Field performance of a genetic algorithm in the settlement prediction of a thick soft clay deposit in the southern part of the Korean peninsula

Abstract

Long-term settlement data of a thick soft clay deposit improved by vertical drains frequently shows different field settlement behaviors from laboratory-driven predictions by conventional theories due to the variability and uncertainty of the soil properties, modeling simplifications, and types of prediction methods. This paper presents the field application of a back-analysis method based on a genetic algorithm (GA) to evaluate the performance of a new settlement prediction method compared with conventional graphical settlement prediction methods, such as the hyperbolic method and the Asaoka method. The GA back-analysis method shows better flexibility in modifying surcharging plans and adaptability to multi-layered thick soft soil deposits at the early stages of post-construction settlement. Thus, this new settlement prediction method enables geotechnical engineers to subsequently modify the heights of surcharge fills in accordance with field settlement data monitored in the interim for rapid and cost-effective construction. The comparative results show that the GA back-analysis method is capable of superior field performance in settlement predictions compared with two conventional graphical methods, within a margin of less than 200mm in a thick soft clay deposit with multiple layers under complex loading conditions.