Fatigue failure of structures used in transportation, industry, medical equipment, and electronic components needs to build a link between cutting-edge experimental characterization and probabilistically grounded numerical and artificially intelligent tools. The physics involved in this process chain is computationally prohibitive to comprehend using traditional computation methods. Using machine learning and Bayesian statistics, a defect-correlated estimate of fatigue strength was developed. Fatigue, which is a random variable, is studied in a Bayesian-based machine learning algorithm. The stress-life model was used based on the compatibility condition of life and load distributions. The defect-correlated assessment of fatigue strength was established using the proposed machine learning and Bayesian statistics algorithms. It enabled the mapping of structural and process-induced fatigue characteristics into a geometry-independent load density chart across a wide range of fatigue regimes.

This engaging volume presents the exciting new technology of additive manufacturing (AM) of metal objects for a broad audience of academic and industry researchers, manufacturing professionals, undergraduate and graduate students, hobbyists, and artists. Innovative applications ranging from rocket nozzles to custom jewelry to medical implants illustrate a new world of freedom in design and fabrication, creating objects otherwise not possible by conventional means. The author describes the various methods and advanced metals used to create high value components, enabling readers to choose which process is best for them. Of particular interest is how harnessing the power of lasers, electron beams, and electric arcs, as directed by advanced computer models, robots, and 3D printing systems, can create otherwise unattainable objects. A timeline depicting the evolution of metalworking, accelerated by the computer and information age, ties AM metal technology to the rapid evolution of global technology trends. Charts, diagrams, and illustrations complement the text to describe the diverse set of technologies brought together in the AM processing of metal. Extensive listing of terms, definitions, and acronyms provides the reader with a quick reference guide to the language of AM metal processing. The book directs the reader to a wealth of internet sites providing further reading and resources, such as vendors and service providers, to jump start those interested in taking the first steps to establishing AM metal capability on whatever scale. The appendix provides hands-on example exercises for those ready to engage in experiential self-directed learning.

Thermo-mechanical Modeling of Additive Manufacturing provides the background, methodology and description of modeling techniques to enable the reader to perform their own accurate and reliable simulations of any additive process. Part I provides an in depth introduction to the fundamentals of additive manufacturing modeling, a description of adaptive mesh strategies, a thorough description of thermal losses and a discussion of residual stress and distortion. Part II applies the engineering fundamentals to direct energy deposition processes including laser cladding, LENS builds, large electron beam parts and an exploration of residual stress and deformation mitigation strategies. Part III concerns the thermo-mechanical modeling of powder bed processes with a description of the heat input model, classical thermo-mechanical modeling, and part scale modeling. The book serves as an essential reference for engineers and technicians in both industry and academia, performing both research and full-scale production. Additive manufacturing processes are revolutionizing production throughout industry. These technologies enable the cost-effective manufacture of small lot parts, rapid repair of damaged components and construction of previously impossible-to-produce geometries. However, the large thermal gradients inherent in these processes incur large residual stresses and mechanical distortion, which can push the finished component out of engineering tolerance. Costly trial-and-error methods are commonly used for failure mitigation. Finite element modeling provides a compelling alternative, allowing for the prediction of residual stresses and distortion, and thus a tool to investigate methods of failure mitigation prior to building. - Provides understanding of important components in the finite element modeling of additive manufacturing processes necessary to obtain accurate results - Offers a deeper understanding of how the thermal gradients inherent in additive manufacturing induce distortion and residual stresses, and how to mitigate these undesirable phenomena - Includes a set of strategies for the modeler to improve computational efficiency when simulating various additive manufacturing processes - Serves as an essential reference for engineers and technicians in both industry and academia

This book is a printed edition of the Special Issue "Fatigue Damage" that was published in Metals

This book contains the proceedings of the Additive Manufacturing in Product Development Conference. The content focus on how to support real-world value chains by developing additive manufactured series products.

In five chapters, this volume presents recent developments in fatigue assessment. In the first chapter, a generalized Neuber concept of fictitious notch rounding is presented where the microstructural support factors depend on the notch opening angle besides the loading mode. The second chapter specifies the notch stress factor including the strain energy density and J-integral concept while the SED approach is applied to common fillet welded joints and to thin-sheet lap welded joints in the third chapter. The forth chapter analyses elastic-plastic deformations in the near crack tip zone and discusses driving force parameters. The last chapter discusses thermomechanical fatigue, stress, and strain ranges.

Recent developments in engineering and technology have brought about serious and enlarged demands for reliability, safety and economy in wide range of fields such as aeronautics, nuclear engineering, civil and structural engineering, automotive and production industry. This, in turn, has caused more interest in continuum damage mechanics and its engineering applications. This book aims to give a concise overview of the current state of damage mechanics, and then to show the fascinating possibility of this promising branch of mechanics, and to provide researchers, engineers and graduate students with an intelligible and self-contained textbook. The book consists of two parts and an appendix. Part I is concerned with the foundation of continuum damage mechanics. Basic concepts of material damage and the mechanical representation of damage state of various kinds are described in Chapters 1 and 2. In Chapters 3-5, irreversible thermodynamics, thermodynamic constitutive theory and its application to the modeling of the constitutive and the evolution equations of damaged materials are descried as a systematic basis for the subsequent development throughout the book. Part II describes the application of the fundamental theories developed in Part I to typical damage and fracture problems encountered in various fields of the current engineering. Important engineering aspects of elastic-plastic or ductile damage, their damage mechanics modeling and their further refinement are first discussed in Chapter 6. Chapters 7 and 8 are concerned with the modeling of fatigue, creep, creep-fatigue and their engineering application. Damage mechanics modeling of complicated crack closure behavior in elastic-brittle and composite materials are discussed in Chapters 9 and 10. In Chapter 11, applicability of the local approach to fracture by means of damage mechanics and finite element method, and the ensuing mathematical and numerical problems are briefly discussed. A proper understanding of the subject matter requires knowledge of tensor algebra and tensor calculus. At the end of this book, therefore, the foundations of tensor analysis are presented in the Appendix, especially for readers with insufficient mathematical background, but with keen interest in this exciting field of mechanics.

Additive Manufacturing for the Aerospace Industry explores the design, processing, metallurgy and applications of additive manufacturing (AM) within the aerospace industry. The book's editors have assembled an international team of experts who discuss recent developments and the future prospects of additive manufacturing. The work includes a review of the advantages of AM over conventionally subtractive fabrication, including cost considerations. Microstructures and mechanical properties are also presented, along with examples of components fabricated by AM. Readers will find information on a broad range of materials and processes used in additive manufacturing. It is ideal reading for those in academia, government labs, component fabricators, and research institutes, but will also appeal to all sectors of the aerospace industry. - Provides information on a broad range of materials and processes used in additive manufacturing - Presents recent developments in the design and applications of additive manufacturing specific to the aerospace industry - Covers a wide array of materials for use in the additive manufacturing of aerospace parts - Discusses current standards in the area of aerospace AM parts

These proceedings exchange ideas and knowledge among engineers, designers and managers on how to support real-world value chains by developing additive manufactured series products. The papers from the conference show a holistic, multidisciplinary view.

Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.