A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks

A transfer learning object detection model for defects detection in X-ray images of spacecraft composite structures

(2022) Yanfeng Gong et al.   COMPOSITE STRUCTURES

Machine learning for accelerating the design process of double-double composite structures

(2022) Zilan Zhang et al.   COMPOSITE STRUCTURES

Graph neural networks for simulating crack coalescence and propagation in brittle materials

(2022) Roberto Perera et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Molecular dynamics inferred transfer learning models for finite‐strain hyperelasticity of monoclinic crystals: Sobolev training and validations against physical constraints

(2022) Nikolaos N. Vlassis et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

Transfer learning using attentions across atomic systems with graph neural networks (TAAG)

(2022) Adeesh Kolluru et al.   JOURNAL OF CHEMICAL PHYSICS

3D-structure-attention graph neural network for crystals and materials

(2022) Xuanjie Lin et al.   MOLECULAR PHYSICS

Machine-learning convex and texture-dependent macroscopic yield from crystal plasticity simulations

(2022) Jan N. Fuhg et al.   Materialia

Graph neural network predictions of metal organic framework CO2 adsorption properties

(2022) Kamal Choudhary et al.   COMPUTATIONAL MATERIALS SCIENCE

Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties

(2022) T. Kadeethum et al.   COMPUTERS & GEOSCIENCES

Prediction of fatigue crack growth under variable amplitude loading by artificial neural network-based Lagrange interpolation

(2022) Lin Zhang et al.   MECHANICS OF MATERIALS

Thermodynamically consistent Recurrent Neural Networks to predict non linear behaviors of dissipative materials subjected to non-proportional loading paths

(2022) Aymen Danoun et al.   MECHANICS OF MATERIALS

Transfer learning for materials informatics using crystal graph convolutional neural network

(2021) Joohwi Lee et al.   COMPUTATIONAL MATERIALS SCIENCE

Deep learning model to predict complex stress and strain fields in hierarchical composites

(2021) Zhenze Yang et al.   Science Advances

Deep learning model to predict fracture mechanisms of graphene

(2021) Andrew J. Lew et al.   npj 2D Materials and Applications

Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images

(2021) Roberto Perera et al.   COMPUTATIONAL MATERIALS SCIENCE

A polygonal FEM and continuum damage mechanics based framework for stochastic simulation of fatigue life scatter in duplex microstructure titanium alloys

(2021) Deepak Sharma et al.   MECHANICS OF MATERIALS

Knowledge extraction and transfer in data-driven fracture mechanics

(2021) Xing Liu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Transfer Learning Based Semantic Segmentation for 3D Object Detection from Point Cloud

(2021) Muhammad Imad et al.   SENSORS

Scalable Graphene Defect Prediction Using Transferable Learning

(2021) Bowen Zheng et al.   Nanomaterials

Deep learning framework for material design space exploration using active transfer learning and data augmentation

(2021) Yongtae Kim et al.   npj Computational Materials

Surrogate modeling of elasto-plastic problems via long short-term memory neural networks and proper orthogonal decomposition

(2021) Sunyoung Im et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Predicting the multiaxial stress-strain behavior of polyethylene terephthalate (PET) at different strain rates and temperatures above Tg by using an Artificial Neural Network

(2021) Fei Teng et al.   MECHANICS OF MATERIALS

Combining crystal graphs and domain knowledge in machine learning to predict metal-organic frameworks performance in methane adsorption

(2021) Ruihan Wang et al.   MICROPOROUS AND MESOPOROUS MATERIALS

A graph-based workflow for extracting grain-scale toughness from meso-scale experiments

(2021) Stylianos Tsopanidis et al.   MATERIALS & DESIGN

AtomSets as a hierarchical transfer learning framework for small and large materials datasets

(2021) Chi Chen et al.   npj Computational Materials

Experimental crack identification of API X70 steel pipeline using improved Artificial Neural Networks based on Whale Optimization Algorithm

(2021) A. Ouladbrahim et al.   MECHANICS OF MATERIALS

A machine learning approach to fracture mechanics problems

(2020) Xing Liu et al.   ACTA MATERIALIA

Accelerating Auxetic Metamaterial Design with Deep Learning

(2020) Jackson K. Wilt et al.   ADVANCED ENGINEERING MATERIALS

SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials

(2020) Yousef Heider et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Machine learning predictions on fracture toughness of multiscale bio-nano-composites

(2020) Vahid Daghigh et al.   JOURNAL OF REINFORCED PLASTICS AND COMPOSITES

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

(2020) Charles Yang et al.   MATERIALS & DESIGN

A machine learning based approach for determining the stress-strain relation of grey cast iron from nanoindentation

(2020) Jian Weng et al.   MECHANICS OF MATERIALS

Simplified ResNet approach for data driven prediction of microstructure-fatigue relationship

(2020) Christian Gebhardt et al.   MECHANICS OF MATERIALS

Continuous fracture of soft tissue under high-speed waterjet impact and its quantification method

(2020) Chao Cao et al.   MECHANICS OF MATERIALS

Investigating the impact of data normalization on classification performance

(2019) Dalwinder Singh et al.   APPLIED SOFT COMPUTING

Constitutive modeling of plastic deformation behavior of open-cell foam structures using neural networks

(2019) Christoph Settgast et al.   MECHANICS OF MATERIALS

Automatic defects detection in CFRP thermograms, using convolutional neural networks and transfer learning

(2019) Numan Saeed et al.   INFRARED PHYSICS & TECHNOLOGY

Deep learning predicts path-dependent plasticity

(2019) M. Mozaffar et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Predictive modeling of dynamic fracture growth in brittle materials with machine learning

(2018) Bryan A. Moore et al.   COMPUTATIONAL MATERIALS SCIENCE

Minimum energy multiple crack propagation. Part III: XFEM computer implementation and applications

(2018) Danas Sutula et al.   ENGINEERING FRACTURE MECHANICS

Minimum energy multiple crack propagation. Part-II: Discrete solution with XFEM

(2018) Danas Sutula et al.   ENGINEERING FRACTURE MECHANICS

Minimum energy multiple crack propagation. Part I: Theory and state of the art review

(2018) Danas Sutula et al.   ENGINEERING FRACTURE MECHANICS

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

(2018) Tian Xie et al.   PHYSICAL REVIEW LETTERS

Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment

(2018) Grace X. Gu et al.   Materials Horizons

Reduced-order modeling through machine learning and graph-theoretic approaches for brittle fracture applications

(2018) Abigail Hunter et al.   COMPUTATIONAL MATERIALS SCIENCE

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

(2016) Hoo-Chang Shin et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Transfer Learning for Visual Categorization: A Survey

(2015) Ling Shao et al.   IEEE Transactions on Neural Networks and Learning Systems