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Vinod Kushvaha, Priyanka Madhushri, Priyanka Madhushri et al, M R Sanjay, M. R. Sanjay, …
Machine Learning Applied to Composite Materials
English · Hardback
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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 materialcomposite modelling and design.
About the author
Dr. Priyanka Madhushri is the Internet of Things (IoT) Ideation Research Engineer at Stanley Black and Decker (SBD), Atlanta. Dr. Madhushri earned her Ph.D. in Electrical Engineering from the University of Alabama in Huntsville, USA. She works with the innovation team and brings new ideas to various projects. As a researcher, she provides Proof of Concept (POC) to various SBD teams and assists in developing the company's software, hardware, and data analytics. Her research interestsinclude predictive analyses using Machine Learning, material modeling, Internet of Things (IoT), mobile computing, etc. She has published in various engineering fields, including materials journals, where her work focused on utilizing machine learning algorithms to predict and explain the mechanical behavior of advanced engineering materials.
Product details
| Assisted by |
Vinod Kushvaha (Editor) |
| Publisher | Springer, Berlin |
| Content | Book |
| Product form | Hardback |
| Publication date | 01.12.2022 |
| Subject |
Natural sciences, medicine, IT, technology |
| EAN | 9789811962776 |
| ISBN | 978-981-1962-77-6 |
| Pages | 198 |
| Illustrations | VI, 198 p. 71 illus., 61 illus. in color. |
| Dimensions (packing) | 15.5 x 1.4 x 23.5 cm |
| Series |
Composites Science and Technology Composites Science and Technol |
| Subjects |
Maschinelles Lernen |
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