{
"item_title" : "Machine Learning in the Analysis of Deformation, Fatigue and Fracture in Solids",
"item_author" : [" Guozheng Kang", "Qianhua Kan", "Xu Zhang "],
"item_description" : "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.",
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Machine Learning in the Analysis of Deformation, Fatigue and Fracture in Solids
Overview
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.
This item is Non-Returnable
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Details
- ISBN-13: 9780443446153
- ISBN-10: 0443446156
- Publisher: Elsevier
- Publish Date: January 2026
- Dimensions: 9.07 x 5.99 x 0.72 inches
- Shipping Weight: 1.25 pounds
- Page Count: 350
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