Prediction of Compression and Permeability Characteristics of Mine Tailingsusing Natural Computation and Large-strain Consolidation Framework

摘要

Prediction of consolidation behavior of soft soil deposits, such as minetailings and hydraulic fills, is an essential and routine exercise in mining and dredgingindustries using large-strain consolidation theory. The values of compressibility andhydraulic conductivity deduced from settlement vs. time response are influenced bythe selected form of e ? logσ ′ and e?k relationship. In this paper, we propose amethod of back-analysis to deduce compressibility and hydraulic conductivity of softsoils from its settlement vs. time response. The curve-fitting parameters for the nonlinearrelations between e ? logσ ′ and e?k are inferred using the settlementresponse and the initial conditions of the soil for the cases of self-weightconsolidation of oil sands mature fine tailings (MFT). A piecewise-linear model oflarge-strain consolidation is used. The inverse analysis is carried out using naturalcomputation algorithms. It is demonstrated that accurate deduction of compressibilityand hydraulic conductivity is possible using natural computation algorithms and thatthese algorithms are much more stable ad accurately predicts the parameters.