Helical anchors are widely used in engineering to resist tension, especially during offshore wind energy harvesting, and their uplift behavior in sand is influenced by many factors. Experimental studies are often used to investigate these anchors; however, scale effects are inevitable in 1× g model tests, soil conditions for in situ tests are challenging to control, and centrifuge tests are expensive and rare. To make full use of the limited valid data and to gain more knowledge about the uplift behaviors of helical anchors in sand, a prediction model integrating gradient-boosting decision trees (GBDT) and particle swarm optimization (PSO) was proposed in this study. Data obtained from a series of centrifuge tests formed the dataset of the prediction model. The relative density of soil, embedment ratio, helix spacing ratio, and the number of helices were used as input parameters, while the anchor mobilization distance and the ultimate monotonic uplift resistance were set as output parameters. A GBDT algorithm was used to construct the model, and a PSO algorithm was used for hyperparameter tuning. The results show that the optimal GBDT model accurately predicted the anchor mobilization distance and the ultimate monotonic uplift resistance of helical anchors in dense fine silica sand. By analyzing the relative importance of influencing variables, the embedment ratio was found to be the most significant variable in the model, while the relative density of the fine silica sand soil, the helix spacing ratio, and the number of helices had relatively minor influence. In particular, the helix spacing ratio was found to have no influence on the capacity of adjacent helices when S/D > 6.

Helical piles with small sizes are widely used in traditional civil engineering infrastructure application, especially in onshore electrical power industry. The floating offshore wind power industry has taken an interest in helical piles because of their rapid installation and ability to support immediate loading. Compared with onshore structures, wind power structures suffer larger external load and it becomes necessary to increase the overall size of helical piles, leading to considerable load capacity provided by the shaft, which is typically neglected for a light structure. In this paper, the undrained uplift capacity of helical piles was studied using finite-element limit analysis. The analysis explored various diameter ratios of the shaft to the plate and embedment depths, as well as different interface conditions. The local bearing capacity on the plate was also explored for attached and vented interface conditions. The failure mechanisms of a helical pile were presented to explain the mutual influence between plate anchor and shaft on the uplift capacity. Algebraic expressions for the uplift capacity of a helical pile were proposed. Engineers may use these expressions to improve the accuracy of their estimates for the uplift capacity of helical piles.

Helical piles are utilized worldwide as foundations for onshore infrastructure, providing fast installation and high capacity. Their unique advantages have led to their potential as an alternative to monopile foundations for offshore wind turbines. One challenge in their service life is dealing with combined loading caused by wind, waves, current, and the weight of the structure itself. While research has focused on helical piles’ capacity for uniaxial tensile loads, there is limited knowledge regarding their performance under combined loads. This study used FEM analysis to investigate the impact of aspects such as helix-to-shaft diameter ratios and helix position on the capacity and failure mechanisms of hollow shaft single-plate helical piles in clay. With 561 analysis cases under both uniaxial and combined loading, failure envelopes were evaluated for various helix-to-shaft diameter ratios and positions. The study revealed a linear positive correlation between helix-to-shaft diameter aspect ratios and load-bearing ability, while the effect of helix positioning on failure envelopes was more complex and nonlinear. The outcomes from this comprehensive analysis enabled the development of a formula to predict the bearing capacity of helical anchors under combined loading.