Moisture and suction variation beneath pavement contribute significantly to the volumetric deformation of expansive subgrade in response to climatic loading. In order to quantify the damage due to climatic loading, estimation of moisture, and suction variation in pavement subgrade is of paramount importance. The objective of the current study is to investigate the moisture and suction variation in response to precipitation events with the aid of numerical modeling in the unsaturated pavement subgrade. In unsaturated soils where the voids are filled with both water and air, the SWCC describes the volume of the voids that remain filled with water as the soil drains pore water. The SWCC has been identified as the vital soil information required to analyze seepage, stability, and volume change problems involved in unsaturated soils. However, the selection of unsaturated flow parameters is typically laboratory-based which represents specific conditions rather than a dynamic scenario of the field. In this study, an attempt was undertaken to conduct numerical modeling using field generated unsaturated flow parameters along with five other predictive models. Results indicated the distinct variation of moisture and suction distribution in subgrade from the same rainfall event while using laboratory versus field generated SWCC unsaturated flow parameters. In addition, predicted model yielded output was also varying with the field generated parameters’ output. Instead of using laboratory-generated static parameters, it was found that field generated dynamic unsaturated flow parameters were able to capture better suction variation at the pavement subgrade.
Numerical modeling of the influence of the gas-hydrodynamic flow parameters on streamlined surface icing
