Thermal Damage Characterization and Modeling in Granite Samples Subjected to Heat Treatment by Leveraging Machine Learning and Experimental Data

Featured Application: The predictive model developed in this study can be used to assess the thermal damage of granite for general applications such as geothermal energy extraction, deep mining, and nuclear waste disposal. By leveraging machine learning and experimental data, the model enables engineers and researchers to evaluate the effect of high temperature on rock properties in underground excavations. High temperatures significantly affect the physical and mechanical properties of rocks in deep geoengineering projects, such as geothermal development, deep mining, and the geological disposal of nuclear waste. Therefore, it is essential to explore the relationship between the thermal damage (TD) of granite and its influencing factors. This paper characterizes the TD of granite specimens subjected to high temperatures of up to 800 °C and proposes a predictive model for this thermal damage. A database, which includes publicly available experimental data of advanced microscopic observations of granite specimens exposed to high-temperature treatments and their changes in physical and mechanical properties, was compiled and analyzed. The collected data revealed a consistent trend: crack development among quartz, feldspar, and biotite minerals was observed to intensify notably between 400 °C and 600 °C, as indicated by changes in the mechanical properties. Based on these characteristics, the relationships between TD and its influential parameters were determined using regression models and several machine learning algorithms. The derived models indicated good predictability performance with a coefficient of determination (R²) varying between 0.60 and 0.97, with the boosted ensemble tree model being the best. Nevertheless, mineral contents were not found to be good predictors of TD, even if they control the evolution of the crack during the heat treatment. It was concluded that the findings of this study could serve as a valuable tool for assessing the thermal damage of rocks.