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A FEM-Supported Hybrid Approach for Determination of Stress–Strain Relation of Poly-alloy Coating by Inverse Analysis

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Abstract

During last few years, researchers have been concentrating toward the estimation of stress–strain behavior of thin-film coatings using nanoindentation and finite element simulation. In present days, advancement of machine learning algorithms and artificial intelligence made it possible to implement a hybrid approach to extract the properties of a material in a more systematic way. The aim of this work is to find the optimum value of the constants of power-law plastic behavior of thin-film alloy coatings. In this study, an average load–displacement plot was obtained from nanoindentation tests of poly-alloy coatings. Then, a simulation data set was generated in ABAQUS according to design of experiment. A machine learning algorithm was used to generate the surrogate model correlating the constants of power-law plastic behavior as input and mean error between simulation and experimental results as output. Finally, optimization algorithm was used to find out the optimum values of constants of power-law plastic behavior.

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Acknowledgements

This work is financially supported by Council of Scientific and Industrial Research (CSIR-HRDG), Govt. of India, under Sanction No.: 22(0804)/19/EMR-II, dated 25.07.2019

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  1. Department of Mechanical Engineering, Haldia Institute of Technology, Haldia, 721657, India

    Bal Mukund Mishra & Supriyo Roy

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  1. Bal Mukund Mishra
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  2. Supriyo Roy
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Correspondence to Supriyo Roy.

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Mishra, B.M., Roy, S. A FEM-Supported Hybrid Approach for Determination of Stress–Strain Relation of Poly-alloy Coating by Inverse Analysis. Trans Indian Inst Met 75, 2939–2947 (2022). https://doi.org/10.1007/s12666-022-02674-7

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