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Machine learning in the analysis of solid deformation, fatigue and fracture
Paperback
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- Book Synopsis
- 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.
- About The Author
- 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
- Product Details
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- ISBN
- 9780443446153
- Format
- Paperback
- Publisher
- Elsevier, (23 January 2026)
- Number of Pages
- 350
- Weight
- 450 grams
- Language
- English
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