Prediction of thermal conductivity of quartz chlorite schist rocks: a comparative study of MLR and ridge regression

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Date

2025

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Inderscience Publishers

Abstract

Thermal conductivity is a key physical property with broad applications in engineering and geosciences, particularly in energy-efficient building design, geothermal energy systems, and subsurface geological studies. Accurate determination of thermal conductivity is essential for understanding heat transfer mechanisms in rock materials. However, direct in-situ measurement is often impractical due to technical and logistical constraints. As a result, indirect estimation methods, which establish empirical relationships between thermal conductivity and various physico-mechanical properties, have gained attention. This study investigates the thermal conductivity of quartz chlorite schist through laboratory experiments, alongside measuring key physico-mechanical properties, including P-wave velocity, porosity, density, and uniaxial compressive strength (UCS). The objective is to analyse the correlations between thermal conductivity and these properties to develop a reliable predictive model. Multiple regression and ridge regression analysis are employed to derive an empirical equation for estimating thermal conductivity based on the measured parameters. The findings of this study contribute to improving indirect assessment techniques, which are valuable for geotechnical and geological applications where direct measurements are challenging. © © 2025 Inderscience Enterprises Ltd.

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Keywords

Architectural design, Compressive strength, Density (specific gravity), Geothermal fields, Metamorphic rocks, Predictive analytics, Quartz, Regression analysis, Seismic waves, Structural design, Thermal Engineering, Broad application, Comparatives studies, Machine-learning, P-wave velocity, Physicomechanical properties, Property, Quartz chlorite schist, Ridge regression, Schist rock, Thermal, Thermal conductivity

Citation

International Journal of Mining and Mineral Engineering, 2025, 16, 2, pp. 194-212

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