Due to the lack of historical subsidence data on goaf sites alongside expressways, it is difficult to comprehensively evaluate the stability of goaf sites and accurately identify potential risk points. An investigation to study the stability of goaf sites in the Huaibei section of the Xu Huaifu Expressway is conducted through SBAS-InSAR technology and field investigation. Initially, the stability of the goaf site around the route is anticipated through field investigation. Afterwards, based on the extraction of Sentinel-1 satellite images, subsidence data of the goaf sites from 2017 to 2021 were extracted. Finally, the stability of risk points is analysed. Results demonstrate that although mining in the area stopped more than five years ago, the goaf site has continued to slowly sink. According to four years of goaf site subsidence data extracted by SBAS-InSAR technology, two subsidence risk areas, namely, Y1-05 and Y1-09, were discovered, and the subsidence areas displayed an obvious inverted “convex” shape. Of these two areas, Y1-05 is a potential risk point that was not found during the field investigation. The subsidence basin in the Y1-05 area has developed gradually, and the residual subsidence is expected to be close to 475 millimetres within the next 15 years. Although it can be considered a stable area, the subsidence value is quite large and may pose risks to route safety. Therefore, a flexible reinforced mesh can be adopted for the route. The subsidence basin of Y1-09 is the largest, but the expected residual subsidence is only 50 millimetres and will have insignificant influence on the route. Engineering practice shows that SBAS-InSAR technology can effectively analyse the surface deformation of goaf sites and has important practical significance in optimising the selection of special geological routes in expressways.

In deep coal mine strata, characterized by high ground stress and extensive fracturing, predicting the strength of fractured rock masses is crucial for stability analysis of the surrounding rock in coal mine strata. In this study, rock samples were obtained from construction sites in deep coal mine strata and intact, as well as fissured, rock specimens were prepared and subjected to triaxial compression tests. A numerical model based on the discrete element method was then established and the micro-parameters were calibrated. A total of 288 triaxial compression tests on the rock specimens under different conditions of confining pressure, loading rate, fissure dip angle, and fissure length, were conducted to obtain the triaxial compressive strength of the fractured rock specimens under different conditions. To address the limitations of traditional back propagation (BP) neural networks in solving stochastic problems, a modified BP neural network model was developed using a random factor and an interlayer mean square error corrected network model evaluation function. The traditional and modified BP neural network models were then employed to predict the triaxial compressive strength of the fractured rock specimens. Through comparative analysis, it was found that the modified BP neural network prediction model exhibited smaller errors and significantly reduced overfitting, making it an effective tool for predicting the strength of fractured rocks in deep coal mine strata.

Huanghuai area is rich in coal resources, but due to the increasingly complex geological environment faced by coal mining, the complexity of structural stress is one of the main problems. In order to find out the distribution law of deep in situ stress in the Huanghuai area, the in situ stress measurement data of 81 effective measuring points in 24 mines with depths ranging from −100 m to −1200 m are analyzed in the present study base on the in situ stress measurement data. Furthermore, numerical simulation and field observation are used to analyze the deformation and failure characteristics of the surrounding rock. The research results show that the deep mining area of Huanghuai exhibited a high stress level, and the vertical and horizontal principal stress increases with increasing depth. The ratio of the lateral pressure coefficient ranges from 0.90 to 2.70, and the in situ stress field presented a trend of transition to the quasihydrostatic pressure field type as the depth extended, in which 80.23% of the measuring points are distributed between 1.20 and 2.10, belonging to the typical tectonic stress field type in which tectonic stress is absolutely dominant. The observation results of the surrounding rock and numerical simulation reveal that when the layout axis of the roadway is approximately perpendicular to the direction of the maximum horizontal principal stress, a high stress concentration area is present on the roof and floor of the roadway, the deformation increases sharply, and the support pressure of the roof and floor increases.

As one of the extensively used gasoline additives, MTBE can leak into the subsurface, which will not only deteriorate the ecological environment, but also affect the geotechnical characteristics of the soil. In this study, the geotechnical properties of MTBE-contaminated soil consisting of the basic physical properties, strength, compressibility, hydraulic conductivity, leachability, electrical resistivity and microstructural characteristics are comprehensively investigated. The results show that the Atterberg limits consistently decrease with increasing MTBE content in the soil. As the MTBE content increases from 0% to 10%, the specific surface area of the soil decreases by 28%, the sand content increases by 22%, the clay and silt contents decreases by 3% and 18%, respectively. The soil compression index, hydraulic conductivity, leached MTBE concentration and electrical resistivity increase, while the UCS decreases with increasing the MTBE content. Microstructural analysis shows that increasing MTBE content would result in mineralogical alterations that decrease the illite and kaolinite content in the soil. The aggregation and flocculated structures could be detected with an increase in the number and size of the inter-aggregate pores. Additionally, electrical resistivity of the contaminated soil is adopted to assess the geotechnical properties of MTBE-contaminated soil based on the well-established empirical relations.