International Journal of Performance Analysis in Sport, 2021, 17(3): 253-262 doi: 10.23940/ijpe.21.03.p1.253262

Original article

Material Modeling of Epoxy Granite Composite by Analytical Model and Regression Analysis

S. Nallusamy,1,*

Department of Mechanical Engineering, Educational and Research Institute, Chennai, 600095, India

*Corresponding Author(s): Corresponding author. E-mail address: Corresponding author. E-mail address:

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This research work mainly focuses on the material modeling of epoxy granite composite with the help of experimental methods. Generalized mixture rule (GMR) for particulate composite was proposed by screening to estimate a specific mechanical property of epoxy granite with regards to their properties, volume fractions, and microstructures (PVFM) of component. In GMR relation, the effects of microstructures were expressed by means of a scaling fractal parameter j. Taguchi’s design of experiments was applied to plan the number of experiments. The investigations were carried out based on flexural and damping test of epoxy granite specimens with dimension 125x12x6mm and young’s modulus with specimens of dimension 50x50x50mm. Analytical values of specific mechanical property and varying volume fraction were presented for j values 0.25 to 0.1. The experimental results obtained from different tests were plotted over the analytical graph, which further helped to fix the value of j for each effective property. From the results, a unique j value of 0.3 was finalized for epoxy granite with the j fixed for each effective mechanical property. Regression analysis was applied to establish the empirical relation between effective and material properties for experimental results. Comparison between the analytical model from GMR and regression model from experimental results was carried out to validate the mathematical model.

Keywords: epoxy granite ; damping ratio ; generalized mixture rule ; mechanical properties ; aggregate type ; regression analysis

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S. Nallusamy. Material Modeling of Epoxy Granite Composite by Analytical Model and Regression Analysis. International Journal of Performance Analysis in Sport, 2021, 17(3): 253-262 doi:10.23940/ijpe.21.03.p1.253262


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