A multi-algorithm integration machine learning approach for high cycle fatigue prediction of a titanium alloy in aero-engine
Author:
Funder
National Major Science and Technology Projects of China
Publisher
Elsevier BV
Subject
Mechanical Engineering,Mechanics of Materials,General Materials Science
Reference57 articles.
1. Cumulative damage and life prediction models for high-cycle fatigue of metals: a review;Hectors;Metals,2021
2. Fracture mechanics and damage mechanics based fatigue lifetime prediction of adhesively bonded joints subjected to variable amplitude fatigue;Shenoy;Eng Fract Mech,2010
3. Machine learning-based fatigue life prediction of metal materials: Perspectives of physics-informed and data-driven hybrid methods
4. Life prediction method based on damage mechanism for titanium alloy TC4 under multiaxial thermo-mechanical fatigue loading;Li;Eng Fract Mech,2023
5. Machine learning-based predictions of fatigue life and fatigue limit for steels;He;J Mater Sci Technol,2021
Cited by 8 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. A novel nonlinear fatigue cumulative damage model based on machine learning;International Journal of Fatigue;2024-11
2. Evaluating fatigue onset in metallic materials: Problem, current focus and future perspectives;International Journal of Fatigue;2024-11
3. A tensile properties-related fatigue strength predicted machine learning framework for alloys used in aerospace;Engineering Fracture Mechanics;2024-05
4. High cycle fatigue life prediction of titanium alloys based on a novel deep learning approach;International Journal of Fatigue;2024-05
5. Interpretation of fatigue lifetime prediction by machine learning modeling in piston aluminum alloys under different manufacturing and loading conditions;Frattura ed Integrità Strutturale;2024-03-11
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