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Austenitic TRIP/TWIP Steels and Steel-Zirconia Composites

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Book Series: Springer Series in Materials Science ISBN: 9783030426033 Year: Pages: 829 DOI: 10.1007/978-3-030-42603-3 Language: English
Publisher: Springer Nature
Subject: Agriculture (General) --- Mathematics
Added to DOAB on : 2020-06-16 23:59:31
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This open access book presents a collection of the most up-to-date research results in the field of steel development with a focus on pioneering alloy concepts that result in previously unattainable materials properties. Specifically, it gives a detailed overview of the marriage of high-performance steels of the highest strength and form-ability with damage-tolerant zirconia ceramics by innovative manufacturing technologies, thereby yielding a new class of high-performance composite materials. This book describes how new high-alloy stainless TRIP/TWIP steels (TRIP: TRansformation-Induced Plasticity, TWIP: TWinning-induced Plasticity) are combined with zirconium dioxide ceramics in powder metallurgical routes and via melt infiltration to form novel TRIP-matrix composites. This work also provides a timely perspective on new compact and damage-tolerant composite materials, filigree light-weight structures as well as gradient materials, and a close understanding of the mechanisms of the phase transformations. With a detailed application analysis of state-of-the-art methods in spatial and temporal high-resolution structural analysis, in combination with advanced simulation and modelling, this edited volume is ideal for researchers and engineers working in modern steel development, as well as for graduate students of metallurgy and materials science and engineering.

Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

Authors: --- --- --- --- et al.
ISBN: 9789811562631 Year: Pages: 137 DOI: 10.1007/978-981-15-6263-1 Language: English
Publisher: Springer Nature
Subject: Agriculture (General) --- Mathematics --- Computer Science
Added to DOAB on : 2020-09-01 00:02:34
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This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.

Software for Exascale Computing - SPPEXA 2016-2019

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Book Series: Lecture Notes in Computational Science and Engineering ISBN: 9783030479565 Year: Pages: 620 DOI: 10.1007/978-3-030-47956-5 Language: English
Publisher: Springer Nature
Subject: Computer Science --- Science (General) --- Agriculture (General) --- Mathematics
Added to DOAB on : 2020-09-01 00:03:54
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This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest.

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