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

Applied Micromechanics of Complex Microstructures explains the fundamental concepts of continuum modeling of various complicated microstructures, covering nanocomposites, multiphase composites, biomaterials, biological materials, and more. The authors outline the calculation of effective mechanical and thermal properties, allowing readers to understand the step-by-step modeling and homogenization of complicated microstructures, and the book also features a chapter on microstructure hull and material design. Modeling of complex samples with nonlinear properties such as neural tissue, bone microstructure, and liver tissue is also explained and analyzed. Explains the core concepts of continuum modeling of different complex microstructures, including nanocomposites, multiphase composites, biomaterials, and biological materials Provides detailed calculations of eff ective mechanical and thermal properties allowing the audience to understand the modeling and homogenization of complex microstructures Covers several methods for designing the microstructure of heterogeneous materials

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 to possess the knowledge of how materials are optimized and how they will behave in service. The book integrates aspects of computational materials science, physical metallurgy, alloy design, process design, and structure-properties relationships, in a manner not done before. It fills a knowledge gap in the interrelationships of multiple microstructural and deformation mechanisms by applying the concepts and tools of designing microstructures for achieving combinations of engineering properties—such as strength, corrosion resistance, durability and damage tolerance in multi-component materials—used for critical structural applications. - Discusses the science behind the properties and performance of advanced metallic materials - Provides for the efficient design of materials and processes to satisfy targeted performance in materials and structures - Enables the selection and development of new alloys for specific applications based upon evaluation of their microstructure as illustrated in this work

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 Infrastructure Tools, and (6) Process Optimization. . These papers are intended to further the global implementation of ICME, broaden the variety of applications to which ICME is applied, and ultimately help industry design and produce new materials more efficiently and effectively.

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, development and practical application of optimization methods applied to all engineering disciplines, in a common scientific forum to present, analyze and discuss the latest developments in this area. Engineering Optimization 2014 contains the edited papers presented at the 4th International Conference on Engineering Optimization (ENGOPT2014, Lisbon, Portugal, 8-11 September 2014). ENGOPT2014 is the fourth edition of the biennial “International Conference on Engineering Optimization”. The first conference took place in 2008 in Rio de Janeiro, the second in Lisbon in 2010 and the third in Rio de Janeiro in 2012. The contributing papers are organized around the following major themes: - Numerical Optimization Techniques - Design Optimization and Inverse Problems - Effi cient Analysis and Reanalysis Techniques - Sensitivity Analysis - Industrial Applications - Topology Optimization For Structural Static and Dynamic Failures - Optimization in Oil and Gas Industries - New Advances in Derivative-Free Optimization Methods for Engineering Optimization - Optimization Methods in Biomechanics and Biomedical Engineering - Optimization of Laminated Composite Materials - Inverse Problems in Engineering Engineering Optimization 2014 will be of great interest to engineers and academics in engineering, mathematics and computer science.

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 to end users engaged in product design and design for manufacturing efforts. As such, this emerging field has a pivotal role in realizing the goals outlined in current strategic national initiatives such as the Materials Genome Initiative (MGI) and the Advanced Manufacturing Partnership (AMP). This book presents the foundational elements of this new discipline as it relates to the design, development, and deployment of hierarchical materials critical to advanced technologies. - Addresses a critical gap in new materials research and development by presenting a rigorous statistical framework for the quantification of microstructure - Contains several case studies illustrating the use of modern data analytic tools on microstructure datasets (both experimental and modeling)