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Additive And Advanced Manufacturing Inverse Problem Methodologies And Machine Learning And Data Science Volume 4
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Book Synopsis Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4 by : Sharlotte L. B. Kramer
Download or read book Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4 written by Sharlotte L. B. Kramer and published by Springer Nature. This book was released on with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Thermomechanics & Infrared Imaging, Inverse Problem Methodologies, Mechanics of Additive & Advanced Manufactured Materials, and Advancements in Optical Methods & Digital Image Correlation, Volume 4 by : Sharlotte L.B. Kramer
Download or read book Thermomechanics & Infrared Imaging, Inverse Problem Methodologies, Mechanics of Additive & Advanced Manufactured Materials, and Advancements in Optical Methods & Digital Image Correlation, Volume 4 written by Sharlotte L.B. Kramer and published by Springer Nature. This book was released on 2022-02-14 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thermomechanics & Infrared Imaging, Inverse Problem Methodologies and Mechanics of Additive & Advanced Manufactured Materials, and Advancement of Optical Methods & Digital Image Correlation, Volume 4 of the Proceedings of the 2021 SEM Annual Conference & Exposition on Experimental and Applied Mechanics, the fourth volume of four from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on a wide range of areas, including: Test Design and Inverse Method Algorithms Inverse Problems: Virtual Fields Method Material Characterizations Using Thermography Fatigue, Damage & Fracture Evaluation Using Infrared Thermography Mechanics of Additive & Advanced Manufactured Materials DIC Methods & Its Applications Photoelasticity and Interferometry Applications Micro-Optics and Microscopic Systems Multiscale and New Developments in Optical Methods
Book Synopsis Smart Materials in Additive Manufacturing, volume 2: 4D Printing Mechanics, Modeling, and Advanced Engineering Applications by : Mahdi Bodaghi
Download or read book Smart Materials in Additive Manufacturing, volume 2: 4D Printing Mechanics, Modeling, and Advanced Engineering Applications written by Mahdi Bodaghi and published by Elsevier. This book was released on 2022-06-25 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart Materials in Additive Manufacturing, Volume 2 covers the mechanics, modeling, and applications of the technology and the materials produced by it. It approaches the topic from an engineering design perspective with cutting-edge modeling techniques and real-world applications and case studies highlighted throughout. The book demonstrates 4D printing techniques for electro-induced shape memory polymers, pneumatic soft actuators, textiles, and more. Modeling techniques with ABAQUS and machine learning are outlined, as are manufacturing techniques for highly elastic skin, tunable RF and wireless structures and modules, and 4D printed structures with tunable mechanical properties. Closed-loop control of 4D printed hydrogel soft robots, hierarchical motion of 4D printed structures using the temperature memory effect, multimaterials 4D printing using a grasshopper plugin, shape reversible 4D printing, and variable stiffness 4D printing are each discussed as well. Outlines cutting-edge techniques, structural design, modeling, simulation, and tools for application-based 4D printing Details design, modeling, simulation, and manufacturing considerations for various fields Includes case studies demonstrating real-world situations where the techniques and concepts discussed were successfully deployed Applications covered include textiles, soft robotics, auxetics and metamaterials, micromachines, sensors, bioprinting, and wireless devices Covers the mechanics, manufacturing processes and applications of 4D-printed smart materials and structures Discusses applications in civil, mechanical, aerospace, polymer and biomedical engineering Presents experimental, numerical and analytical studies in a simple and straightforward manner, providing tools that can be immediately implemented and adapted by readers to fit their work
Book Synopsis Machine Learning for Powder-Based Metal Additive Manufacturing by : Gurminder Singh
Download or read book Machine Learning for Powder-Based Metal Additive Manufacturing written by Gurminder Singh and published by Elsevier. This book was released on 2024-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning for Powder-based Metal Additive Manufacturing outlines machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing processes, and reduce costs. The book combines ML and AM methods to develop intelligent models that train AM techniques in pre-processing, process optimization, and post-processing for optimized microstructure, tensile and fatigue properties, and biocompatibility for various applications. The book covers ML for design in AM, ML for materials development and intelligent monitoring in metal AM, both geometrical deviation and physics informed machine learning modeling, as well as data-driven cost estimation by ML. Optimization for slicing and orientation, ML to create models of materials for AM processes, ML prediction for better mechanical and microstructure prediction, and feature extraction by sensing data are all covered, and each chapter includes a case study.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309494206 Total Pages :79 pages Book Rating :4.3/5 (94 download)
Book Synopsis Data-Driven Modeling for Additive Manufacturing of Metals by : National Academies of Sciences, Engineering, and Medicine
Download or read book Data-Driven Modeling for Additive Manufacturing of Metals written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-11-09 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: Additive manufacturing (AM) is the process in which a three-dimensional object is built by adding subsequent layers of materials. AM enables novel material compositions and shapes, often without the need for specialized tooling. This technology has the potential to revolutionize how mechanical parts are created, tested, and certified. However, successful real-time AM design requires the integration of complex systems and often necessitates expertise across domains. Simulation-based design approaches, such as those applied in engineering product design and material design, have the potential to improve AM predictive modeling capabilities, particularly when combined with existing knowledge of the underlying mechanics. These predictive models have the potential to reduce the cost of and time for concept-to-final-product development and can be used to supplement experimental tests. The National Academies convened a workshop on October 24-26, 2018 to discuss the frontiers of mechanistic data-driven modeling for AM of metals. Topics of discussion included measuring and modeling process monitoring and control, developing models to represent microstructure evolution, alloy design, and part suitability, modeling phases of process and machine design, and accelerating product and process qualification and certification. These topics then led to the assessment of short-, immediate-, and long-term challenges in AM. This publication summarizes the presentations and discussions from the workshop.
