To analyze the excavation stability and reasonable reinforcement measures of cutting slope with a goaf collapsed roadway and collapsed mining face, the finite element software Midas GTS NX was used to model and analyze the change in the slope stability coefficient under different excavation slope ratios. Combined with the scope of the project land, it is proposed that the slope ratio of grades 1–3 (close to the top of the cut) is 1:1.5, while the slope ratio of grades 4–6 (close to the bottom of the cut) is 1:1, to excavate the slope. During the excavation process, the change in the plastic zone after each level of slope excavation was further analyzed, and the control variable method was used to analyze the influence of the collapsed roadway and the collapsed mining face on the slope stability. We found that the collapsed mining face was one of the main factors affecting the stability of the slope. During the reinforcement of the slope, the reinforcement effects of different schemes were analyzed, and we found that the slope can be stabilized by reinforcement of the third- and fourth-level slopes adjacent to the collapsed mining face. In this study, the old goaf and cutting slope excavation are combined, and the stability of slope excavation with a goaf collapsed roadway and collapsed mining face is analyzed by coupling. This research provides a scientific basis for the stability analysis of cutting slope excavation in old goafs in the future and has great practical engineering significance.

Our aim in this study was to analyze the major and minor factors affecting the stability of a slope containing a coal seam in a goaf. Based on engineering experience, we first identified nine factors that may affect slope stability, of which we determined eight that may substantially affect slope stability through a single-factor numerical simulation analysis. Then, we arranged 27 groups of numerical simulation tests with eight factors and three levels with the orthogonal test method, and we determined the ranking of the major and minor influencing factors through a range of variance analyses. The results showed that the influence of each factor was ranked as the roadway width > coal seam position > slope gradient > coal seam thickness > coal seam internal friction angle > coal seam cohesion > coal seam dip angle. Among these, the roadway width, coal seam position, and slope gradient were the major factors affecting slope stability; coal seam thickness, coal seam internal friction angle, coal seam cohesion, and coal seam dip angle were the minor factors. In this study, we combined the goaf and slope containing the coal seam, and we couple analyzed the factors influencing the stability of the slope containing the coal seam in the goaf. Our findings provide a scientific basis for the treatment and protection of slopes containing coal seams in goafs in the future and have a practical engineering importance for the analysis of the excavation stability of road-cutting slopes in goafs.

The disturbance depth of traffic load has a direct impact on the stability of a room-and-pillar mining goaf. To quantitatively calculate the relationship between the traffic load disturbance depth and influencing factors, 49 groups of horizontal combinations of different influencing parameters are designed in this study, based on the orthogonal experimental design method. Midas GTS is used to simulate and obtain the corresponding traffic load disturbance depth data. A multivariate linear regression analysis of the traffic load disturbance depth is conducted, and a regression formula for calculating the traffic load disturbance depth is established. According to the traffic load disturbance depth, goaf depth, and the stability of the roof, coal pillar, and base plate under traffic load conditions, a judgment flow of the room-and-pillar mining goaf treatment method under traffic load conditions is established, and it is applied to the reconstruction and expansion project of the Jixi section of the Dan-A national highway. The results show that a geogrid can be used for treatment purposes when the traffic load disturbance depth is 1.5 times lower than the depth of the room-and-pillar mining goaf, or when the traffic load disturbance depth is 1.5 times greater than the depth of the room-and-pillar mining goaf but the roof, coal pillar, and base plate are stable. Additionally, grouting is needed for treatment in other cases. The results of this study can provide a scientific basis for the selection of treatment methods for room-and-pillar mining goafs underlying highways in the future. The results are of great significance in the field of engineering for the safety measures concerning highway room-and-pillar mining goafs.

Considering that it is easily disturbed by various engineering factors such as weather, hydrology, and construction during engineering monitoring, the collected subsidence data contain various noises. In order to reduce the influence of engineering noise on the accuracy of subsidence prediction, it is proposed to use the Daubechies (DB) wavelet to decompose the original subsidence time series; the items with the low-frequency trend, after decomposition, are predicted using long short-term memory (LSTM) model, items with high-frequency noise used the autoregressive (AR) time series model to make predictions, and the prediction results of the low-frequency trend term and the high-frequency noise term are summed to obtain the total time series predicted value. Combining the actual engineering subsidence monitoring data of the old goaf, compared with the prediction results of the LSTM and RNN models without DB wavelet decomposition and the gray model GM (1,1), the results show that the DB wavelet has an obvious improvement effect in reducing the influence of measurement data noise on prediction error. Compared with the single prediction model LSTM, RNN, and GM (1,1), the proposed prediction model has higher prediction accuracy, smaller error, and better trend. It can be used as a calculation method to improve the prediction accuracy of surface subsidence in old goaf.