Integrated Computational Materials Engineering (ICME)

Advancing Computational and Experimental Methods
Herausgegeben:Ghosh, Somnath; Woodward, Christopher; Przybyla, Craig

• Gebundenes Buch

Produktbeschreibung

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 atdifferent 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.

Produktdetails

• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-40561-8
• 1st ed. 2020
• Seitenzahl: 428
• Erscheinungstermin: 21. März 2020
• Englisch
• Abmessung: 241mm x 160mm x 27mm
• Gewicht: 836g
• ISBN-13: 9783030405618
• ISBN-10: 3030405613
• Artikelnr.: 58469712

Autorenporträt

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.

Inhaltsangabe

Scale Hierarchical Modeling of Ni-based Superalloys: from sub-grain to polycrystalline scales.- Underpinning and benchmarking multi-scale models with micro-tensile and bending experiments.- Discrete network dynamics: From dislocation to polymer chain simulations.- Survey of ICME methods for Polymer Matrix Composites.- Structure-property measurements: Multi-scale experiments for model calibration and validation for PMC.- Computational micromechanics and multi-scale modeling of PMCs.- Determining property-based statistically equivalent representative volume elements or P- SERVE for polymer matrix composites using exterior statistics-based boundary conditions.- Quantification of error and uncertainty in materials characterization.

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Scale Hierarchical Modeling of Ni-based Superalloys: from sub-grain to polycrystalline scales.- Underpinning and benchmarking multi-scale models with micro-tensile and bending experiments.- Discrete network dynamics: From dislocation to polymer chain simulations.- Survey of ICME methods for Polymer Matrix Composites.- Structure-property measurements: Multi-scale experiments for model calibration and validation for PMC.- Computational micromechanics and multi-scale modeling of PMCs.- Determining property-based statistically equivalent representative volume elements or P- SERVE for polymer matrix composites using exterior statistics-based boundary conditions.- Quantification of error and uncertainty in materials characterization.