The ability to predict the soil mechanical parameters swiftly is critical for off-road vehicle mobility. This paper introduces a novel interpretation methodology for determining critical soil mechanical parameters by impact penetration tests, enabling rapid and remote assessment of terramechanics properties. Initially, the method employs the Mohr-Coulomb constitutive model and the Coupled Eulerian-Lagrangian (CEL) finite element method to generate a dataset of soil impact penetration resistance and acceleration responses. Subsequently, a Radial Basis Function (RBF) neural network is employed as a surrogate model and integrated with the Nondominated Sorting Genetic Algorithm II (NSGA-II) to accurately interpret parameters such as density, cohesion, internal friction angle, elastic modulus, and Poisson's ratio. Experimental validation using sand and silty clay from Yangbaijing, Tibet, confirmed the accuracy and robustness of the method. The results indicate that the mean absolute percentage error for interpreted values was below 25%, with relative errors for some key parameters even below 10%. Furthermore, each single-condition calculation was completed on a standard computer in less than one minute. Comparative analyses with other algorithms, including MIGA and POS, demonstrated the superior performance of NSGA-II in avoiding local optima. The proposed interpretation framework offers a rapid, reliable, and remote solution for identifying the soil mechanical properties. Its potential applications range from disaster mitigation and emergency response operations to extraterrestrial soil exploration and other scenarios where in-situ investigations are challenging.

This study investigates the pore water pressure (PWP) behavior of soil around large-diameter open-ended thin- walled piles (LOTPs) during impact driving using a large deformation finite-element method. A comparative analysis of the PWP accumulation curves of the soil inside, outside, and below the LOTP tips with different diameters and wall thicknesses during impact driving is conducted under the same hammering solution. The PWP development is dependent on the absolute distance from the pile surface to the location of the soil and the dimensions of the LOTP. The excess pore water pressure (EPWP) accumulates and gradually dissipates, and its level decreases with increasing pile diameter. However, a negative excess pore water pressure (Ne-EPWP) is identified during hammering. Based on the above findings and analyses, a PWP prediction equation for LOTP during driving is proposed, and the predicted curves are compared with the numerical results. The influence of PWP accumulation after penetration of 2d (d is the LOTP internal diameter) does not increase significantly. This equation can provide the initial distribution field of PWP in saturated clay for LOTPs, thereby facilitating pile drivability analyses.