End-to-end prediction of multimaterial stress fields and fracture patterns using cycle-consistent adversarial and transformer neural networks-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

End-to-end prediction of multimaterial stress fields and fracture patterns using cycle-consistent adversarial and transformer neural networks

Published:2022-12 Issue: Volume:4 Page:100038
ISSN:2667-0992
Container-title:Biomedical Engineering Advances
language:en
Short-container-title:Biomedical Engineering Advances

Author:

Buehler Eric L.,Buehler Markus J.^ORCID

Publisher

Elsevier BV

Subject

General Medicine

Reference60 articles.

1. Data-driven strategies for accelerated materials design;Pollice;Acc. Chem. Res.,2021

2. Computational scale linking in biological protein materials;Buehler,2010

3. Theory of Dislocations;Anderson,2017

4. Applications of digital-image-correlation techniques to experimental mechanics;Chu;Exp. Mech. 1985 253,1985

5. Using physics-informed enhanced super-resolution generative adversarial networks for subfilter modeling in turbulent reactive flows;Bode;Proc. Combust. Inst.,2021

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven integration of synthetic representative volume elements and machine learning for improved microstructure-property linkage and material performance in ceramics;Computational Materials Today;2024-12

2. Virtual rapid prototyping of materials with deep learning: spatiotemporal stress fields prediction in ceramics employing convolutional neural networks and transfer learning;Virtual and Physical Prototyping;2024-09-09

3. Machine learning based framework for rapid forecasting of the crack propagation;Engineering Fracture Mechanics;2024-08

4. Data-driven approach to predict the fatigue properties of ferrous metal materials using the cGAN and machine-learning algorithms;Advances in Manufacturing;2024-06-03

5. Prediction of microstructural-dependent mechanical properties, progressive damage, and stress distribution from X-ray computed tomography scans using a deep learning workflow;Computer Methods in Applied Mechanics and Engineering;2024-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3