Machine Learning Applied to Composite Materials
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Machine Learning Applied to Composite Materials

SKU: 9789811962783

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Additional information

Full Title

Machine Learning Applied to Composite Materials
Author(s)
Edition
ISBN

9789811962783, 9789811962776
Publisher

Springer
Format

PDF and EPUB

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.

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