To evaluate the performance of dual-row batter pile wall (DRBPW) in deep excavations, a three-dimensional numerical model was established. The plastic hardening (PH) constitutive model in FLAC^3D was adopted, considering the hardening property of the soil. A series of parametric study was conducted to investigate the effect of different factors. By analyzing the maximum lateral displacement, the pile shaft deflection and bending moment of both the leading and trailing row, the effect of inclination angle, pile diameter, penetration depth, and row spacing on the behavior of DRBPW was determined. The following conclusions could be drawn: (1) The bearing capacity of DRBPW is quite larger than that of the dual-row vertical pile wall (DRVPW). With the increase of inclination angle, a substantial reduction of lateral displacement could be observed. However, the beneficial role of batter pile is almost negligible when the inclination angle is not larger than 5°. The recommended inclination degree of the batter pile is 10° to 15°. (2) The maximum displacement of the leading and trailing rows lies at a distance below the pile cap, while the maximum bending moment is located at a small distance below the dredging line. The maximum bending moment of the leading pile is approximately twice that of the trailing one, thereby indicating that the leading pile bear more lateral earth pressure than the trailing pile. (3) The pile diameter, penetration depth and row spacing should be maintained in a suitable range; otherwise, the DRBPW may fail earlier than expected. The slender ratios is recommend to be set not larger than 30. The penetration ratio should not be less than 0.22. The optimal row spacing for the DRBPW is four times the diameter.

The construction of modern city consists of many underground facilities, and one major concern is how to construct them safely and efficiently. Thus, the excavation-induced pile response needs to be evaluated. Dual-row batter pile wall (DRBPW) exhibits better performance than traditional dual-row vertical pile wall (DRVPW) in foundation pit engineering. However, the study of single pile subjected to excavation-induced soil movement behind DRVPW is rather limited, needless to say that of the DRBPW. An explicit finite difference method (FDM) was utilized to obtain the responses of isolated floating single pile (IFSP) near deep excavations braced by DRBPW. The responses of IFSP in the vicinity of foundation pit reinforced by DRBPW were compared to that of the DRVPW. The pile length, distance of pile from wall, excavation depth, working load, and Young’s modulus of pile were considered in the parametric study. The conclusions were as follows: (1) The DRBPW can minimize the influence on the existing pile; thus, the induced lateral displacement and bending moment of pile retained by DRBPW are smaller than that of DRVPW. (2) The excavation depth, pile location, and pile length have significant influence on the responses of IFSP adjacent excavation, while the working load and Young’s modulus of pile have diminutive influence. (3) The influence zone induced by excavation can be divided into two areas. The primary influence zone is the severely affected area where the induced deformation and bending moment are remarkable. The secondary influence zone is the moderately affected area where the induced deformation and bending moment are mild. The primary influence zone is within twice of the excavation depth. The secondary influence zone is 2.0–3.0 times that of the excavation depth. (4) The pile toe of IFSP has considerable lateral displacement during excavation, and attentions should be paid to the whole pile shaft during construction.

Accurate determination of constitutive model parameters is crucial for reliable numerical simulation in deep foundation pit engineering. This study presents an inverse analysis method using Multioutput Least-Squares Support Vector Regression (MLSSVR) optimized by the Gray Wolf Optimization (GWO) algorithm to invert key parameters of the Hardening Soil (HS) model. A case study on a foundation pit in the dredger fill stratum of Xiamen Railway integrates finite element simulation with machine learning. The proposed GWO-MLSSVR model demonstrates high predictive accuracy, with lateral displacement predictions closely matching field monitoring data and relative errors within 5% at various depths of measurement point. Compared to traditional inversion methods and MLSSVR models optimized by other algorithms, this approach significantly reduces prediction errors. Additionally, the influence of construction stages, input layer nodes, and training sample size on inversion performance is investigated. This method provides a practical and efficient solution for accurately obtaining soil parameters under complex soil conditions, thereby enhancing the reliability of geotechnical numerical simulations and offering valuable guidance for foundation pit design and safety assessment.

Offshore wind energy is a key contributor to sustainable energy, yet its development faces significant technological challenges, particularly in the design of substructures that interface with the marine environment. In this study, a comprehensive numerical analysis was conducted to investigate the mechanical behavior of a high-rise pile cap foundation under hydrostatic loading conditions. A high batter pile bearing foundation model was employed to examine the effects of pile inclinations, embedment depths, lateral loads, and cap elevations on foundation performance. The results indicate that the displacement and bending moment at the pile head decrease significantly as the pile inclination gradually increases. Similarly, as the embedding depth increases gradually, both the displacement and bending moment decrease significantly. Additionally, a positive batter pile exhibits greater bending moments and displacements than a negative batter pile, with the maximum bending moment occurring in the lower one-third of pile below the mudline. These findings provide valuable theoretical guidance for the design of offshore wind turbine foundations, recommending an inclination angle of 8–12° and an embedment depth of 12–15 m to enhance structural stability, economic efficiency, and construction feasibility.