In this paper, the results of a series of experiments on wave-induced pore-water pressures around a mono-pile are presented. Unlike the previous study, in which the mono-pile was fully buried, the mono-pile in this study was installed at 0.6 m below the seabed surface. In this study, we focus on the pore-water pressures around the mono-pile and beneath the pile. The experimental results lead to the following conclusions: (1) the seabed response is more pronounced near the surface (in the region above 30 cm deep), and the rate of pore pressure attenuation gradually slows down. For the region below 0.3 m, the response is much smaller; (2) in general, along the surface of the pile, pore pressures increase as the wave height and wave period increase; (3) the spatial distribution of pore pressure near the pile will vary with different wave periods, while the wave height only has a significant effect on the amplitude; and (4) At z = −0.15 m, the pore pressure in front of the pile is the largest, while at the point 0.1 m below the bottom of the pile, the largest pore pressure occurs behind the pile.

Numerous studies have proven that natural particle-packed granular materials, such as soil and rock, are consistent with the grain-size fractal rule. The majority of existing studies have regarded these materials as ideal fractal structures, while few have viewed them as particle-packed materials to study the pore structure. In this study, theoretical analysis, the discrete element method, and digital image processing were used to explore the general rules of the pore structures of grain-size fractal granular materials. The relationship between the porosity and grain-size fractal dimension was determined based on bi-dispersed packing and the geometric packing theory. The pore structure of the grain-size fractal granular material was proven to differ from the ideal fractal structure, such as the Menger sponge. The empirical relationships among the box-counting dimension, lacunarity, succolarity, grain-size fractal dimension, and porosity were provided. A new segmentation method for the pore structure was proposed. Moreover, a general function of the pore size distribution was developed based on the segmentation results, which was verified by the soil-water characteristic curves from the experimental database.

The morphology of particles formed in different environments contains critical information. Thus, the rapid and effective reconstruction of their three-dimensional (3D) morphology is crucial. This study reconstructs the 3D morphology from two-dimensional (2D) images of particles using artificial intelligence (AI). More than 100,000 particles were sampled from three sources: naturally formed particles (desert sand), manufactured particles (lunar soil simulant), and numerically generated digital particles. A deep learning approach based on a voxel representation of the morphology and multi-dimensional convolutional neural networks was proposed to rapidly upscale and reconstruct particle morphology. The trained model was tested using the three particle types and evaluated using different multi-scale morphological descriptors. The results demonstrated that the statistical properties of the morphological descriptors were consistent for the real 3D particles and those derived from the 2D images and the model. This finding confirms the model’s validity and generalizability in upscaling and reconstructing diverse particle samples. This study provides a method for generating 3D numerical representations of geological particles, facilitating in-depth analysis of properties, such as mechanical behavior and transport characteristics, from 2D images.

Investigations into the Wenchuan earthquake (2008, China) demonstrated that landslides were concentrated in the near‐fault areas, and numerous large‐scale landslides occurred in slopes with weak interlayers. A mathematical model was established based on the shear beam theory, while a numerical model was developed based on the discrete element method which perfectly matched layer boundary theory. Through a theoretical analysis and numerical simulation, the dynamic response and failure modes of the slope with a weak interlayer under the near‐fault ground motion were studied. It was found that a combined effect took place between the near‐fault ground motion and the weak interlayer, causing the slope near a fault to be destroyed more easily. The coupling between the near‐fault ground motion and the weak interlayer leads to a maximum amplification effect of the slope. The existence of a weak interlayer induces nonconforming vibration between the upper and the lower rock masses of the interlayer. The variation in the amplification effect along the slope elevation is related to the ratio of the input seismic period to the natural slope period. Under horizontal ground motion, weak interlayers will be subjected to impacting and shearing action. The failure mode of the slope with a weak interlayer under near‐fault ground motion can be expressed as a trailing edge tension crack, as well as weak interlayer impacting and shearing failure.

Dispersion forces (van der Waals force and Casimir force) originating from quantum fluctuations are crucial in the cohesion of microscale and nanoscale particles. The nonadditivity of these forces and the complex geometry of realistic particles make conventional additive algorithms produce unacceptable errors, and it is experimentally challenging to identify the contribution of dispersion forces from the many forces that constitute the cohesion. In this study, we use the fluctuating surface current technique, an exact scattering theory-based nonadditive algorithm, to accurately quantify the influence of geometry on dispersion forces. To characterize the complex geometries, we employ a data-adaptive spatial filtering method and three-level descriptors. Our results determine the influence of multiscale surface fluctuations on dispersion forces. Additionally, we establish a convenient formula for predicting the dispersion forces between realistic particles with complex shapes from the exact Lifshitz solution via multistage corrections.