Optimum design of stone column-improved soft soil using multiobjective optimization technique

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Abstract

A combined simulation–optimization-based methodology is proposed to identify the optimal design parameters for granular bed–stone column-improved soft soil. The methodology combines a finite difference-based simulation model and an evolutionary multiobjective optimization model. A combined simulation–optimization methodology is developed for two different formulations: (a) the minimization of maximum settlement and the minimization of differential settlement subject to stress constraints; (b) the minimization of maximum settlement, the minimization of differential settlement and the maximization of the degree of consolidation subject to stress constraints. The developed methodology is applied to an illustrative system. Different scenarios are evaluated to examine critical field conditions. The solution results show that the modular ratio and the ultimate stress carrying capacity of the stone column are the most important parameters for optimal design. The obtained results also show the potential applicability of the developed methodology.

Introduction

Stone columns are commonly used to increase the bearing capacity and to reduce the settlement of soft soil. The use of stone columns also increases the rate of the consolidation of the soft clay. Granular beds are generally placed on top of the stone column-improved soft soil to provide a drainage path and to distribute the stresses coming from the superstructure. The choice of the proper stiffness, spacing and diameter of the stone columns is very important to improve an existing soft soil. Studies have shown that maximum settlement decreases as the stiffness of the stone column increases, but differential settlement (differential settlement is the settlement difference between the center of the stone columns and the mid-span of the column spacing) increases [1]. Therefore, the proper level of stiffness must be used to obtain an optimum value of the maximum and the differential settlement of the improved ground. It has been further observed that the rate of the consolidation of the soft soil increases as the stiffness of the stone column increases [2]. The maximum and differential settlement increases as the spacing-to-diameter ratio increases [1], whereas the rate of consolidation decreases as this ratio increases [2]. The properties of the soft soil and the granular bed also influence the settlement behavior of the improved ground. Therefore, it is necessary to estimate the proper parameters so that the optimum value of the maximum and differential settlement and the degree of consolidation can be achieved.

Numerous studies have focused on optimizing geotechnical structures such as slopes, tunnels and foundations [3], [4], [5], [6], [7], [8], [9], [10], [11], [12]. However, few studies have been conducted on stone column-improved soft soil to determine the optimal design parameters. In the present study, the appropriate design parameters of the granular bed–stone column-improved soft soil were estimated with a multiobjective optimization technique to obtain the optimum values of maximum and differential settlement and the degree of consolidation. The model proposed by Deb [1] was used as the basic simulation model for this analysis. A coupled simulation–optimization-based methodology is proposed by combining the basic simulation model and the evolutionary multiobjective optimization model NSGA-II [13].

Section snippets

Simulation model

A variant of the model proposed by Deb [1] is used as a simulation model for this analysis. Fig. 1 shows a granular fill–stone column-reinforced soft soil system. The granular fill is idealized as a Pasternak shear layer. The saturated soft soil is idealized by the Kelvin–Voigt model and the stone columns are idealized as stiffer non-linear springs. The non-linear behavior of the granular fill is incorporated in this study by assuming a hyperbolic variation of shear stress with shear strain. In

Results and discussion

Computational burden is an important factor for simulation–optimization-based methodologies because of the repetitive solution of the basic simulation model. The non-dominated fronts for different scenarios are for population sizes of 60 and 200 generations. The solutions show that there is not much change in the non-dominated front after 200 generations. The probability of crossover and mutations are 0.9 and 0.1, respectively. A higher index value (=15) for crossover and a lower index value

Conclusions

A linked simulation–optimization-based methodology is developed to estimate the optimum design parameters for granular bed–stone column-improved soft ground. The methodology combines a finite difference-based mechanical model to predict the behavior of stone column reinforced foundations with the evolutionary optimization algorithm NSGA-II. The developed methodology is applied to an illustrative system. It is observed from the two-objective optimization model that middle portion of the

References (24)

  • C.S. Desai et al.

    Parameter optimization and sensitivity analysis for disturbed state constitutive model

    Int J Geomech

    (2006)
  • Y. Wang et al.

    Economic design optimization of foundations

    J Geotech Environ Eng (ASCE)

    (2008)
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