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This book provides readers with an incisive look at cutting-edge peridynamic modeling methods, numerical techniques, their applications, and potential future directions for the field. It starts with an introductory chapter authored by Stewart Silling, who originally developed peridynamics. It then looks at new concepts in the field, with chapters covering dual-horizon peridynamics, peridynamics for axisymmetric analysis, beam and plate models in peridynamics, coupled peridynamics and XFEM, peridynamics for dynamic fracture modeling, and more. From there, it segues into coverage of cutting-edge applications of peridynamics, exploring its biological applications, modeling at the nanoscale, peridynamics for composites delamination and damage in ceramics, and more, concluding with a chapter on the application of artificial intelligence and machine learning in peridynamics.
This book presents the peridynamic theory, which provides the capability for improved modeling of progressive failure in materials and structures, and paves the way for addressing multi-physics and multi-scale problems. The book provides students and researchers with a theoretical and practical knowledge of the peridynamic theory and the skills required to analyze engineering problems. The text may be used in courses such as Multi-physics and Multi-scale Analysis, Nonlocal Computational Mechanics, and Computational Damage Prediction. Sample algorithms for the solution of benchmark problems are available so that the reader can modify these algorithms, and develop their own solution algorithms for specific problems. Students and researchers will find this book an essential and invaluable reference on the topic.
This book presents the peridynamic theory, which provides the capability for improved modeling of progressive failure in materials and structures, and paves the way for addressing multi-physics and multi-scale problems. The book provides students and researchers with a theoretical and practical knowledge of the peridynamic theory and the skills required to analyze engineering problems. The text may be used in courses such as Multi-physics and Multi-scale Analysis, Nonlocal Computational Mechanics, and Computational Damage Prediction. Sample algorithms for the solution of benchmark problems are available so that the reader can modify these algorithms, and develop their own solution algorithms for specific problems. Students and researchers will find this book an essential and invaluable reference on the topic.
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