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Computational modeling demonstrates how particle reorganization impairs heat transfer in saturated porous media, indicating key controls for underground thermal storage.
This study develops a validated pore-scale numerical framework to investigate particle reorganization and thermo-hydrodynamic processes in water-saturated porous media, with aquifer thermal energy storage considered as a potential application background. The discrete element method models particle dynamics, incorporating DLVO theory-based forces. The double-distribution-function lattice Boltzmann method simulates fluid flow and heat transfer, with fluid-solid coupling achieved via the partially saturated method. The framework is validated against laboratory chromatography column experiments. The model systematically analyzes the influence of five selected parameters—medium length ( L ), seepage velocity ( v ), medium porosity ( ε ), particle size ( d ), and ionic strength ( I )—on pore structure evolution and thermal behavior. Results indicate that increases in L , d , or I enhance particle aggregation and clogging, altering the pore structure, which induces flow attenuation and suppresses convective heat transfer. Conversely, higher ε and v facilitate particle transport, improve permeability, and accelerate thermal equilibration. Based on the 25-case orthogonal-design dataset, this study further develops a multiple linear regression model to characterize the outlet-temperature response. The ANOVA results indicate that medium length and seepage velocity contribute more strongly to the variation in outlet temperature than the other selected parameters.
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Ma et al. (2026) studied this question.
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