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Microstructure Sensitive Design for Performance Optimization

Microstructure Sensitive Design for Performance Optimization
  • Author : Brent L. Adams
  • Publsiher : Butterworth-Heinemann
  • Release : 31 December 2012
  • ISBN : 0123972922
  • Pages : 424 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKMicrostructure Sensitive Design for Performance Optimization

Summary:
The accelerating rate at which new materials are appearing, and transforming the engineering world, only serves to emphasize the vast potential for novel material structure and related performance. Microstructure Sensitive Design for Performance Optimization (MSDPO) embodies a new methodology for systematic design of material microstructure to meet the requirements of design in optimal ways. Intended for materials engineers and researchers in industry, government and academia as well as upper level undergraduate and graduate students studying material science and engineering, MSDPO provides a novel mathematical framework that facilitates a rigorous consideration of the material microstructure as a continuous design variable in the field of engineering design. Presents new methods and techniques for analysis and optimum design of materials at the microstructure level Authors' methodology introduces spectral approaches not available in previous texts, such as the incorporation of crystallographic orientation as a variable in the design of engineered components with targeted elastic properties Numerous illustrations and examples throughout the text help readers grasp the concepts


Microstructure Sensitive Design for Performance Optimization

Microstructure Sensitive Design for Performance Optimization
  • Author : Brent L. Adams,Surya R. Kalidindi,David T. Fullwood
  • Publisher : Butterworth-Heinemann
  • Release : 31 December 2012
GET THIS BOOKMicrostructure Sensitive Design for Performance Optimization

The accelerating rate at which new materials are appearing, and transforming the engineering world, only serves to emphasize the vast potential for novel material structure and related performance. Microstructure Sensitive Design for Performance Optimization (MSDPO) embodies a new methodology for systematic design of material microstructure to meet the requirements of design in optimal ways. Intended for materials engineers and researchers in industry, government and academia as well as upper level undergraduate and graduate students studying material science and engineering, MSDPO

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Microstructure-sensitive Design for Performance Optimization

Microstructure-sensitive Design for Performance Optimization
  • Author : Brent L. Adams,Surya Kalidindi,David T. Fullwood
  • Publisher : Butterworth-Heinemann
  • Release : 16 October 2021
GET THIS BOOKMicrostructure-sensitive Design for Performance Optimization

The accelerating rate at which new materials are appearing, and transforming the engineering world, only serves to emphasize the vast potential for novel material structure and related performance. Microstructure Sensitive Design for Performance Optimization (MSDPO) embodies a new methodology for systematic design of material microstructure to meet the requirements of design in optimal ways. Intended for materials engineers and researchers in industry, government and academia as well as upper level undergraduate and graduate students studying material science and engineering, MSDPO

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Hierarchical Materials Informatics

Hierarchical Materials Informatics
  • Author : Surya R. Kalidindi
  • Publisher : Elsevier
  • Release : 06 August 2015
GET THIS BOOKHierarchical Materials Informatics

Custom design, manufacture, and deployment of new high performance materials for advanced technologies is critically dependent on the availability of invertible, high fidelity, structure-property-processing (SPP) linkages. Establishing these linkages presents a major challenge because of the need to cover unimaginably large dimensional spaces. Hierarchical Materials Informatics addresses objective, computationally efficient, mining of large ensembles of experimental and modeling datasets to extract this core materials knowledge. Furthermore, it aims to organize and present this high value knowledge in highly accessible forms

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Proceedings of the 3rd World Congress on Integrated Computational Materials Engineering (ICME)

Proceedings of the 3rd World Congress on Integrated Computational Materials Engineering (ICME)
  • Author : Warren Poole,Steve Christensen,Surya Kalidindi,Alan Luo,Jonathan Madison,Dierk Raabe,Xin Sun
  • Publisher : Springer
  • Release : 05 December 2016
GET THIS BOOKProceedings of the 3rd World Congress on Integrated Computational Materials Engineering (ICME)

This book presents a collection of papers presented at the 3rd World Congress on Integrated Computational Materials Engineering (ICME), a specialty conference organized by The Minerals, Metals & Materials Society (TMS). This meeting convened ICME stakeholders to examine topics relevant to the global advancement of ICME as an engineering discipline. The papers presented in these proceedings are divided into six sections: (1) ICME Applications; (2) ICME Building Blocks; (3) ICME Success Stories and Applications (4) Integration of ICME Building Blocks: Multi-scale Modeling; (5) Modeling, Data and

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Computational Materials System Design

Computational Materials System Design
  • Author : Dongwon Shin,James Saal
  • Publisher : Springer
  • Release : 10 November 2017
GET THIS BOOKComputational Materials System Design

This book provides state-of-the-art computational approaches for accelerating materials discovery, synthesis, and processing using thermodynamics and kinetics. The authors deliver an overview of current practical computational tools for materials design in the field. They describe ways to integrate thermodynamics and kinetics and how the two can supplement each other.

