Description
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.
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.
- Langue
- en
- Version
- Couverture rigide
- Date de sortie initiale
- 21 mars 2020
- Nombre de pages
- 405
- Illustrations
- Avec illustrations
Personnes impliquées
- Auteur principal
-
Somnath Ghosh
- Deuxième auteur
-
Christopher Woodward
- Rédacteur en chef
-
Somnath Ghosh
- Deuxième rédacteur
-
Christopher Woodward
- Editeur principal
-
Springer Nature Switzerland AG
Informations sur le fabricant
- Nom du fabricant
- Springer Nature Customer Service Center GmbH
- Adresse du fabricant
- Europaplatz 3 | 69115| Heidelberg| DE
- Adresse électronique du fabricant
- ProductSafety@springernature.com
- Informations sur le fabricant
- Les informations du fabricant ne sont actuellement pas disponibles
Autres spécifications
- Hauteur de l’emballage
- 235 mm
- Largeur d’emballage
- 155 mm
- Largeur du produit
- 155 mm
- Livre d‘étude
- Non
- Longueur d’emballage
- 235 mm
- Longueur du produit
- 235 mm
- Poids de l’emballage
- 990 g
- Police de caractères extra large
- Non
- Édition
- 1st ed. 2020
EAN
- EAN
- 9783030405618
Sécurité des produits
- Opérateur économique responsable dans l’UE
-
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Vous trouverez cet article :
- Catégories
-
Science et nature
Technologie et architecture
Chimie industrielle
Génie mécanique
Science en général
Mathématiques pour ingénieurs
Technologie de la céramique et du verre
Science des matériaux
Recherche et information
Tests de matériaux
Informatique
Livres
- Livre, ebook ou livre audio ?
-
Livre
- Disponibilité
-
Disponible à l’adresse suivante
- Langue
-
Anglais
- Type de livre
-
Hardcover
