Ant Colony Optimization Method for Design of Piled-Raft Foundations (DFI 2013 Student Paper Competition Winner)

Abstract

Abstract In comparison to conventional piled foundations, piled-raft foundations provide a more economical solution to support high-rise buildings constructed on compressible soils. In this type of foundation, the bearing capacity of the underlying soil is taken into account in supporting the superstructure loads, and the piles are placed to control both the total and differential movements of the superstructure. Currently, there are no universally accepted methods to design piled-raft foundations including the selection of the piles locations and dimensions. Most piled-raft foundation designs are based on empirical methods and the experience of designers. However, piled-raft foundations are massive and expensive. Therefore, developing methodologies for their optimal design could significantly help minimize their otherwise high construction costs and would make them more feasible and common practice. This paper examines the capability of the ant colony optimization (ACO) algorithm to optimize piled-raft foundations. The soil-pile interactions are taken into account by modeling the side and tip capacities of the piles using the nonlinear p-y, t-z, and Q-z springs in the OpenSees platform. The soil-raft interaction is taken into consideration using the Winkler springs beneath the raft. The objective of the optimization problem is to minimize the volume of the foundation by taking the number, configuration, and penetration depth of the piles, as well as the thickness of the raft, as design variables. The side and tip forces of the piles, the pressure applied on the underlying soil, and the total and differential movements of the foundation under the serviceability limit state are the constraints adopted for the optimization problem. Results indicate that the ACO algorithm is a suitable method for optimal design of piled-raft foundations. Findings of the study also indicate that including soil nonlinearity in the analysis (as opposed to a linear elastic soil model) can lead to a more economical design for these foundation systems.