Machine Learning Applied to Composite Materials PDF Download
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Author: Vinod Kushvaha
Publisher: Springer Nature
ISBN: 9811962782
Category : Technology & Engineering
Languages : en
Pages : 202
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Book Description
This book introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials to achieve the required properties for certain applications. ML can learn from existing experimental data obtained from very limited number of experiments and subsequently can be trained to find solutions of the complex non-linear, multi-dimensional functional relationships without any prior assumptions about their nature. In this case the ML models can learn from existing experimental data obtained from (1) composite design based on various properties of the matrix material and fillers/reinforcements (2) material processing during fabrication (3) property relationships. Modelling of these relationships using ML methods significantly reduce the experimental work involved in designing new composites, and therefore offer a new avenue for material design and properties. The book caters to students, academics and researchers who are interested in the field of material composite modelling and design.
Author: Vinod Kushvaha
Publisher: Springer Nature
ISBN: 9811962782
Category : Technology & Engineering
Languages : en
Pages : 202
Get Book
Book Description
This book introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials to achieve the required properties for certain applications. ML can learn from existing experimental data obtained from very limited number of experiments and subsequently can be trained to find solutions of the complex non-linear, multi-dimensional functional relationships without any prior assumptions about their nature. In this case the ML models can learn from existing experimental data obtained from (1) composite design based on various properties of the matrix material and fillers/reinforcements (2) material processing during fabrication (3) property relationships. Modelling of these relationships using ML methods significantly reduce the experimental work involved in designing new composites, and therefore offer a new avenue for material design and properties. The book caters to students, academics and researchers who are interested in the field of material composite modelling and design.
Author: Akarsh Verma
Publisher: Springer Nature
ISBN: 9819721040
Category :
Languages : en
Pages : 385
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Book Description
Author: S.M. Sapuan
Publisher: CRC Press
ISBN: 9781420093339
Category : Technology & Engineering
Languages : en
Pages : 368
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Book Description
Artificial neural networks (ANN) can provide new insight into the study of composite materials and can normally be combined with other artificial intelligence tools such as expert system, genetic algorithm, and fuzzy logic. Because research on this field is very new, there is only a limited amount of published literature on the subject. Compiling information from diverse sources, Composite Materials Technology: Neural Network Applications fills the void in knowledge of these important networks, covering composite mechanics, materials characterization, product design, and other important aspects of polymer matrix composites. Light weight, corrosion resistance, good stiffness and strength properties, and part consolidation are just some of the reasons that composites are useful in areas including civil engineering and structure, chemical processing, management, agriculture, space study, and manufacturing. ANN has already been used to carry out design prediction, mechanical property prediction, and selection processes in the evolution of composites, but although it has already been used with great success in various branches of scientific and technological research, it is still in the nascent stage of its development. Featuring contributions from leading researchers throughout the world, this book is divided into four parts, starting with an introduction to neural networks and a review of existing literature on the subject. The text then covers structural health monitoring and damage detection in composites, addresses mechanical properties, and discusses design, analysis, and materials selection. Training, testing, and validation of experimental data were carried out to optimize the results presented in the book. This book will be an important aid to researchers as they work on the future implementation of ANN in industries such as aerospace, automotive, marine, sporting goods, furniture, and electronics and communication.
Author: Nirav Joshi
Publisher: Springer Nature
ISBN: 9819903939
Category : Science
Languages : en
Pages : 306
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Book Description
This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material’s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.
Author: Kamal K. Kar
Publisher: Springer
ISBN: 3662495147
Category : Technology & Engineering
Languages : en
Pages : 686
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Book Description
Composite materials are used as substitutions of metals/traditional materials in aerospace, automotive, civil, mechanical and other industries. The present book collects the current knowledge and recent developments in the characterization and application of composite materials. To this purpose the volume describes the outstanding properties of this class of advanced material which recommend it for various industrial applications.
Author: Akarsh Verma
Publisher: Springer Nature
ISBN: 9819935490
Category : Technology & Engineering
Languages : en
Pages : 419
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Book Description
This book comprehensively reviews assorted types of coatings, their applications, and various strategies employed by several scientists and researchers to fabricate them. Exclusively, the recent progress in computational strategies that are helpful to optimize the best suitable coating formulation before one goes for the real-time fabrication has been discussed in detail. And this book is also intended to shed light on the computational modeling techniques that are used in the characterization of various coating materials. It covers mechanisms, salient features, formulations, important aspects, and case studies of coatings utilized for various applications. The latest research in this area as well as possible avenues of future research is also highlighted to encourage the researchers.
Author: Igor Kononenko
Publisher: Horwood Publishing
ISBN: 9781904275213
Category : Computers
Languages : en
Pages : 484
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Book Description
Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. Written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining, this text is suitable foradvanced undergraduates, postgraduates and tutors in a wide area of computer science and technology, as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to libraries and bookshelves of the many companies who are using the principles of data mining to effectively deliver solid business and industry solutions.
Author: Maciej Paszynski
Publisher: Springer Nature
ISBN: 3030779645
Category : Computers
Languages : en
Pages : 609
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Book Description
The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually. Chapter “Effective Solution of Ill-posed Inverse Problems with Stabilized Forward Solver” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Rajiv Gupta
Publisher: CRC Press
ISBN: 1000820815
Category : Technology & Engineering
Languages : en
Pages : 793
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Book Description
The role of manufacturing in a country’s economy and societal development has long been established through their wealth generating capabilities. To enhance and widen our knowledge of materials and to increase innovation and responsiveness to ever-increasing international needs, more in-depth studies of functionally graded materials/tailor-made materials, recent advancements in manufacturing processes and new design philosophies are needed at present. The objective of this volume is to bring together experts from academic institutions, industries and research organizations and professional engineers for sharing of knowledge, expertise and experience in the emerging trends related to design, advanced materials processing and characterization, and advanced manufacturing processes.
Author: Jie Yang
Publisher: Elsevier
ISBN: 0443154260
Category : Technology & Engineering
Languages : en
Pages : 481
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Book Description
Functionally Graded Porous Structures: Applied Methods in Mechanical Performance Evaluation, Machine Learning Aided Analysis, and Additive Manufacturing presents a state-of-the-art review of the latest advances and cutting-edge technologies in this important research field. The book is divided into three key sections. The first section begins with an introduction to functionally graded porous structures and details the effects of graded porosities on bending, buckling, and vibration behaviours within the framework of Timoshenko beam theory, and first-order shear deformable plate theory. The second section is focused on the usage of machine learning techniques for smart structural analysis of porous components as an evolution from traditional engineering, methods. The third section focuses on additive manufacturing of structures with graded porosities for end-user applications. The book follows a clear path from design and analysis to fabrication and applications. Readers will find extensive knowledge and examples of functionally graded porous structures that are suitable for innovative research and market needs, with applications relevant to a diverse range of industrial fields, including mechanical, structural, aerospace, energy, and biomedical engineering. Provides a comprehensive picture of novel porous materials and advanced lightweight structural technologies that are applicable to a diverse range of industrial sectors Updated with the most recent advances in the field of porous structures Goes beyond traditional structural aspects and covers novel evaluation strategies, machine learning aided analysis, and additive manufacturing Covers weight management strategies for structural components to achieve multifunctional purposes Addresses key issues in the design of lightweight structures, offering significant environmental benefits
