Deep energy method in topology optimization applications

Physics informed neural networks for continuum micromechanics

(2022) Alexander Henkes et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems

(2022) Jeremy Yu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A framework based on physics-informed neural networks and extreme learning for the analysis of composite structures

(2022) C.A. Yan et al.   COMPUTERS & STRUCTURES

A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method

(2022) Shahed Rezaei et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A deep learning energy method for hyperelasticity and viscoelasticity

(2022) Diab W. Abueidda et al.   EUROPEAN JOURNAL OF MECHANICS A-SOLIDS

Enhanced physics‐informed neural networks for hyperelasticity

(2022) Diab W. Abueidda et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

Recurrent neural networks (RNNs) learn the constitutive law of viscoelasticity

(2021) Guang Chen   COMPUTATIONAL MECHANICS

A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics

(2021) Ehsan Haghighat et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Unsupervised discovery of interpretable hyperelastic constitutive laws

(2021) Moritz Flaschel et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Meshless Physics‐Informed Deep Learning Method for Three‐Dimensional Solid Mechanics

(2021) Diab W. Abueidda et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

AuTO: a framework for Automatic differentiation in Topology Optimization

(2021) Aaditya Chandrasekhar et al.   STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture

(2021) Sina Amini Niaki et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Parametric deep energy approach for elasticity accounting for strain gradient effects

(2021) Vien Minh Nguyen-Thanh et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks

(2021) Sifan Wang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

TONR: An exploration for a novel way combining neural network with topology optimization

(2021) Zeyu Zhang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

The mixed Deep Energy Method for resolving concentration features in finite strain hyperelasticity

(2021) Jan N. Fuhg et al.   JOURNAL OF COMPUTATIONAL PHYSICS

An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications

(2020) E. Samaniego et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

On the Potential of Recurrent Neural Networks For Modeling Path Dependent Plasticity

(2020) Maysam B. Gorji et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Prediction of composite microstructure stress-strain curves using convolutional neural networks

(2020) Charles Yang et al.   MATERIALS & DESIGN

The neural particle method – An updated Lagrangian physics informed neural network for computational fluid dynamics

(2020) Henning Wessels et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Topology optimization of 2D structures with nonlinearities using deep learning

(2020) Diab W. Abueidda et al.   COMPUTERS & STRUCTURES

Rapid prediction and inverse design of distortion behaviors of composite materials using artificial neural networks

(2020) Ling Luo et al.   POLYMERS FOR ADVANCED TECHNOLOGIES

Deep learning for plasticity and thermo-viscoplasticity

(2020) Diab W. Abueidda et al.   INTERNATIONAL JOURNAL OF PLASTICITY

Neural network based constitutive modeling of nonlinear viscoplastic structural response

(2019) Marcus Stoffel et al.   MECHANICS RESEARCH COMMUNICATIONS

Machine learning for composite materials

(2019) Chun-Teh Chen et al.   MRS Communications

Topology optimization of material microstructures using energy-based homogenization method under specified initial material layout

(2019) Yan Zhang et al.   Journal of Mechanical Science and Technology

Application of deep learning neural network to identify collision load conditions based on permanent plastic deformation of shell structures

(2019) Guorong Chen et al.   COMPUTATIONAL MECHANICS

Neural networks for topology optimization

(2019) Ivan Sosnovik et al.   RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING

A deep energy method for finite deformation hyperelasticity

(2019) Vien Minh Nguyen-Thanh et al.   EUROPEAN JOURNAL OF MECHANICS A-SOLIDS

Design of materials using topology optimization and energy-based homogenization approach in Matlab

(2015) Liang Xia et al.   STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

Efficient topology optimization in MATLAB using 88 lines of code

(2010) Erik Andreassen et al.   STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

A critical review of established methods of structural topology optimization

(2008) G. I. N. Rozvany   STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION