Many works in the field of science and engineering, such as agronomy and building science, are physically related to soils and require an accurate determination of temperature and moisture content spatial distributions. In the building science area, for example, mathematical models are developed to provide better indoor thermal comfort with lower energy consumption and, mainly in low-rise buildings, the heat and moisture transfer through soils plays an important role on the energy and mass balances. Although, the presence of moisture can strongly affect the temperature distribution in soils due, especially, to the evaporation and/or condensation mechanisms and to the strong variation of their thermophysical properties, building simulation codes normally do not take into account the soil moisture effects for predicting the ground heat transfer. Therefore, in order to calculate the temperature profiles in a more accurate way, a computational code has been developed and conceived to model the coupled heat and moisture transfer in soils. The presented methodology is based on the theory of Philip and De Vries, using variable thermophysical properties for two types of soil with different chemical composition and porous size distribution. The governing equations were discretized using the finite-volume method, and a three-dimensional model was used for describing the physical phenomena of heat and mass transfer in unsaturated moist porous soils. The robust MultiTriDiagonal-Matrix Algorithm was used to solve this strongly-coupled problem, allowing one to use high time steps for long-term simulations. In conclusion, effects of boundary conditions for the soil, such as solar radiation, water table, and adiabatic and impermeable surfaces on the temperature and moisture content profiles, were presented. A sensitivity analysis of grid refinement and time step is presented as well. Additionally, daily average temperatures and moisture contents for different depths are also shown and compared for sandy silt and backfill soils.
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