Thermal Conductivity of Binary Sand Mixtures Evaluated through Full Water Content Range

Abstract

Core Ideas Thermal conductivity and water content relationship based upon mixtures are distinct. Systematic change in particle fine fraction directly affects thermal conductivity. Strong correlation between density and thermal conductivity Campbell model well predicts thermal conductivity with all four parameters calibrated. Lu and Dong model well predicts thermal conductivity with both parameters calibrated. A soil's grain‐size distribution affects its physical and hydraulic properties; however, little is known about its effect on soil thermal properties. To better understand how grain‐size distribution affects soil thermal properties, specifically the effective thermal conductivity, a set of laboratory experiments was performed using binary mixtures of two uniform sands tightly packed with seven different mixing fractions over the full range of saturation. For each binary mixture, the effective thermal conductivity, λ, capillary pressure, hc, and volumetric water content, θ, were measured. Results demonstrated that the λ–θ relationship exhibited distinct characteristics based on the percentage of fine‐ and coarse‐grained sands. We further compared measured λ–θ properties with independent estimates from two semi‐empirical models (Campbell Model and Lu and Dong Model) to evaluate the models' applicability in relation to physically based parameters associated with changes in soil mixing (e.g., porosity and grain size). Both models were able to fit experimental data but to varying degrees based on the number of physically based parameters used. In general, model improvements are needed to capture the λ–θ relationship solely on physically based parameters.