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Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture
Deformation, Fracture, and Fatigue
Elsevier Science & Technology
ISBN 978-0-443-44615-3
Standardpreis
Bibliografische Daten
Buch. Softcover
2026
Format (B x L): 15,2 x 22,9 cm
Gewicht: 450
Verlag: Elsevier Science & Technology
ISBN: 978-0-443-44615-3
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.
Autorinnen und Autoren
Kundeninformationen
- Provides a systematic summary of machine learning methods applied to solid deformation, fatigue and fracture analysis - Fills a clear gap in the literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanics - Introduces the application of physics-informed machine learning in multiaxial fatigue life prediction - Introduces the application of physics-informed machine learning in predicting the fatigue life of additively manufactured metallic metals - Includes numerous practical examples and case studies and draws on the authors’ extensive experience in multiscale simulation of solid materials and fatigue life prediction
Produktsicherheit
Hersteller
Libri GmbH
Europaallee 1
36244 Bad Hersfeld, DE
gpsr@libri.de
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