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Application of Machine Learning in Determining the Mechanical Properties of Materials

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Machine Learning Applied to Composite Materials

Part of the book series: Composites Science and Technology ((CST))

Abstract

Currently, the challenge in front of researchers is to discover new novel material with superior properties as per the demand of the society with a vast range of applications. With evaluation in material characterization techniques large amounts of material data are obtained through experiments and simulations. Even in some cases theoretical concepts cannot be applicable to these data. With increase in material data, application of machine learning and data analytics come into play. Application of machine learning is applicable in various fields such as material properties, analyzing complex reactions, inorganic chemistry, understanding crystal structure, in the design of experiments, etc. Through this article our focus is towards application of machine learning in the field of material characterization techniques in determining the mechanical properties of materials. In this chapter, a brief review of application of machine learning in the field of characterization of the mechanical properties such as tensile strength, fatigue behavior and visco-elastic study have been done.

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Acknowledgements

The authors are grateful to the monetary support provided by the University of Petroleum and Energy Studies (UPES)-SEED Grant program.

Conflicts of Interest

“There are no conflicts of interest to declare by the authors.”

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Authors and Affiliations

  1. Department of Mechanical Engineering, ABES Engineering College, Ghaziabad, India

    Naman Jain

  2. Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, 560-8531, Japan

    Akarsh Verma & Shigenobu Ogata

  3. Department of Mechanical Engineering, University of Petroleum and Energy Studies, Dehradun, India

    Akarsh Verma

  4. The Sirindhorn International Thai-German Graduate School of Engineering, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    M. R. Sanjay & Suchart Siengchin

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  1. Naman Jain
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  2. Akarsh Verma
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  4. M. R. Sanjay
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  5. Suchart Siengchin
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Correspondence to Akarsh Verma .

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Editors and Affiliations

  1. Department of Civil Engineering—Materials and Structures, Indian Institute of Technology Jammu, Jammu, India

    Vinod Kushvaha

  2. Bangkok, President Office Building, King Mongkut’s Univ of Tech North, Bangkok, Thailand

    M. R. Sanjay

  3. Proof of Concept and Innovation Group, Stanley Black & Decker (United States), Atlanta, GA, USA

    Priyanka Madhushri

  4. King Mongkut’s University of Technology, Bangkok, Thailand

    Suchart Siengchin

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Jain, N., Verma, A., Ogata, S., Sanjay, M.R., Siengchin, S. (2022). Application of Machine Learning in Determining the Mechanical Properties of Materials. In: Kushvaha, V., Sanjay, M.R., Madhushri, P., Siengchin, S. (eds) Machine Learning Applied to Composite Materials. Composites Science and Technology . Springer, Singapore. https://doi.org/10.1007/978-981-19-6278-3_5

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