标题
Deep learning method for predicting the strengths of microcracked brittle materials
作者
关键词
-
出版物
ENGINEERING FRACTURE MECHANICS
Volume 271, Issue -, Pages 108600
出版商
Elsevier BV
发表日期
2022-06-08
DOI
10.1016/j.engfracmech.2022.108600
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Analyses of internal structures and defects in materials using physics-informed neural networks
- (2022) Enrui Zhang et al. Science Advances
- A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials
- (2022) Somdatta Goswami et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- Defect, temperature, and strain effects on lattice heat conductivity of egg-tray graphene
- (2021) Zhihui Sun et al. MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING
- Deep learning-based planar crack damage evaluation using convolutional neural networks
- (2021) X.Y. Long et al. ENGINEERING FRACTURE MECHANICS
- Highly accurate protein structure prediction with AlphaFold
- (2021) John Jumper et al. NATURE
- Computed structures of core eukaryotic protein complexes
- (2021) Ian R. Humphreys et al. SCIENCE
- Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials
- (2020) Joshua L. Lansford et al. Nature Communications
- Predicting the effective mechanical property of heterogeneous materials by image based modeling and deep learning
- (2019) Xiang Li et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- Deep neural network method for predicting the mechanical properties of composites
- (2019) Sang Ye et al. APPLIED PHYSICS LETTERS
- Predictive modeling of dynamic fracture growth in brittle materials with machine learning
- (2018) Bryan A. Moore et al. COMPUTATIONAL MATERIALS SCIENCE
- Insightful classification of crystal structures using deep learning
- (2018) Angelo Ziletti et al. Nature Communications
- Deep Learning for Computer Vision: A Brief Review
- (2018) Athanasios Voulodimos et al. Computational Intelligence and Neuroscience
- A note on the defect sensitivity of brittle solid foams
- (2018) Shaohui Chen et al. ENGINEERING FRACTURE MECHANICS
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
- Effect of defects on fracture strength of graphene sheets
- (2011) M.C. Wang et al. COMPUTATIONAL MATERIALS SCIENCE
- Damage Micromechanics for Constitutive Relations and Failure of Microcracked Quasi-Brittle Materials
- (2010) Xi-Qiao Feng et al. INTERNATIONAL JOURNAL OF DAMAGE MECHANICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now