Fatigue failure of engineering materials and structures has long been a great challenge for structural integrity, reliability and safety in mechanical, civil and aerospace engineering. These failure mechanisms and their modeling are critical concerns for managing aging structures, and directly affect sustainability across society.
In this context, the fundamental theories and methods of fatigue failure of engineering materials and structures are discussed in detail. Fatigue damage accumulation, crack initiation and crack growth analysis are presented from materials to structures, deterministic to probabilistic fatigue, physics to data science, uniaxial to multiaxial fatigue, and extremely low cycle fatigue to very high cycle fatigue. The focus is on mechanical understanding and risk management for design, maintenance, and operation.
Some recent advancements include fatigue of additive manufactured (AM) metals and advanced materials, which could potentially transform fatigue analysis and offer new perspectives on fatigue failure mechanisms and reliability design. Both experimental supporting evidence and simulation benefits are demonstrated. It integrates recent developments in artificial intelligence with fatigue in AM metals and advanced materials. It provides case studies, and future research challenges for the fusion of fatigue physics modeling with data analytics, for graduate students and advanced practitioners.
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Qingyuan Wang is a Professor and the President of Chengdu University, China and a Professor at Sichuan University, China as well as a fellow of the International Association of Advanced Materials.
Shun-Peng Zhu is Professor at University of Electronic Science and Technology of China.
José Correia is a Researcher at the University of Porto, Portugal.
Abílio de Jesus is an Associate Professor at the University of Porto, Portugal.
Grzegorz Lesiuk is a Professor at the Wroclaw University of Technology in Poland.
Key theories and methods of fatigue failure are discussed with fatigue damage accumulation, crack initiation and crack growth analysis. The focus is on mechanical understanding and risk management for design, maintenance, and operation, plus fatigue of additive manufactured metals and advanced materials, with data analytics and AI.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Qingyuan Wang is a Professor and the President of Chengdu University, China and a Professor at Sichuan University, China as well as a fellow of the International Association of Advanced Materials.Shun-Peng Zhu is Professor at University of Electro. Bestandsnummer des Verkäufers 1962288889
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Hardback. Zustand: New. Fatigue failure of engineering materials and structures has long been a great challenge for structural integrity, reliability and safety in mechanical, civil and aerospace engineering. These failure mechanisms and their modeling are critical concerns for managing aging structures, and directly affect sustainability across society.In this context, the fundamental theories and methods of fatigue failure of engineering materials and structures are discussed in detail. Fatigue damage accumulation, crack initiation and crack growth analysis are presented from materials to structures, deterministic to probabilistic fatigue, physics to data science, uniaxial to multiaxial fatigue, and extremely low cycle fatigue to very high cycle fatigue. The focus is on mechanical understanding and risk management for design, maintenance, and operation.Some recent advancements include fatigue of additive manufactured (AM) metals and advanced materials, which could potentially transform fatigue analysis and offer new perspectives on fatigue failure mechanisms and reliability design. Both experimental supporting evidence and simulation benefits are demonstrated. It integrates recent developments in artificial intelligence with fatigue in AM metals and advanced materials. It provides case studies, and future research challenges for the fusion of fatigue physics modeling with data analytics, for graduate students and advanced practitioners. Bestandsnummer des Verkäufers LU-9781032497556
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