Prediction of Hydraulic Conductivity Function Parameters of Slurries Using Hybrid Metaheuristics Approach

The self-weight consolidation behavior of slurries like dredged clay and mine tailings is governed by the finite-strain consolidation theory. This theory considers the hydraulic conductivity and compressibility of slurries as functions of the void ratio. The determination of these material functions is essential for understanding the settlement behavior of the concerned materials which is necessary for the safe and efficient disposal of these materials. The experimental procedures for the determination of these functional relations need elaborate setups and are time-consuming. Therefore, it is convenient to adopt methods based on numerical techniques for this purpose. In this paper, an inverse analysis method is proposed for the estimation of hydraulic conductivity function parameters from the settlement versus time behavior and initial conditions of slurry materials obtained from the settling column test. The finite difference solution of the governing equation for finite-strain consolidation was used for the forward analysis. The inverse analysis was carried out using Particle Swarm Optimization (PSO) algorithm combined with a gradient-based optimization algorithm fmincon. The method was tested using the synthetic settlement response of two slurries. The shortcomings of fmincon and PSO algorithms were discussed. The proposed method of back analysis estimated the hydraulic conductivity function parameters accurately when the compressibility function is known and is assumed to be time-invariant.