Integrated Computational Materials Engineering ICME: Advancing Computational and Experimental Methods - Rilegato

Rilegato

ISBN 10: 3030405613 ISBN 13: 9783030405618

Casa editrice: Springer Nature, 2020

Riassunto

?This book introduces research advances in Integrated Computational Materials Engineering (ICME) that have taken place under the aegis of the AFOSR/AFRL sponsored Center of Excellence on Integrated Materials Modeling (CEIMM) at Johns Hopkins University. Its author team consists of leading researchers in ICME from prominent academic institutions and the Air Force Research Laboratory. The book examines state-of-the-art advances in physics-based, multi-scale, computational-experimental methods and models for structural materials like polymer-matrix composites and metallic alloys. The book emphasizes Ni-based superalloys and epoxy matrix carbon-fiber composites and encompasses atomistic scales, meso-scales of coarse-grained models and discrete dislocations, and micro-scales of poly-phase and polycrystalline microstructures. Other critical phenomena investigated include the relationship between microstructural morphology, crystallography, and mechanisms to the material response at different scales; methods of identifying representative volume elements using microstructure and material characterization, and robust deterministic and probabilistic modeling of deformation and damage. 

Encompassing a slate of topics that enable readers to comprehend and approach ICME-related issues involved in predicting material performance and failure, the book is ideal for mechanical, civil, and aerospace engineers, and materials scientists, in in academic, government, and industrial laboratories.

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Informazioni sull'autore

Dr. Somnath Ghosh is Michael G. Callas Chair Professor in the Departments of Civil, Mechanical and Materials Science & Engineering, Johns Hopkins University and Director of the Center for Integrated Structure-Materials Modeling and Simulations (CISMMS).

Dr. Christopher Woodward is Principal Materials Research Engineer within the Materials and Manufacturing Directorate, Air Force Research Laboratory/RX, Wright Patterson Air Force Base.

Dr. Craig Przybyla is Senior Materials Engineer & Research Team Leader within the Air Force Research Laboratory/RX, Wright Patterson Air Force Base, OH.

Dalla quarta di copertina

This book introduces research advances in Integrated Computational Materials Engineering (ICME) that have taken place under the aegis of the Center of Excellence on Integrated Materials Modeling (CEIMM). Its author team consists of leading researchers in ICME from prominent academic institutions and the Air Force Research Laboratory. The book examines state-of-the-art advances in physics-based, multi-scale, computational-experimental methods and models for structural materials like polymer-matrix composites and metallic alloys. The book emphasizes Ni-based superalloys and epoxy matrix carbon-fiber composites and encompasses atomistic scales, meso-scales of coarse-grained models and discrete dislocations, and micro-scales of poly-phase and polycrystalline microstructures. Other critical phenomena investigated include the relationship between microstructural morphology, crystallography, and mechanisms to the material response at different scales; methods of identifying representative volume elements using microstructure and material characterization, and robust deterministic and probabilistic modeling of deformation and damage. 

Encompassing a slate of topics that enable readers to comprehend and approach ICME-related issues involved in predicting material performance and failure, the book is ideal for mechanical, civil, and aerospace engineers, and materials scientists, in in academic, government, and industrial laboratories.

• Presents data acquisition, characterization, and image-based virtual models across multiple scales;
• Adopts a physics-based approach to multi-scale model development for material performance and failure response;
• Describes experimental methods for constitutive models, response functions, and failure processes;
• Maximizes reader understanding with probabilistic modeling and uncertainty quantification.

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 3030405613
• ISBN 13: 9783030405618
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 428
• Redattore: Ghosh Somnath, Woodward Christopher, Przybyla Craig
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Germania