep operator network for field predictions on 3D parameterized geometries

Influence of pore structure on the strength behavior of particle- and fiber-reinforced metakaolin-based geopolymer composites

Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads

A deep learning energy-based method for classical elastoplasticity

Sparse matrix factorization in the implicit finite element method on petascale architecture

Additional Cover

Fracture analysis of multi-osteon cortical bone using XFEM

Enhanced physics‐informed neural networks for hyperelasticity

Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene

Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads

Deep energy method in topology optimization applications

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