Explore constitutive modeling from fundamental theory through cutting-edge AI applications
Constitutive Models of Solid Materials: From Mechanical Principles to Engineering Applications provides researchers and engineers with comprehensive methods to predict material responses under complex loading conditions. Written by internationally recognized experts in materials mechanics and computational methods, this systematic treatment connects rigorous theoretical foundations to practical engineering applications, demonstrating the accurate modeling of material behavior across multiple scales.
The text progresses methodically from tensor analysis and continuum mechanics through elasticity, plasticity, and damage mechanics to micromechanics and numerical implementation strategies. Coverage extends to artificial intelligence integration in constitutive research, featuring Physics-Informed Neural Networks for constitutive parameter prediction. Four detailed case studies examine sintered nano-silver, high-strength steel, solder alloys, rock modeling, and high-temperature concrete performance.
The book offers:
This comprehensive resource serves materials scientists, mechanical engineers, civil engineers, aerospace professionals, and graduate students seeking to master constitutive modeling. By combining rigorous mathematical formulation with computational methods and practical case studies, it provides an essential foundation for advanced materials research and engineering practice.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Yao Yao is a Professor researching mechanical properties of materials and disaster prevention of engineering structures under extreme loads. His research is also focused on engineering material construction, fatigue, and damage under multi-physical fields.
Hu Fang, PhD, develops high-temperature damage constitutive models for solid materials. His research is also focused on material fracture and damage theory, as well as the research on the mechanical properties of composite material interfaces.
Hongcun Guo, PhD, researches the mechanical behavior of green building materials and the high-temperature mechanical properties of ultra-high performance concrete.
Tao Zeng, PhD, is a council member of the Shaanxi Society for Rock Mechanics and Engineering. His research is focused on underground engineering, including rock mechanics and the development of micromechanical models of rock materials.
Xu He, PhD, specializes in multi-scale modeling of mechanical properties, constitute behavior, and failure processes of advanced materials under extreme loads.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. Explore constitutive modeling from fundamental theory through cutting-edge AI applications Constitutive Models of Solid Materials: From Mechanical Principles to Engineering Applications provides researchers and engineers with comprehensive methods to predict material responses under complex loading conditions. Written by internationally recognized experts in materials mechanics and computational methods, this systematic treatment connects rigorous theoretical foundations to practical engineering applications, demonstrating the accurate modeling of material behavior across multiple scales. The text progresses methodically from tensor analysis and continuum mechanics through elasticity, plasticity, and damage mechanics to micromechanics and numerical implementation strategies. Coverage extends to artificial intelligence integration in constitutive research, featuring Physics-Informed Neural Networks for constitutive parameter prediction. Four detailed case studies examine sintered nano-silver, high-strength steel, solder alloys, rock modeling, and high-temperature concrete performance. The book offers: Comprehensive coverage from mathematical foundations through elastoplastic theory, damage mechanics, and micromechanics to AI-enhanced modeling approachesNumerical implementation strategies including time-stepping schemes, Newton-Raphson iteration, and elastic predictor plastic corrector methods for simulationsDetailed case studies on sintered nano-silver, high-strength steels, solder alloys, rocks, and concrete under extreme conditionsIntegration of machine learning including Artificial Neural Networks, XGBoost, and Physics-Informed Neural Networks with example programsMultiscale frameworks combining Eshelbys theory, Hills method, and homogenization techniques linking microstructure to macroscopic behaviorThis comprehensive resource serves materials scientists, mechanical engineers, civil engineers, aerospace professionals, and graduate students seeking to master constitutive modeling. By combining rigorous mathematical formulation with computational methods and practical case studies, it provides an essential foundation for advanced materials research and engineering practice. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783527355532
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Hardcover. Etat : new. Hardcover. Explore constitutive modeling from fundamental theory through cutting-edge AI applications Constitutive Models of Solid Materials: From Mechanical Principles to Engineering Applications provides researchers and engineers with comprehensive methods to predict material responses under complex loading conditions. Written by internationally recognized experts in materials mechanics and computational methods, this systematic treatment connects rigorous theoretical foundations to practical engineering applications, demonstrating the accurate modeling of material behavior across multiple scales. The text progresses methodically from tensor analysis and continuum mechanics through elasticity, plasticity, and damage mechanics to micromechanics and numerical implementation strategies. Coverage extends to artificial intelligence integration in constitutive research, featuring Physics-Informed Neural Networks for constitutive parameter prediction. Four detailed case studies examine sintered nano-silver, high-strength steel, solder alloys, rock modeling, and high-temperature concrete performance. The book offers: Comprehensive coverage from mathematical foundations through elastoplastic theory, damage mechanics, and micromechanics to AI-enhanced modeling approachesNumerical implementation strategies including time-stepping schemes, Newton-Raphson iteration, and elastic predictor plastic corrector methods for simulationsDetailed case studies on sintered nano-silver, high-strength steels, solder alloys, rocks, and concrete under extreme conditionsIntegration of machine learning including Artificial Neural Networks, XGBoost, and Physics-Informed Neural Networks with example programsMultiscale frameworks combining Eshelbys theory, Hills method, and homogenization techniques linking microstructure to macroscopic behaviorThis comprehensive resource serves materials scientists, mechanical engineers, civil engineers, aerospace professionals, and graduate students seeking to master constitutive modeling. By combining rigorous mathematical formulation with computational methods and practical case studies, it provides an essential foundation for advanced materials research and engineering practice. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783527355532
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Hardcover. Etat : new. Hardcover. Explore constitutive modeling from fundamental theory through cutting-edge AI applications Constitutive Models of Solid Materials: From Mechanical Principles to Engineering Applications provides researchers and engineers with comprehensive methods to predict material responses under complex loading conditions. Written by internationally recognized experts in materials mechanics and computational methods, this systematic treatment connects rigorous theoretical foundations to practical engineering applications, demonstrating the accurate modeling of material behavior across multiple scales. The text progresses methodically from tensor analysis and continuum mechanics through elasticity, plasticity, and damage mechanics to micromechanics and numerical implementation strategies. Coverage extends to artificial intelligence integration in constitutive research, featuring Physics-Informed Neural Networks for constitutive parameter prediction. Four detailed case studies examine sintered nano-silver, high-strength steel, solder alloys, rock modeling, and high-temperature concrete performance. The book offers: Comprehensive coverage from mathematical foundations through elastoplastic theory, damage mechanics, and micromechanics to AI-enhanced modeling approachesNumerical implementation strategies including time-stepping schemes, Newton-Raphson iteration, and elastic predictor plastic corrector methods for simulationsDetailed case studies on sintered nano-silver, high-strength steels, solder alloys, rocks, and concrete under extreme conditionsIntegration of machine learning including Artificial Neural Networks, XGBoost, and Physics-Informed Neural Networks with example programsMultiscale frameworks combining Eshelbys theory, Hills method, and homogenization techniques linking microstructure to macroscopic behaviorThis comprehensive resource serves materials scientists, mechanical engineers, civil engineers, aerospace professionals, and graduate students seeking to master constitutive modeling. By combining rigorous mathematical formulation with computational methods and practical case studies, it provides an essential foundation for advanced materials research and engineering practice. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9783527355532
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Buch. Etat : Neu. Neuware - Covers a wide range of essential concepts and skills, from continuum mechanics to advanced constitutive modeling, addressing the needs of both academics and professionals. N° de réf. du vendeur 9783527355532
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