Benefit of Unsaturated Soil Mechanics Approach on the Modeling of Early-Age Behavior of Rammed Earth Building

Rammed earth has the potential to reduce the carbon footprint and limit the energy consumption in the building sector due to its sustainable characteristics. Still, its use is not generalized due to a lack of understanding of the material behavior, notably its sensitivity to water. The coupled hydro-mechanical behavior has been recently studied in the framework of unsaturated soil mechanics, using suction as the parameter to represent the hydric state. This dependency of the mechanical behavior on the hydric state leads to uncertainty of the drying period required to progress in the construction process. Notably, the drying period before building the next floor is unknown. To determine the drying period, thermo-hydro-mechanical coupled finite element method simulations were carried out on a single wall by using the unsaturated soil mechanics approach and safety criterion recommendations from the practical guide for rammed earth construction in France. It was determined that it takes significant time for the construction of additional floor both in ‘summer-like’ and ‘winter-like’ environmental conditions, whereas the walls were far away from the ultimate failure state. Thus the drying periods were overestimated. It was concluded that the safety criterion from the practical guide is very conservative and drying periods can be reduced without significantly compromising the safety factor.

The role of unsaturated soil mechanics in unconventional tailings deposition

Desiccation (water loss by drying or freeze-thaw sufficient to generate matric suction), can influence the performance of a tailings deposit both positively and negatively. The significance of desiccation is largest in tailings that have been dewatered prior to deposition, by thickening or filtration. Such tailings can be “stacked” or deposited with a significant slope, which usually implies that a substantial volume of tailings remain above water. Under such conditions the tailings, by accident or by design, may undergo desiccation before burial by fresh tailings. Desiccation can contribute substantially to strength, above and beyond the contribution arising from increase in density, through stress history effects. For some deposits, it is required practice that at least some tailings undergo desiccation to improve, particularly when those tailings for a structural part of a deposit. If, however, tailings remain exposed to the atmosphere in an unsaturated state for some period of time, this may have potential negative consequences through oxidation of sulphide minerals and the formation of acid drainage. This paper describes previous research on the strength gained through desiccation in tailings, and on modelling work that incorporates unsaturated soil phenomena into consolidation analysis. Both types of research are applied to a real field site, providing an example of how novel improvements to tailings management can arise out of application of principles of unsaturated soil mechanics.

A Framework for Interpreting Lateral Swelling Pressure in Unsaturated Expansive Soils

Lateral swelling pressure (LSP) develops when expansive soil volume increment associated with water infiltration is restrained in a confined domain, for example, due to construction of civil infrastructure. In this paper, initially a flowchart is developed to highlight various key factors that influence the LSP mobilization according to lab and field studies collected from previous literature studies. Then extending unsaturated soil mechanics, a theoretical framework is proposed for illustrating the LSP mobilization in the field against retaining structures and pile foundations under different boundary conditions, respectively. An example problem for a basement wall and a pile foundation constructed in a typical expansive soil from Regina, Canada, is presented to illustrate the proposed theoretical framework. The framework and corresponding analysis presented in this paper can facilitate to provide rational designs of geotechnical infrastructures in expansive soils.

Transient unsaturated shaft resistance of a single pile during water flow

The pile foundations’ design is commonly based on the soil’s initial in situ condition during field investigations or the assumption of its saturated condition. However, for some regions in tropical weather, a significant part of the pile shaft remains above the groundwater table (i.e., unsaturated condition) during the structure’s lifespan. Only considering a constant moisture condition in the soil (unsaturated or saturated) can overestimate or underestimate the pile design. The soil shear strength governs the shaft resistance of a pile and depends on the soil matric suction, which is significant in the unsaturated zone. In this study, an analytical model is proposed to estimate piles’ unsaturated shaft resistance and encourage the use of unsaturated soil mechanics in engineering practice. The mathematical equation involves well-known parameters from unsaturated soil mechanics theory and simulates the pile shaft resistance variation with its length and time, considering a unidimensional infiltration downwards (e.g., during a rainfall event).

Estimating soil-water characteristic curve based on soil type and best-fitting regressions derived from a simplified method using Aburra Valley dataset

In unsaturated soil mechanics, many attempts have been made to estimate the SWCC based on soil texture and grain-size distribution. This paper proposes a simplified method to estimate the soil-water characteristic curve (SWCC) for both coarse and fine-grained soils using SWCC data and machine learning computer code in the Aburra Valley. Fredlund and Xing parameters has been used to estimate the SWCC correlations. Soil samples collected from field survey were subjected to laboratory testing, SWCCs were estimated using filter paper method. Each SWCC data set from Aburra Valley was fitted with Fredlund and Xing curve using multiple regression analysis, correlations were derived for those four parameters based on predictors derived from machine learning. The proposed method gives a good estimation and low residual errors of the SWCC.