Intelligent back analysis using clonal selection algorithm in calculating equivalent top loading curve using O-cell test data

The bearing behaviour of larger-diameter piles significantly influences the performance of subway station construction using the pile foundation pile-beam-arch (PBA) approach. This paper proposes a numerical method combined with back analysis optimized by the clonal selection algorithm (CSA) to construct an equivalent top-loading (ETL) curve using the field O-cell test data. The test data are used to verify the proposed method. The behaviour of large-diameter piles is analysed based on the test data. In the specific conditions of this study, the optimal positioning of the self-equilibrium point is determined to be within a range of 0.10 to 0.25 times the pile length from the bottom of the pile. In addition, the effects of pile diameter, length, and buried depth on the empirical factor, self-equilibrium factor, and ultimate bearing capacity of the original pile are investigated. The influence of the loading direction on the side friction resistance is minimal. The ratio of the total skin friction to the ultimate bearing capacity increase as the pile length and buried depth, but decrease when the pile diameter increases.