Guozheng Kang, Qianhua Kan, Xu Zhang, Ya-Nan Hu, Xiangyu Li

Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture

• Broschiertes Buch

Produktbeschreibung

Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture fills a clear gap in literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanics. The book’s focus on complex mechanisms and coupling phenomena, discussed with practical examples, makes it a valuable resource for advanced researchers. Practical examples and case studies enable readers to understand both the underlying engineering problems and the application of machine learning methods to enhance fatigue life prediction analysis for solid materials and structures.

Produktdetails

• Verlag: Elsevier Science
• Seitenzahl: 350
• Erscheinungstermin: 1. Januar 2026
• Englisch
• Gewicht: 450g
• ISBN-13: 9780443446153
• ISBN-10: 0443446156
• Artikelnr.: 74957402

Autorenporträt

Guozheng Kang is Chair and Professor of Mechanics at Southwest Jiaotong University, China. He is also vice president of Southwest Jiaotong University. His research activities focus on cyclic plasticity and visco-plasticity, fatigue failure and life prediction, low-cycle fatigue, multiaxial fatigue, fretting fatigue, rolling contact fatigue and ratcheting-fatigue interaction for metallic and polymeric materials, as well as the thermo-mechanical fatigue of shape memory alloys. He has been the author/co-author of more than 400 research publications in refereed international journals and conference proceedings

Inhaltsangabe

1. Introduction
2. Introduction to the algorithm and procedure of machine learning methods
3. Machine learning based multiscale plasticity analysis
4. Machine learning based fracture analysis of solid materials
5. Machine learning based fatigue life prediction of solid materials
6. Machine learning based solid structure analyses