Physics-informed machine learning model for computational fracture of quasi-brittle materials without labelled data

Efficient training of physics‐informed neural networks via importance sampling

(2021) Mohammad Amin Nabian et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

A physics-guided machine learning model for two-dimensional structures based on ordinary state-based peridynamics

(2021) Cong Tien Nguyen et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

Energy minimization versus criteria-based methods in discrete cohesive fracture simulations

(2021) M. R. Hirmand et al.   COMPUTATIONAL MECHANICS

A novel deep learning-based modelling strategy from image of particles to mechanical properties for granular materials with CNN and BiLSTM

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

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

A novel dynamic stability analysis method for jointed rock slopes based on block-interface interaction

(2021) Lin’gang Gao et al.   COMPUTERS AND GEOTECHNICS

Physics-Informed Deep Learning for Computational Elastodynamics without Labeled Data

(2021) Chengping Rao et al.   JOURNAL OF ENGINEERING MECHANICS

Mapped phase field method for brittle fracture

(2021) Tianju Xue 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

Learning nonlocal constitutive models with neural networks

(2021) Xu-Hui Zhou et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method

(2021) Theron Guo et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

(2020) Maziar Raissi et al.   SCIENCE

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

A variable parameters damage model for concrete

(2020) Huijun Qi et al.   ENGINEERING FRACTURE MECHANICS

Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems

(2020) Ameya D. Jagtap et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Physics-guided convolutional neural network (PhyCNN) for data-driven seismic response modeling

(2020) Ruiyang Zhang et al.   ENGINEERING STRUCTURES

Adaptive fourth-order phase field analysis using deep energy minimization

(2020) Somdatta Goswami et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

A self-adaptive deep learning algorithm for accelerating multi-component flash calculation

(2020) Tao Zhang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Transfer learning based multi-fidelity physics informed deep neural network

(2020) Souvik Chakraborty   JOURNAL OF COMPUTATIONAL PHYSICS

PhyGeoNet: Physics-informed geometry-adaptive convolutional neural networks for solving parameterized steady-state PDEs on irregular domain

(2020) Han Gao et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Thermodynamics-based Artificial Neural Networks for constitutive modeling

(2020) Filippo Masi et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

(2019) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Adversarial uncertainty quantification in physics-informed neural networks

(2019) Yibo Yang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems

(2019) Dongkun Zhang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A deep energy method for finite deformation hyperelasticity

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

Transfer learning enhanced physics informed neural network for phase-field modeling of fracture

(2019) Somdatta Goswami et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

DGM: A deep learning algorithm for solving partial differential equations

(2018) Justin Sirignano et al.   JOURNAL OF COMPUTATIONAL PHYSICS