A Numerical Simulation of Moisture Reduction in Fine Soil Subgrade with Wicking Geotextiles.

A new wicking geotextile is proposed to control the water content of fine-grained soil subgrade. By comparing the spatial distribution of volumetric water content and matric suction before and after the installation of the wicking geotextile, the effectiveness of the geotextile in controlling the subgrade humidity is evaluated. Firstly, the hydraulic parameters of the wicking geotextile are obtained through laboratory tests using a pressure plate apparatus. Then, a numerical model for water flow in the subgrade is established using COMSOL to obtain the spatial distribution characteristics of humidity in the subgrade under different groundwater levels (2~8 m). The results show the wicking geotextile exhibits strong hydrophilicity, low water retention, and high horizontal permeability. Compared to the subgrade without geotextile, the water content of the soil above the geotextile decreases significantly by 7.6~9.6% at groundwater levels of 4~8m, while the saturation decreases by 18.3~23.0%, and the matric suction increases by 2~2.3 times. The wicking fabric functions as an effective drainage material to serve as a capillary barrier in the cross-plane direction and an effective drainage tunnel to transport water in the in-plane direction. The dynamic resilient modulus of the subgrade increases by 23.2~43.6%. The wicking geotextile effectively absorbs and drains weakly bound water in unsaturated soil due to the matric suction difference and its horizontal drainage capacity to improve the bearing capacity of the subgrade. It suggests that using wicking geotextile for drainage and reinforcement in fine-grained soil subgrades with groundwater levels ranging from 4 to 8 m is beneficial.

Lightweight Tunnel Obstacle Detection Based on Improved YOLOv5.

Considering the high incidence of accidents at tunnel construction sites, using robots to replace humans in hazardous tasks can effectively safeguard their lives. However, most robots currently used in this field require manual control and lack autonomous obstacle avoidance capability. To address these issues, we propose a lightweight model based on an improved version of YOLOv5 for obstacle detection. Firstly, to enhance detection speed and reduce computational load, we modify the backbone network to the lightweight Shufflenet v2. Secondly, we introduce a coordinate attention mechanism to enhance the network's ability to learn feature representations. Subsequently, we replace the neck convolution block with GSConv to improve the model's efficiency. Finally, we modify the model's upsampling method to further enhance detection accuracy. Through comparative experiments on the model, the results demonstrate that our approach achieves an approximately 37% increase in detection speed with a minimal accuracy reduction of 1.5%. The frame rate has improved by about 54%, the parameter count has decreased by approximately 74%, and the model size has decreased by 2.5 MB. The experimental results indicate that our method can reduce hardware requirements for the model, striking a balance between detection speed and accuracy.

Highly efficient and reusable Mg-Fe layered double hydroxides anchored in attapulgite for uranium uptake from wastewater.

Micro/nano interface adsorption is an effective strategy for separating uranium from aqueous solutions. However, their undesirable capture efficiency and poor cycling stability limit their practical application. In this study, we developed a clay-based micro-adsorbent constructed using attapulgite (ATP) and Mg-Fe layered double hydroxides (Mg-Fe LDHs) for uranium uptake from wastewater. The surface charge affinity between ATP and Mg-Fe LDHs contributed to the robust heterostructure of the ATP@Mg-Fe LDHs adsorbent, thereby enabling a uniform distribution of Mg-Fe LDHs on the ATP surface. Thus, the aggregation behavior of Mg-Fe LDHs was significantly reduced and stellated with an improved dispersion performance of this ATP@Mg-Fe LDHs micro-composite in an aqueous solution. The uranium adsorption capacity was 670.21 mg/g, which is the maximum among previously reported clay-based adsorbents. Notably, a satisfying performance was achieved for the adsorbent stability; the uranium adsorption efficiency remained as high as 97% after eight cycles of adsorption-desorption. The ATP@Mg-Fe LDHs adsorbent for separating UO22+ from water is a promising system that combines efficiency, capacity, selectivity, and reusability, and has potential for scaled-up applications.

Effect Analysis of Soil Type and Silt Content on Silt-Based Foamed Concrete with Different Density.

This paper investigates the influence of silt content and coarse particle content on the mechanical and physical properties of foamed concrete, including compressive and flexural strength, modulus of elasticity, water absorption, drying shrinkage, and air-void structure. Four types of silt with different coarse particle contents were obtained by soil mixing. The results showed that high density, low silt content, and high coarse particle content can provide better mechanical properties. High silt content and high coarse particle content would lead to lower drying shrinkage. Silt content was the main factor affecting the pore distribution of foamed concrete, and higher coarse particle content could optimize the air-void structure. Meanwhile, the change in air-void structure can accordingly affect the water absorption of foamed concrete. Results showed that, at the same density and silt content, higher coarse particle content can optimize the physical and mechanical properties of foamed concrete.