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Engineering Optimization 2014

Engineering Optimization 2014
  • Author : Hélder Rodrigues,José Herskovits,Christóvão Mota Soares,José Miranda Guedes,Aurelio Araujo,João Folgado,Filipa Moleiro,José Aguilar Madeira
  • Publisher : CRC Press
  • Release : 26 September 2014
GET THIS BOOKEngineering Optimization 2014

Modern engineering processes and tasks are highly complex, multi- and interdisciplinary, requiring the cooperative effort of different specialists from engineering, mathematics, computer science and even social sciences. Optimization methodologies are fundamental instruments to tackle this complexity, giving the possibility to unite synergistically team members’ inputs and thus decisively contribute to solving new engineering technological challenges. With this context in mind, the main goal of Engineering Optimization 2014 is to unite engineers, applied mathematicians, computer and other applied scientists working on research,

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Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes

Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes
  • Author : Anand Balu Nellippallil,Janet K. Allen,B. P. Gautham,Amarendra K. Singh,Farrokh Mistree
  • Publisher : Springer Nature
  • Release : 13 June 2020
GET THIS BOOKArchitecting Robust Co-Design of Materials, Products, and Manufacturing Processes

This book explores systems-based, co-design, introducing a “Decision-Based, Co-Design” (DBCD) approach for the co-design of materials, products, and processes. In recent years there have been significant advances in modeling and simulation of material behavior, from the smallest atomic scale to the macro scale. However, the uncertainties associated with these approaches and models across different scales need to be addressed to enable decision-making resulting in designs that are robust, that is, relatively insensitive to uncertainties. An approach that facilitates co-design is

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Multiscale Structural Topology Optimization

Multiscale Structural Topology Optimization
  • Author : Liang Xia
  • Publisher : Elsevier
  • Release : 27 April 2016
GET THIS BOOKMultiscale Structural Topology Optimization

Multiscale Structural Topology Optimization discusses the development of a multiscale design framework for topology optimization of multiscale nonlinear structures. With the intention to alleviate the heavy computational burden of the design framework, the authors present a POD-based adaptive surrogate model for the RVE solutions at the microscopic scale and make a step further towards the design of multiscale elastoviscoplastic structures. Various optimization methods for structural size, shape, and topology designs have been developed and widely employed in engineering applications. Topology

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Information Science for Materials Discovery and Design

Information Science for Materials Discovery and Design
  • Author : Turab Lookman,Francis J. Alexander,Krishna Rajan
  • Publisher : Springer
  • Release : 12 December 2015
GET THIS BOOKInformation Science for Materials Discovery and Design

This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop

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Integrated Design of Multiscale, Multifunctional Materials and Products

Integrated Design of Multiscale, Multifunctional Materials and Products
  • Author : David L. McDowell,Jitesh Panchal,Hae-Jin Choi,Carolyn Seepersad,Janet Allen,Farrokh Mistree
  • Publisher : Butterworth-Heinemann
  • Release : 30 September 2009
GET THIS BOOKIntegrated Design of Multiscale, Multifunctional Materials and Products

Integrated Design of Multiscale, Multifunctional Materials and Products is the first of its type to consider not only design of materials, but concurrent design of materials and products. In other words, materials are not just selected on the basis of properties, but the composition and/or microstructure iw designed to satisfy specific ranged sets of performance requirements. This book presents the motivation for pursuing concurrent design of materials and products, thoroughly discussing the details of multiscale modeling and multilevel robust

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Statistical Methods for Materials Science

Statistical Methods for Materials Science
  • Author : Jeffrey P. Simmons,Lawrence F. Drummy,Charles A. Bouman,Marc De Graef
  • Publisher : CRC Press
  • Release : 13 February 2019
GET THIS BOOKStatistical Methods for Materials Science

Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.

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Handbook of Software Solutions for ICME

Handbook of Software Solutions for ICME
  • Author : Georg J. Schmitz,Ulrich Prahl
  • Publisher : John Wiley & Sons
  • Release : 19 December 2016
GET THIS BOOKHandbook of Software Solutions for ICME

As one of the results of an ambitious project, this handbook provides a well-structured directory of globally available software tools in the area of Integrated Computational Materials Engineering (ICME). The compilation covers models, software tools, and numerical methods allowing describing electronic, atomistic, and mesoscopic phenomena, which in their combination determine the microstructure and the properties of materials. It reaches out to simulations of component manufacture comprising primary shaping, forming, joining, coating, heat treatment, and machining processes. Models and tools addressing

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Metallurgy and Design of Alloys with Hierarchical Microstructures

Metallurgy and Design of Alloys with Hierarchical Microstructures
  • Author : Krishnan K. Sankaran,Rajiv S. Mishra
  • Publisher : Elsevier
  • Release : 14 June 2017
GET THIS BOOKMetallurgy and Design of Alloys with Hierarchical Microstructures

Metallurgy and Design of Alloys with Hierarchical Microstructures covers the fundamentals of processing-microstructure-property relationships and how multiple properties are balanced and optimized in materials with hierarchical microstructures widely used in critical applications. The discussion is based principally on metallic materials used in aircraft structures; however, because they have sufficiently diverse microstructures, the underlying principles can easily be extended to other materials systems. With the increasing microstructural complexity of structural materials, it is important for students, academic researchers and practicing engineers

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Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)

Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)
  • Author : Anonim
  • Publisher : World Scientific
  • Release : 10 March 2020
GET THIS BOOKHandbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)

This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances

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Homogenization and materials design of mechanical properties of textured materials based on zeroth-, first- and second-order bounds of linear behavior