Fatigue life prediction of the FCC-based multi-principal element alloys via domain knowledge-based machine learning

Author:

Xiao Lu,Wang Gang,Long Weimin,Liaw Peter K.,Ren Jingli

Funder

National Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference46 articles.

1. Advances in fatigue life modeling: A review;Kamal;Renew Sustain Energy Rev,2018

2. Machine learning-enabled high-entropy alloy discovery;Rao;Science,2022

3. Efficient machine-learning model for fast assessment of elastic properties of high-entropy alloys;Vazquez;Acta Mater,2022

4. Short-to-medium range structure and glass-forming ability in metallic glasses;Wei;Phys Rev Mater,2022

5. Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach;Yang;Int J Fatigue,2023

Cited by 6 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

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