Leping He

The WMI (weak muddy intercalation) is a typical weak structural surface in the red-bedded rock mass; ensuring slope stability by increasing the strength of the WMIs helps reduce project costs and carbon emissions. With the advantages of energy saving, high efficiency, and green, microwave technology has attracted scholars’ attention to geotechnical material property improvement. However, the mineral composition of the WMIs is complex and variable, and the applicability of microwave technology needs further evaluation. In this paper, the effects of microwave temperature and clay mineral types and content on the physical and mechanical properties of the WMIs were evaluated. The results show that microwave heating can substantially improve the uniaxial compressive strength of the WMIs, regardless of the types and content of clay minerals. Dehydration, dehydroxylation of clay minerals, and local melting of albite occurring in the specimens under microwave heating enhanced the strength of the soil particles and the interparticle joints. The strength increase ratios of the WMI specimens increased with the temperature increase. With the increase in clay mineral content, the strength increase ratio of kaolinite WMIs and illite WMIs decreased, while the strength increase ratios of montmorillonite WMIs increased. The present multiple regression analysis methods are used to establish the strength prediction models of the WMI microwave-reinforced specimens, which can guide the engineering application.

The bearing stratum of high-rise and ultra-high-rise buildings in southwest China has inevitably faced moderately weathered red mudstone. It was a waste of the potential bearing stratum calculated according to the specification, as the bearing stratum obtained from laboratory and in situ tests was much higher than the values suggested by the specification. Rock mass surface deformation detection is of great significance in the safety management of a foundation project. Some correlation between surface deformation and failure characteristics may exist that could help to understand the bearing stratum of the moderately weathered red mudstone. This research was conducted to study the progressive failure characteristics of the moderately weathered red mudstone through surface deformation. In situ load, triaxial, and binocular visual technology were employed for data acquisition. The proposed conjecture was illustrated and verified by a group of experiments from three construction sites. Five stages could be described as the progressive failure of the moderately weathered red mudstone: compaction, elasticity, elastoplasticity, plasticity, and failure. Furthermore, the surface displacement increment fluctuates with the loading time and fades into the distance. Therefore, this research could provide a robust, practical application for analyzing the progressive failure of moderately weathered red mudstone.

The mechanical behavior of mudstones is significantly affected by their mesostructure. This study investigates the damage evolution of red mudstone mesostructures under uniaxial compression through U-Net image segmentation, mesoscopic representative elementary area (mREA), meso-element equivalent method, and linearly superimposed model. Results show that the mREAs can be simplified as a binary structure comprising nonclayey minerals and a porous matrix. The inclusion-matrix interfaces constituted by the dominant inclusions, such as large inclusions and a series of inclusions with specific arrangements, are the weakest regions at the postpeak stage. The shear failure of these interfaces leads to general shear failure with a penetrating principal fracture or local shear with several nonpenetrating local fractures in the mREAs. The damage evolution and failure mode are sensitive to the inclusion geometric features, e.g., inclination, grain size, and spacing. However, the uniaxial compressive strength (UCS) is mainly determined by the included angle between the dominant inclusion inclination and the loading direction. With consistent composition, an increase in the included angle from 0 to 90° results in an increase in the UCS of the muddy facies and a decrease in the sandy facies, with the UCS of the sandy facies being more sensitive to changes in the included angle. Our findings indicate that the structural failure of red mudstones from mesoscopic to macroscopic is driven by the accumulation and expansion of shear failure at multiple scales due to the presence of hard–soft interfaces. This study enhances our understanding of the structural failure mechanism of mudstones and serves as a practical reference for the mesomechanical testing of clay rocks.

Calculating deformation values and determining deformation areas are essential for slope monitoring and safety management. Recently, terrestrial laser scanning has been widely used for deformation monitoring due to to its speed and efficiency. However, handling a large amount of point cloud data to obtain the deformed area is still challenging. To rapidly evaluate slope deformation information, this study proposes a simplification algorithm for point cloud data based on multi-parameter feature preservation. The proposed method retains feature points (i.e. inflection points and edge points) and simplifies data with the octree structure. In addition, a method based on cloud-to-mesh for displacement is used where the winding number is introduced for the signed function. Next, the deformed area over the level of detection is extracted using density-based spatial clustering for applications with a noise clustering algorithm. To verify the reduction method, two types of slope field data are used for experiments. The results reveal that the proposed point cloud approach is superior to the conventional algorithms. Furthermore, the highway slope in Mianyang is selected as a case study to validate the performance of the proposed method. The entire monitoring area is stable with a deformation of approximately 0.43 mm, and only four regions are deformed over the study period. When the mean displacement value is considered in different deformation regions, the minimum deformation is −82.02 mm and the maximum deformation is 85.31 mm. Moreover, comparative experiments on deformation calculation are conducted and reveal the superior performance of the proposed method.

Working at heights causes heavy casualties among workers during construction activities. Workers’ unsafe action detection could play a vital role in strengthening the supervision of workers to avoid them falling from heights. Existing methods for managing workers’ unsafe actions commonly rely on managers’ observation, which consumes a lot of human resources and impossibly covers a whole construction site. In this research, we propose an automatic identification method for detecting workers’ unsafe actions, considering a heights working environment, based on an improved Faster Regions with CNN features (Faster R-CNN) algorithm. We designed and carried out a series of experiments involving five types of unsafe actions to examine their efficiency and accuracy. The results illustrate and verify the method’s feasibility for improving safety inspection and supervision, as well as its limitations.

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

The failure of muddy intercalation in the slope is mainly due to the clay minerals which mainly contains the kaolinite. This study investigates the structural evolution of kaolinite in muddy intercalation exposed to the microwave heating of 300-800°C by evaluating the uniaxial compressive strength, morphology, mineralogical composition, and water stability. Results show that the crystal structural evolution of kaolinite can be divided into four stages, which are 300-400 °C, 400-500°C, 500-700°C, and 700-800 °C. The kaolinite undertakes the thermal expansion, dehydroxylation-induced crack, kaolinite-metakaolinite transition, and two-step transition of metakaolinite - silica spinel (γ-alumina) - mullite. The mechanical performance increasing consists of three stages. At 300-400 °C, the uniaxial compressive strength increases about 38.7 % due to thermal expansion. At 400-700 °C, the uniaxial compressive strength is unchanged due to the balance between the positive side due to thermal expansion and semi-liquid metakaolinite and the negative side due to the dehydroxylation-induced crack propagation. At 700-800 °C, the re-increase of 35.8 % is mainly due to the two-step transition of metakaolinite - silica spinel (γ-alumina) - mullite. Water leaching test shows that the kaolinite over 500 °C present well integrity.