Parameter Identification of Consolidation Settlement Based on Multi-objective Optimization

Due to the complexity of natural ground condition, consolidation settlement is usually difficult to predict. In this study, a Pareto multi-objective optimization based back analysis method for consolidation settlement is presented in this study. The model is a coupled flow and deformation model for unsaturated soil foundation which is implemented in the interactive multiphysics software environment COMSOL. A multi-objective optimization algorithm AMALGAM is adopted to identify soil parameters based on multiple types of measurements. A case history of a highway trial embankment is used to demonstrate the proposed back analysis method. The observed displacement and pore-water pressures are utilized simultaneously to estimate the mechanical and hydraulic parameters of the soil. The results show that the bi-objective Pareto front exhibits a sharp rectangular pattern. When only displacement is used in back analysis, the numerical model with optimized soil parameters cannot simulate pore-water pressure very well, and vice versa. However, the back analyzed soil parameters of the compromise solution from the bi-objective back analysis can reasonably simulate both the displacement and pore-water pressure and predict the settlement well.

[1]  KnabeTina,et al.  Calibration of constitutive parameters by inverse analysis for a geotechnical boundary problem , 2012 .

[2]  De’an Sun,et al.  Analytical solution to one-dimensional consolidation in unsaturated soils under loading varying exponentially with time , 2010 .

[3]  Jared L. Cohon,et al.  Multiobjective programming and planning , 2004 .

[4]  Van Genuchten,et al.  A closed-form equation for predicting the hydraulic conductivity of unsaturated soils , 1980 .

[5]  Kalyanmoy Deb,et al.  Finding Knees in Multi-objective Optimization , 2004, PPSN.

[6]  Exact solutions for one‐dimensional consolidation of single‐layer unsaturated soil , 2012 .

[7]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[8]  Akira Murakami,et al.  Prediction of embankment behavior of regulating reservoir with foundation improved by vacuum consolidation method , 2014 .

[9]  Jun-mo Kim A fully coupled finite element analysis of water-table fluctuation and land deformation in partially saturated soils due to surface loading , 2000 .

[10]  L. M. Zhang,et al.  Analytical solution to 1D coupled water infiltration and deformation in two‐layer unsaturated soils , 2012 .

[11]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[12]  H. Haario,et al.  An adaptive Metropolis algorithm , 2001 .

[13]  Nasser Khalili,et al.  A meshfree method for fully coupled analysis of flow and deformation in unsaturated porous media , 2013 .

[14]  Seung-Rae Lee,et al.  An equivalent model and back-analysis technique for modelling in situ consolidation behavior of drainage-installed soft deposits , 1997 .

[15]  Delwyn G. Fredlund,et al.  A numerical study of coupled consolidation in unsaturated soils , 1998 .

[16]  Jasper A Vrugt,et al.  Improved evolutionary optimization from genetically adaptive multimethod search , 2007, Proceedings of the National Academy of Sciences.

[17]  Hyun Il Park,et al.  Settlement Prediction in a Vertical Drainage-Installed Soft Clay Deposit Using the Genetic Algorithm (GA) Back-Analysis , 2009 .

[18]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..