Machine Learning Applied To Composite Materials
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Machine Learning Applied To Composite Materials
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Author : Vinod Kushvaha
language : en
Publisher: Springer Nature
Release Date : 2022-11-29
Machine Learning Applied To Composite Materials written by Vinod Kushvaha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-29 with Technology & Engineering categories.
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.
Machine Learning For Composite Material Analysis And Optimization
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Author : Haotian Feng
language : en
Publisher:
Release Date : 2023
Machine Learning For Composite Material Analysis And Optimization written by Haotian Feng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
My PhD research aims to develop Machine Learning methods for the analysis and optimization of composite materials. Specifically, I focus on two key areas: composite material property prediction and composite material optimization. To enhance the accuracy of Machine Learning models in composite material prediction, I explore the incorporation of practical knowledge into the Machine Learning framework, which can be achieved through various approaches such as input layer, Neural Network, or loss function. My research demonstrates that incorporating existing knowledge can improve the prediction accuracy of Machine Learning models, which can be applied to both data-based and function-based machine learning problems. In addition to prediction, I also investigate optimization strategies for discovering optimal composite material designs using Machine Learning. These findings highlight the great potential of Machine Learning in composite material analysis and offer insights for future research in other applications such as medical image analysis, timeseries data analysis, and image segmentation and classification.
Composite Materials Technology
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Author : S.M. Sapuan
language : en
Publisher: CRC Press
Release Date : 2009-12-23
Composite Materials Technology written by S.M. Sapuan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-23 with Technology & Engineering categories.
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.
Machine Learning Aided Analysis Design And Additive Manufacturing Of Functionally Graded Porous Composite Structures
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Author : Jie Yang
language : en
Publisher: Elsevier
Release Date : 2023-10-16
Machine Learning Aided Analysis Design And Additive Manufacturing Of Functionally Graded Porous Composite Structures written by Jie Yang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-16 with Technology & Engineering categories.
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
Coating Materials
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Author : Akarsh Verma
language : en
Publisher: Springer Nature
Release Date : 2023-07-12
Coating Materials written by Akarsh Verma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-12 with Technology & Engineering categories.
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.
Recent Advances In Material Manufacturing And Machine Learning
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Author : Rajiv Gupta
language : en
Publisher: CRC Press
Release Date : 2023-05-26
Recent Advances In Material Manufacturing And Machine Learning written by Rajiv Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-26 with Technology & Engineering categories.
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.
Dynamic Mechanical And Creep Recovery Behavior Of Polymer Based Composites
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Author : Akarsh Verma
language : en
Publisher: Elsevier
Release Date : 2024-01-19
Dynamic Mechanical And Creep Recovery Behavior Of Polymer Based Composites written by Akarsh Verma and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-19 with Technology & Engineering categories.
Dynamic Mechanical and Creep-Recovery Behaviour of Polymer-Based Composites: Mechanical and Mathematical Modeling covers mathematical modelling, dynamic mechanical analysis, and the ways in which various factors impact the creep-recovery behaviour of polymer composites. The effects of polymer molecular weight, plasticizers, cross-linking agents, and chemical treatment of filler material are addressed and information on thermoplastic and thermosetting polymer-based composites is also covered, including their various applications and the advantages and disadvantages of their use in different settings. The final 2 chapters of the book cover mathematical modeling of creep-recovery behavior for polymer composites and software-based simulation of creep-recovery in polymer composites, respectively. Dynamic Mechanical and Creep-Recovery Behaviour of Polymer-Based Composites: Mechanical and Mathematical Modeling covers mathematical modelling, dynamic mechanical analysis, and the ways in which various factors impact the creep-recovery behaviour of polymer composites. The effects of polymer molecular weight, plasticizers, cross-linking agents, and chemical treatment of filler material are addressed and information on thermoplastic and thermosetting polymer-based composites is also covered, including their various applications and the advantages and disadvantages of their use in different settings. The final 2 chapters of the book cover mathematical modeling of creep-recovery behavior for polymer composites and software-based simulation of creep-recovery in polymer composites, respectively. Analyzes the dynamic mechanical and creep-recovery behaviors of thermoplastic and thermosetting polymer composites in a variety of applications Features diverse mechanical/mathematical models utilized to fit data collected from creep-recovery studies Covers various factors that influence dynamic mechanical properties Discusses the advantages and disadvantages of using these materials in different settings
Machine Learning For Advanced Functional Materials
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Author : Nirav Joshi
language : en
Publisher: Springer Nature
Release Date : 2023-05-22
Machine Learning For Advanced Functional Materials written by Nirav Joshi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-22 with Science categories.
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.
Additive Manufacturing For Biocomposites And Synthetic Composites
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Author : M. T. Mastura
language : en
Publisher: CRC Press
Release Date : 2023-12-27
Additive Manufacturing For Biocomposites And Synthetic Composites written by M. T. Mastura and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-27 with Technology & Engineering categories.
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.
Advances In Machine Learning Research And Application 2011 Edition
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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2012-01-09
Advances In Machine Learning Research And Application 2011 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-09 with Computers categories.
Advances in Machine Learning Research and Application: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Machine Learning. The editors have built Advances in Machine Learning Research and Application: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Machine Learning in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Machine Learning Research and Application: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.