The volume focuses on theoretical and computational approaches and involves areas such as simulation-based engineering and science, integrated computational materials engineering, mechanics, material science, manufacturing processes, and other specialized areas. Most importantly, the state-of-the-art progress in developing predictive theoretical, computational and experimental approaches for additive manufacturing is summarized.

Additive manufacturing (AM) methods have great potential for promoting transformative research in many fields across the vast spectrum of engineering and materials science. AM is one of the leading forms of advanced manufacturing which enables direct computer-aided design (CAD) to part production without part-specific tooling. In October 2015 the National Academies of Sciences, Engineering, and Medicine convened a workshop of experts from diverse communities to examine predictive theoretical and computational approaches for various AM technologies. While experimental workshops in AM have been held in the past, this workshop uniquely focused on theoretical and computational approaches and involved areas such as simulation-based engineering and science, integrated computational materials engineering, mechanics, materials science, manufacturing processes, and other specialized areas. This publication summarizes the presentations and discussions from the workshop.

Additive Manufacturing for Bio-Composites and Synthetic Composites focuses on processes, engineering, and product design applications of bio-composites and synthetic composites in additive manufacturing (AM). It discusses the preparation and material characterization and selection, as well as future opportunities and challenges. Reviews the latest research on the development of composites for AM and the preparation of composite feedstocks. Offers an analytical and statistical approach for the selection of composites for AM, including characterization of material properties. Emphasizes the use of environmentally friendly composites. Analyzes the lifecycle including costs. Considers potential new fibers, their selection, and future applications. This book provides a comprehensive overview of the application of advanced composite materials in AM and is aimed at researchers, engineers, and advanced students in materials and manufacturing engineering and related disciplines.

Innovation and Sustainable Manufacturing: Research and Development addresses the manufacturing sustainability challenge from different points of view, drawing on research from different disciplines to shed light on the latest green technologies, green product design methods, and materials. Addressing the needs of practitioners as well as academics, this book examines a range of important themes such as environmental impacts and how to assess them, how to set boundary conditions to include or exclude downstream supply chains, how to improve sustainability without sacrificing productivity, the cost benefits of sustainability, and how to trace impacts in manufacturing. By providing a thorough review of global research in this field, Innovation and Sustainable Manufacturing acts as an ideal entry point into this discipline for researchers, and a guide to the latest developments for forward-thinking practitioners. Covers how different stages of the manufacturing supply chain can impact on sustainability Combines research from a variety of disciplines to provide a comprehensive coverage of this complex subject Explores the relationship between sustainability and other goals such as productivity, quality, and profitability

This book gathers the latest advances, innovations, and applications in the field of computational engineering, as presented by leading international researchers and engineers at the 24th International Conference on Computational & Experimental Engineering and Sciences (ICCES), held in Tokyo, Japan on March 25-28, 2019. ICCES covers all aspects of applied sciences and engineering: theoretical, analytical, computational, and experimental studies and solutions of problems in the physical, chemical, biological, mechanical, electrical, and mathematical sciences. As such, the book discusses highly diverse topics, including composites; bioengineering & biomechanics; geotechnical engineering; offshore & arctic engineering; multi-scale & multi-physics fluid engineering; structural integrity & longevity; materials design & simulation; and computer modeling methods in engineering. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.

This book introduces Mechanistic Data Science (MDS) as a structured methodology for combining data science tools with mathematical scientific principles (i.e., “mechanistic” principles) to solve intractable problems. Traditional data science methodologies require copious quantities of data to show a reliable pattern, but the amount of required data can be greatly reduced by considering the mathematical science principles. MDS is presented here in six easy-to-follow modules: 1) Multimodal data generation and collection, 2) extraction of mechanistic features, 3) knowledge-driven dimension reduction, 4) reduced order surrogate models, 5) deep learning for regression and classification, and 6) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems as well as real-life problems. This book is written in a spectral style and is ideal as an entry level textbook for engineering and data science undergraduate and graduate students, practicing scientists and engineers, as well as STEM (Science, Technology, Engineering, Mathematics) high school students and teachers.

Although computational modeling and simulation of material deformation was initiated with the study of structurally simple materials and inert environments, there is an increasing demand for predictive simulation of more realistic material structure and physical conditions. In particular, it is recognized that applied mechanical force can plausibly alter chemical reactions inside materials or at material interfaces, though the fundamental reasons for this chemomechanical coupling are studied in a material-speci c manner. Atomistic-level s- ulations can provide insight into the unit processes that facilitate kinetic reactions within complex materials, but the typical nanosecond timescales of such simulations are in contrast to the second-scale to hour-scale timescales of experimentally accessible or technologically relevant timescales. Further, in complex materials these key unit processes are “rare events” due to the high energy barriers associated with those processes. Examples of such rare events include unbinding between two proteins that tether biological cells to extracellular materials [1], unfolding of complex polymers, stiffness and bond breaking in amorphous glass bers and gels [2], and diffusive hops of point defects within crystalline alloys [3].