A newly developed line-style sand pluviator has been calibrated to prepare repeatable sand specimens of specific statuses of compactness and homogeneity for laboratory tests. Sand is falling via a bottom slot of a fixed hopper, and by moving the sample container under the slot, the container is evenly filled with sand. The pluviator is designed with high flexibility: The falling height of sand, the hopper's opening width and the relative moving speed between the hopper and the sample box can be easily adjusted. By changing these control factors, sand specimens of a wide range of densities can be prepared. A series of specimen preparation was performed using the coarse Merwede River sand. Performance of the pluviator was systematically evaluated by exploring the alteration of achievable density, as well as checking the homogeneity and fabric of the prepared samples by CT scanning. It was found that the density of prepared coarse sand samples has monotonic correlations with none of the three control factors. Furthermore, CT scanning results suggested that the prepared samples exhibited excellent homogeneity in the horizontal direction but periodical alteration of density in the vertical direction. Based on these calibration test results, a preliminary hypothesis is proposed to describe the general working principles of this type of pluviators a priori, illustrating the mechanisms dominating the non-monotonic correlations between control factors and the relative density as well as the vertically prevalent heterogeneity of specimens. Accordingly, practical recommendations are made in a unified framework in order to lessen the load of similar calibration work.

The use of sand-tire chip mixtures in construction industry is a sustainable and environmentally friendly approach that addresses both waste tire disposal and soil improvement needs. However, the addition of tire chip particles to natural soils decreases maximum shear modulus (G_max), but increases compressibility, which can be potential drawbacks. This study examines the effect of overconsolidation stress history on the maximum shear modulus (G_max) of rigid-soft mixtures with varying size ratios (SR) and tire chip contents (TC) by measuring the wave velocity through a 1-D compression test during loading and unloading. The results demonstrate that the G_max of tested mixtures in the normally consolidated state increased with increasing SR and decreasing TC. However, the tested mixtures with a smaller SR exhibited a greater increase in G_max during unloading because of the active pore-filling behavior of the smaller rubber particles and the consequent increased connectivity between sand particles. The SR-dependent impact of the overconsolidation stress history on G_max was verified using the ratio between the swelling and compression indices. Most importantly, this study reveals that the excessive settlement and lower G_max of rigid-soft mixtures can be overcome by introducing an overconsolidated state in sand-tire chip mixtures with low TC.

This paper presents a logarithmic shear deformation theory to study the thermal buckling response of power-law FG one-dimensional structures in thermal conditions with different boundary conditions. It is assumed that the functionally graded material and thermal properties are supposed to vary smoothly according to a contentious function across the vertical direction of the beams. A P-FG type function is employed to describe the volume fraction of material and thermal properties of the graded (1D) beam. The Ritz model is employed to solve the thermal buckling problems in immovable boundary conditions. The outcomes of the stability analysis of FG beams with temperature-dependent and independent properties are presented. The effects of the thermal loading are considered with three forms of rising: nonlinear, linear and uniform. Numerical results are obtained employing the present logarithmic theory and are verified by comparisons with the other models to check the accuracy of the developed theory. A parametric study was conducted to investigate the effects of various parameters on the critical thermal stability of P-FG beams. These parameters included support type, temperature fields, material distributions, side-to-thickness ratios, and temperature dependency.

Monitoring and managing the condition of underground utilities is crucial for ground stability. This study aims to determine whether images obtained using ground penetrating radar (GPR) accurately reflect the characteristics of buried pipelines through image analysis. The investigation focuses on pipelines made from different materials, namely concrete and steel, with concrete pipes tested under various diameters to assess detectability under differing conditions. A total of 400 images are acquired at locations with pipelines, and for comparison, an additional 100 data points are collected from areas without pipelines. The study employs GPR at frequencies of 200 MHz and 600 MHz, and image analysis is performed using machine learning-based convolutional neural network (CNN) techniques. The analysis results demonstrate high classification reliability based on the training data, especially in distinguishing between pipes of the same material but of different diameters. The findings suggest that the integration of GPR and CNN algorithms can offer satisfactory performance in exploring the ground's interior characteristics.

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.

In northern China, abundant summer rainfall and a higher water table can weaken the soil due to salt heave, collapsibility, and increased moisture absorption, thus the chlorine saline soil (silty clay) needs to be stabilized prior to use in road embankments. To optimize chlorine saline soil stabilizing programs, unconfined compressive strength tests were conducted on soil treated with five different stabilizers before and after soaking, followed by field compaction test and unconfined compressive strength test on a trial road embankment. In situ testing were performed with the stabilized soils in an expressway embankment, and the results demonstrated that the stabilized soil with lime and SH agent (an organic stabilizer composed of modified polyvinyl alcohol and water) is suitable for road embankments. The appropriate addition ratio of stabilized soil is 10% lime and 0.9% SH agent. SH agent wrapped soil particles, filled soil pores, and generated a silk-like web to improve the moisture stability, strength, and stress-strain performance of stabilized soil.

Micropiled raft has been used to support the existing and new structures or to provide the seismic reinforcement of foundation systems. Recently, research on micropile or micropiled raft has been actively conducted as the usage of micropile has increased, and the reinforcement effect of pile for the raft, the pile installation methods, and methods for calculating the bearing capacity of micropiled raft have been proposed. In addition, existing research results show that the behavior of this foundation system is different depending on the pile conditions and can be greatly influenced by the characteristics of the upper or lower ground depending on the conditions of pile. In other words, considering that the micropile is a friction pile, it can be predicted that the reinforcing effect of micropile for the raft and the bearing capacity of micropiled raft may depend on the cohesion of upper soil layer depending on the pile conditions. However, existing studies have limitations in that they were conducted without taking this into account. However, existing studies have limitations as they have been conducted without considering these characteristics. Accordingly, this study investigated the reinforcing effect of micropile and the bearing characteristics of micropiled raft by varying the cohesion of upper soil layer and the stiffness of pile which affect the behavior of micropiled raft. In this results, the reinforcing effect of micropile on the raft also increased as the cohesion of soil layer increased, but the reinforcing effect of pile was more effective in ground conditions with decreased the cohesion. In addition, the relationship between the axial stiffness of micropile and the bearing capacity of micropiled raft was found to be a logarithmic linear relationship. It was found that the reinforcing effect of micropile can increase the bearing capacity of raft by 1.33~ 3.72 times depending on the cohesion of soil layer and the rigidity of pile.

This study proposes a two-dimensional hyperbolic soil spring model for mat foundations in clays subjected to vertically uniform loads to simplify the complexity of three-dimensional finite element analysis on mat foundations. The solutions from three-dimensional finite element analysis were examined to determine the hyperbolic model parameters of the soil springs underneath the slab. Utilizing these model parameters, normalized functions across the middle section of the mat were obtained. The solutions from the proposed model, along with the approximate finite difference analysis of the mat in clays under vertical load, were found to be consistent with those from the three-dimensional finite element analysis. The authors conclude that the proposed method can serve as an alternative for the preliminary design of mat foundations.