This study presents a three-dimensional numerical analysis of natural convection during the postharvest storage of corn and wheat in a galvanized steel silo with a conical roof and floor, measuring 3 m in radius and 18.7 m in height, located in the Bajío region of Mexico. Simulations were carried out specifically for December, a period characterized by cold ambient temperatures (10–20 °C) and comparatively lower solar radiation than in warmer months, yet still sufficient to induce significant heating of the silo’s metallic surfaces. The governing conservation equations of mass, momentum, energy, and species were solved using the finite volume method under the Boussinesq approximation. The model included grain–air sorption equilibrium via sorption isotherms, as well as metabolic heat generation: for wheat, a constant respiration rate was assumed due to limited biochemical data, whereas for corn, respiration heat was modeled as a function of grain temperature and moisture, thereby more realistically representing metabolic activity. The results, obtained for December storage conditions, reveal distinct thermal and hygroscopic responses between the two grains. Corn, with higher thermal diffusivity, developed a central thermal core reaching 32 °C, whereas wheat, with lower diffusivity, retained heat in the upper region, peaking at 29 °C. Radial temperature profiles showed progressive transitions: the silo core exhibited a delayed response relative to ambient temperature fluctuations, reflecting the insulating effect of grain. In contrast, grain at 1 m from the wall displayed intermediate amplitudes. In contrast, zones adjacent to the wall reached 40–41 °C during solar exposure. In comparison, shaded regions exhibited minimum temperatures close to 15 °C, confirming that wall heating is governed primarily by solar radiation and metal conductivity. Axial gradients further emphasized critical zones, as roof-adjacent grain heated rapidly to 38–40 °C during midday before cooling sharply at night. Relative humidity levels exceeded 70% along roof and wall surfaces, leading to condensation risks, while core moisture remained stable (~14.0% for corn and ~13.9% for wheat). Despite the cold ambient temperatures typical of December, neither temperature nor relative humidity remained within recommended safe storage ranges (10–15 °C; 65–75%). These findings demonstrate that external climatic conditions and solar radiation, even at reduced levels in December, dominate the thermal and hygroscopic behavior of the silo, independent of grain type. The identification of unstable zones near the roof and walls underscores the need for passive conservation strategies, such as grain redistribution and selective ventilation, to mitigate fungal proliferation and storage losses under non-aerated conditions.

Grain storage in silos plays a fundamental role in preserving the quality and safety of agricultural products. This study presents a comparative evaluation of two-dimensional (2D) and three-dimensional (3D) mathematical models to predict the temperature and moisture distribution during unventilated corn storage in cylindrical silos with conical roofs. The models incorporate external temperature fluctuations, solar radiation, grain moisture equilibrium with air humidity via sorption isotherm (water activity), and grain respiration to simulate real-world storage conditions. The 2D model offers computational efficiency and is suitable for preliminary assessments but simplifies natural convection effects and underestimates axial temperature gradients. Conversely, the 3D model provides a detailed representation of heat and moisture transfer phenomena, capturing complex interactions such as buoyancy-driven flow and localized effects of solar radiation. The results reveal that temperature and moisture accumulation are more pronounced in the upper regions of the silo, driven by solar radiation and natural convection, with significant implications for large-scale silos where thermal inertia plays a key role. This dual modeling approach demonstrates that while the 2D model is valuable for quick evaluations, the 3D model is essential for comprehensive insights into thermal and moisture gradients. The findings support informed decision-making in silo design, optimization, and management, enhancing grain storage strategies globally.

This study presents a numerical investigation of natural convection in a two-dimensional inclined square cavity filled with air and subjected to differential heating. The effects of the Rayleigh number and cavity inclination on heat transfer and flow behavior were investigated for 10³ ≤ Ra ≤ 10⁹ and inclination angles of 0°, 15°, 30°, and 45°. The dimensionless Navier–Stokes and energy equations were solved using the finite-element method under the Boussinesq approximation with a steady laminar formulation. A structured quadrilateral mesh with boundary-layer refinement was employed near the differentially heated walls. Mesh-refinement tests and comparisons with benchmark data for the classical square cavity were used to assess the numerical accuracy of the model. The results show that the average Nusselt number increases with the Rayleigh number, reflecting the progressive intensification of buoyancy-driven heat transfer. The effect of inclination is non-monotonic and depends on the Rayleigh number. At Ra = 10⁴, the highest average Nusselt number is obtained at 45°, whereas for Ra ≥ 10⁵, the maximum is consistently observed at 15°. At Ra = 10⁹, the average Nusselt number is 54.475, 55.617, 53.224, and 49.408 for inclination angles of 0°, 15°, 30°, and 45°, respectively. The results indicate that moderate cavity inclination can enhance heat transfer by favorably modifying the interaction between buoyancy and the imposed thermal gradient, whereas larger inclinations progressively reduce the heat-transfer rate. The present results provide a systematic characterization of the coupled effects of Rayleigh number and cavity inclination within the scope of the steady two-dimensional formulation considered.