This volume presents recent research work focused in the development of adequate theoretical and numerical formulations to describe the behavior of advanced engineering materials. Particular emphasis is devoted to applications in the fields of biological tissues, phase changing and porous materials, polymers and to micro/nano scale modeling. Sensitivity analysis, gradient and non-gradient based optimization procedures are involved in many of the chapters, aiming at the solution of constitutive inverse problems and parameter identification. All these relevant topics are exposed by experienced international and inter institutional research teams resulting in a high level compilation. The book is a valuable research reference for scientists, senior undergraduate and graduate students, as well as for engineers acting in the area of computational material modeling.

Tribology of Additively Manufactured Materials: Fundamentals, Modeling, and Applications starts with a look at the history, methods and mechanics of additive manufacturing (AM), focusing on power bed fusion-based and direct energy deposition-based additive manufacturing. Following sections of the book provide a foundational background in the fundamentals of tribology, covering the basics of surface engineering, friction and wear, corrosion and tribocorrosion, and the tribological considerations of a variety of AM materials, such as friction and wear in non-metallic and metallic AM materials, degradation in non-metallic AM components, and corrosion and tribocorrosion in AM components. The book then concludes with a section covering modeling and simulation scenarios and challenges related to the tribology of AM materials, providing readers with the processing conditions needed to extend and strengthen the lifetime and durability of AM materials and components. - Provides theoretical, experimental and computational data for a better understanding of the complex tribological behaviors in additively manufactured components - Discusses applications of additively manufactured components, considering their tribological properties - Studies how unique surface roughness and texture develop in additively manufactured components and how these unique characteristics affect their tribological function - Outlines variables, additive manufacturing methods and performance of additively manufactured components - Equips readers with a better understanding of degradation effects due to tribology and corrosion

The science and study of functionally graded materials (FGMs) have intrigued researchers over the last few decades. Their application has the capability to produce parts with unmatched properties which are virtually impossible to obtain via conventional material routes. This book addresses various FGM aspects and provides a relevant, high-quality, and comprehensive data source. The book covers trends, process classification on various bases, physical processes involved, structure, properties, applications, advantages, and limitations. Emerging trends in the field are discussed in detail and advancements are thoroughly reviewed and presented to broaden the spectrum of FGM applications. This reference book will be of interest to scholars, researchers, academicians, industry practitioners, government labs, libraries, and anyone interested in the area of materials engineering.

This second volume of the three-volume set (CCIS 1193, CCIS 1194, and CCIS 1195) constitutes the refereed proceedings of the First International Conference on Applied Technologies, ICAT 2019, held in Quito, Ecuador, in December 2019. The 124 full papers were carefully reviewed and selected from 328 submissions. The papers are organized according to the following topics: technology trends; computing; intelligent systems; machine vision; security; communication; electronics; e-learning; e-government; e-participation.

Discover the state-of-the-art in multiscale modeling and optimization in manufacturing from two leading voices in the field Modeling and Optimization in Manufacturing delivers a comprehensive approach to various manufacturing processes and shows readers how multiscale modeling and optimization processes help improve upon them. The book elaborates on the foundations and applications of computational modeling and optimization processes, as well as recent developments in the field. It offers discussions of manufacturing processes, including forming, machining, casting, joining, coating, and additive manufacturing, and how computer simulations have influenced their development. Examples for each category of manufacturing are provided in the text, and industrial applications are described for the reader. The distinguished authors also provide an insightful perspective on likely future trends and developments in manufacturing modeling and optimization, including the use of large materials databases and machine learning. Readers will also benefit from the inclusion of: A thorough introduction to the origins of manufacturing, the history of traditional and advanced manufacturing, and recent progress in manufacturing An exploration of advanced manufacturing and the environmental impact and significance of manufacturing Practical discussions of the economic importance of advanced manufacturing An examination of the sustainability of advanced manufacturing, and developing and future trends in manufacturing Perfect for materials scientists, mechanical engineers, and process engineers, Modeling and Optimization in Manufacturing will also earn a place in the libraries of engineering scientists in industries seeking a one-stop reference on multiscale modeling and optimization in manufacturing.

This book presents the latest advances in manufacturing from both the experimental and simulation point of view. It covers most aspects of manufacturing engineering, i.e. theoretical, analytical, computational and experimental studies. Experimental studies on manufacturing processes require funds, time and expensive facilities, while numerical simulations and mathematical models can improve the efficiency of using the research results. It also provides high level of prediction accuracy and the basis for novel research directions.