Book Synopsis Materials Discovery and Design by : Turab Lookman
Download or read book Materials Discovery and Design written by Turab Lookman and published by Springer. This book was released on 2018-09-22 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the application of data science to materials problems are sketched. Computational and experimental facilities today generate vast amounts of data at an unprecedented rate. The book gives guidance to discover new knowledge that enables materials innovation to address grand challenges in energy, environment and security, the clearer link needed between the data from these facilities and the theory and underlying science. The role of inference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key to achieving the desired goals of real time analysis and feedback. Thus, the importance of this book lies in emphasizing that the full value of knowledge driven discovery using data can only be realized by integrating statistical and information sciences with materials science, which is increasingly dependent on high throughput and large scale computational and experimental data gathering efforts. This is especially the case as we enter a new era of big data in materials science with the planning of future experimental facilities such as the Linac Coherent Light Source at Stanford (LCLS-II), the European X-ray Free Electron Laser (EXFEL) and MaRIE (Matter Radiation in Extremes), the signature concept facility from Los Alamos National Laboratory. These facilities are expected to generate hundreds of terabytes to several petabytes of in situ spatially and temporally resolved data per sample. The questions that then arise include how we can learn from the data to accelerate the processing and analysis of reconstructed microstructure, rapidly map spatially resolved properties from high throughput data, devise diagnostics for pattern detection, and guide experiments towards desired targeted properties. The authors are an interdisciplinary group of leading experts who bring the excitement of the nascent and rapidly emerging field of materials informatics to the reader.
Book Synopsis Parallel Coordinates by : Alfred Inselberg
Download or read book Parallel Coordinates written by Alfred Inselberg and published by Springer Science & Business Media. This book was released on 2009-08-15 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is one book that can genuinely be said to be straight from the horse’s mouth. Written by the originator of the technique, it examines parallel coordinates as the leading methodology for multidimensional visualization. Starting from geometric foundations, this is the first systematic and rigorous exposition of the methodology's mathematical and algorithmic components. It covers, among many others, the visualization of multidimensional lines, minimum distances, planes, hyperplanes, and clusters of "near" planes. The last chapter explains in a non-technical way the methodology's application to visual and automatic data mining. The principles of the latter, along with guidelines, strategies and algorithms are illustrated in detail on real high-dimensional datasets.
Book Synopsis Practical Statistics for Data Scientists by : Peter Bruce
Download or read book Practical Statistics for Data Scientists written by Peter Bruce and published by "O'Reilly Media, Inc.". This book was released on 2017-05-10 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Book Synopsis The Data Science Design Manual by : Steven S. Skiena
Download or read book The Data Science Design Manual written by Steven S. Skiena and published by Springer. This book was released on 2017-07-01 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
Book Synopsis Additive Manufacturing by : Amit Bandyopadhyay
Download or read book Additive Manufacturing written by Amit Bandyopadhyay and published by CRC Press. This book was released on 2015-09-08 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of additive manufacturing has seen explosive growth in recent years due largely in part to renewed interest from the manufacturing sector. Conceptually, additive manufacturing, or industrial 3D printing, is a way to build parts without using any part-specific tooling or dies from the computer-aided design (CAD) file of the part. Today, mo
Book Synopsis Automated Machine Learning by : Frank Hutter
Download or read book Automated Machine Learning written by Frank Hutter and published by Springer. This book was released on 2019-05-17 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Book Synopsis Data Science and Big Data Analytics by : EMC Education Services
Download or read book Data Science and Big Data Analytics written by EMC Education Services and published by John Wiley & Sons. This book was released on 2015-01-05 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
Book Synopsis Introduction to Neural Networks with Java by : Jeff Heaton
Download or read book Introduction to Neural Networks with Java written by Jeff Heaton and published by Heaton Research Incorporated. This book was released on 2005 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: In addition to showing the programmer how to construct Neural Networks, the book discusses the Java Object Oriented Neural Engine (JOONE), a free open source Java neural engine. (Computers)
Book Synopsis Technical, Economic and Societal Effects of Manufacturing 4.0 by : Mikael Collan
Download or read book Technical, Economic and Societal Effects of Manufacturing 4.0 written by Mikael Collan and published by Springer Nature. This book was released on 2020-07-28 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is among the first cross-disciplinary works about Manufacturing 4.0. It includes chapters about the technical, the economic, and the social aspects of this important phenomenon. Together the material presented allows the reader to develop a holistic picture of where the manufacturing industry and the parts of the society that depend on it may be going in the future. Manufacturing 4.0 is not only a technical change, nor is it a purely technically driven change, but it is a societal change that has the potential to disrupt the way societies are constructed both in the positive and in the negative. This book will be of interest to scholars researching manufacturing, technological innovation, innovation management and industry 4.0.
Book Synopsis Econometric Analysis of Cross Section and Panel Data, second edition by : Jeffrey M. Wooldridge
Download or read book Econometric Analysis of Cross Section and Panel Data, second edition written by Jeffrey M. Wooldridge and published by MIT Press. This book was released on 2010-10-01 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
Book Synopsis An Introduction to Computational Micromechanics by : Tarek I. Zohdi
Download or read book An Introduction to Computational Micromechanics written by Tarek I. Zohdi and published by Springer Science & Business Media. This book was released on 2008-03-15 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this, its second corrected printing, Zohdi and Wriggers’ illuminating text presents a comprehensive introduction to the subject. The authors include in their scope basic homogenization theory, microstructural optimization and multifield analysis of heterogeneous materials. This volume is ideal for researchers and engineers, and can be used in a first-year course for graduate students with an interest in the computational micromechanical analysis of new materials.
Download or read book The Book of Why written by Judea Pearl and published by Basic Books. This book was released on 2018-05-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
