Publications

This paper presents a laboratory investigation of the strain-dependent cyclic properties of a compacted tropical residual soil as measured in a resonant column and cyclic triaxial testing program. The mechanical properties were evaluated with respect to cyclic shear strain amplitude, initial void ratio, and confining pressure. It was shown that the existing models for the prediction of shear modulus reduction and damping ratio curves were not pertinent in the case of the compacted residual soil studied. Empirical equations were developed for the small-strain shear modulus and the normalized shear modulus, damping ratio, and pore water pressure ratio curves for void ratios between e = 1.00 and e = 1.50 and mean effective pressures of p′ = 50−300 kPa. The comparison of the models to the measured values suggest that the uncertainties associated with each of these models are lower than 20% of the predicted values. The results were established as part of a project for the construction of an embankment dam in the West Indies. However, the methodology as well as the model formulation framework presented in the article can be generalized to other residual soils and applied in all fields of geotechnical engineering.

No abstract is provided for this article.

Leakages of reservoirs are responsible for the loss of water resources and the spread of contaminants. We develop a methodology to detect leaks located at the bottom side of a reservoir with the minimally invasive mise-à-la-masse method, which involves the potential electrodes located at the ground surface around the reservoir and the current source and sink placed in and out of the reservoir, respectively. This method allows localizing the secondary current distribution associated with leakage using the distribution of potential recorded on a set of electrodes during the mise-à-la-masse experiment. An initial model based on the distribution of root mean square values between the observation and the simulation data is first given to the inversion algorithm. The Tikhonov regularization, which includes a weighting matrix and a minimum support function, is used to strengthen the detection resolution of the leak. 29 sandbox experiments show that the proposed method and inversion algorithm can localize a single leak. For a leak with a crack shape, the inversion algorithm detects the location of the leak with a small bias. When the leak lasts, a conductive zone may occur below the leak due to the increase of water content or ionic strength of the pore water. The occurrence of such a conductive body could affect the localization of the leak because the conductivity distribution may not be well-resolved. The effect is analyzed using synthetic experiments. The results show that the bias between the real leak and inversion results increases with the position and size of the undetected conductive zone. Two small-scale field tests were conducted to test the performance of the mise-à-la-masse method. The two leaks are properly identified. This study provides an efficient approach to detect the bottom leakage of reservoirs.

A probabilistic stability analysis of an embankment dam using in-situ measurements is presented in the paper. Three soil properties, including the dry density ( γ d ), the effective cohesion ( C ′ ) and the friction angle ( ϕ ′ ) are simulated by means of random variables based on in-situ measurements or laboratory test results, to consider the soil variability. Concerning the deterministic calculations, two models are developed in the study. The first one is a numerical model based on the finite difference method, and the second one is an analytical model based on the limit equilibrium method. For the latter, a two-step Genetic Algorithm (GA) is proposed to locate the best noncircular critical slip surface. These two models are both used for the safety factor evaluation of the studied dam and compared in a probabilistic framework in terms of safety factor distribution and failure probability. The employed reliability method for the probabilistic analysis is the Sparse Polynomial Chaos Expansion (SPCE). The failure probability and the safety factor distribution of the considered dam under normal exploitation conditions and seismic loading conditions are presented. The influence of the random variable distribution type on the probabilistic results is studied. In addition, a PCE-based Global Sensitivity Analysis (GSA) is embedded in order to investigate the contribution of each variable to the safety factor variance.

No abstract is provided for this article.

Tropical residual soils are found in different parts of the world and consist of mixtures of different types of soil such as sand, silt and clay, resulting in intricate microstructures and mechanical responses.In this context and inspired by the soil's composition, a 3D-DEM model is developed in which two different contact models are assigned among idealized spherical particles to represent the coarse and fine parts of the tropical soil with two distinct sets of numerical parameters.A simple linear rolling resistance contact model is used to represent the coarse, cohesionless, component, while a softer adhesive rolling resistance contact model with a linear approximation of the van der Waals attraction force is used for the fine, cohesive, component.The numerical coarse network is continuous in terms of interparticle contacts and represents the main skeleton of the DEM sample, whereas so-called fine contacts form a local force network between the coarse particles.After a parametric study on the effects of adopting such a numerical mixture, the model is calibrated for a drained compression triaxial test with a specific void ratio.In order to estimate the equivalent DEM model void ratio, a proportionality between the real soil void ratio and the DEM model void ratio 1 T. Mohamed, April 25, 2023 is efficiently employed.During the validation phase, successful model predictions are achieved on drained and undrained triaxial tests and cyclic tests with different strain amplitudes and moderate (hundreds of kPa) confining pressures.