A deep-learning method for evaluating shaft resistance of the cast-in-site pile on reclaimed ground using field data

This study proposes a deep learning-based approach for shaft resistance evaluation of cast-in-site piles on reclaimed ground, independent of theoretical hypotheses and engineering experience. A series of field tests was first performed to investigate the characteristics of the shaft resistance of cast-in-site piles on reclaimed ground. Then, an intelligent approach based on the long short term memory deep-learning technique was proposed to calculate the shaft resistance of the cast-in-site pile. The proposed method allows accurate estimation of the shaft resistance of cast-in-site piles, not only under the ultimate load but also under the working load. Comparisons with empirical methods confirmed the effectiveness of the proposed method for the shaft resistance estimation of cast-in-site piles on reclaimed ground in offshore areas.