Qingjie Qi

With the deepening development and utilization of urban underground space, the risk of urban road collapse is becoming increasingly prominent, which is a serious threat to the safety of life and property. Therefore, the risk assessment of urban road collapse has vital significance for the safety management of cities. The main idea is to predict ongoing accidents by analyzing historical accident cases in depth. This paper explores the combination of Interpretative Structural Modeling (ISM) and Bayesian Networks (BNs) to construct a risk assessment model of road collapse. First, the main risk factors of road collapse and their coupling relationships are identified, which is used to increase the low reliability of complex systems. Then, the risk factors of road collapse are logically divided by ISM to obtain the BN hierarchy. Finally, the BN node probabilities are evaluated by the Expectation–Maximization (EM) algorithm using the collected 92 real road collapse accident cases. The model can be used to quantify the coupling strength and influence degree of each risk factor on the occurrence of road collapse accidents, which in turn can predict the probability of road collapse accidents in a given scenario. This study can provide a theoretical basis for urban safety management and reduce the risk of road collapse and potential loss of life and property, which is important for the sustainable development of societies.

This research aims to investigate the impact of high-pressure water jet cutting parameters on pressure alleviation around the coal slot. A numerical model of high-pressure water jet cutting coal was developed using FLAC^3D software, allowing for a detailed study of how each cutting parameter affects the pressure relief effect of the slot. The key findings are as follows: as the water jet pressure increases, the plastic area of the coal body around the kerf expands, although the rate of increase diminishes, with the optimal water jet pressure being 30 Mpa. The results suggest that hydraulic slotting measures are particularly beneficial for outburst prevention in high in situ stress coal seams. The pressure relief range exponentially grows with an increase in the kerf depth, signifying that enhancing the kerf depth has a notable effect on improving the hydraulic kerf pressure relief. As the slit width increases, the volume of the slit enlarges, leading to a significant rise in the pressure relief range of the surrounding coal body. Given that an increase in the slit width necessitates an increase in the nozzle outlet diameter and slotting time, the optimal slit width is determined to be 0.2 m. The research concludes that the optimal hydraulic slit spacing is 3 m. This study offers valuable theoretical guidance for high-pressure water jet slotting.

To investigate the influence of moisture content, density, and loading frequency on the dynamic strength and liquefaction characteristics of sandy soil, a series of vibration triaxial tests were designed and conducted. The tests were divided into incremental loading tests and cyclic loading failure tests. The results of the incremental loading tests indicated that the shear modulus decreases with increasing moisture content and density, while it increases with increasing loading frequency. The damping ratio of unsaturated samples showed no significant correlation with moisture content, whereas samples with a density above 50% exhibited an increasing trend in damping ratio with increasing density. The damping characteristics of the sandy soil were found to be related to the loading frequency, exhibiting the characteristics of viscous damping. The results of the cyclic loading tests revealed that the dynamic failure mode of the sand soil is the ultimate equilibrium failure mode. Increasing moisture content and decreasing density make the samples more susceptible to failure. During the process of cyclic loading leading to dynamic failure, the shear modulus of unsaturated samples remains constant, while the shear modulus of saturated samples gradually decreases. The damping ratio of saturated soil is significantly higher than that of unsaturated soil. During the process of cyclic loading leading to dynamic failure, the damping ratio of saturated soil shows no apparent correlation with loading frequency, but it decreases with increasing density.

Life detection technology using ultra-wideband (UWB) radar is a non-contact, active detection technology, which can be used to search for survivors in disaster rescues. The existing multi-target detection method based on UWB radar echo signals has low accuracy and has difficulty extracting breathing and heartbeat information at the same time. Therefore, this paper proposes a new multi-target localization and vital sign detection method using ultra-wide band radar. A target recognition and localization method based on permutation entropy (PE) and K means++ clustering is proposed to determine the number and position of targets in the environment. An adaptive denoising method for vital sign extraction based on ensemble empirical mode decomposition (EEMD) and wavelet analysis (WA) is proposed to reconstruct the breathing and heartbeat signals of human targets. A heartbeat frequency extraction method based on particle swarm optimization (PSO) and stochastic resonance (SR) is proposed to detect the heartbeat frequency of human targets. Experimental results show that the PE—K means++ method can successfully recognize and locate multiple human targets in the environment, and its average relative error is 1.83%. Using the EEMD–WA method can effectively filter the clutter signal, and the average relative error of the reconstructed respiratory signal frequency is 4.27%. The average relative error of heartbeat frequency detected by the PSO–SR method was 6.23%. The multi-target localization and vital sign detection method proposed in this paper can effectively recognize all human targets in the multi-target scene and provide their accurate location and vital signs information. This provides a theoretical basis for the technical system of emergency rescue and technical support for post-disaster rescue.

As a disaster-bearing body, the coal mine is vulnerable to the impact threat of rainstorm disasters, which easily induce flooding accidents. In view of this, this study is designed to propose the vulnerability assessment method of rainstorm-induced coal mine flooding disasters. On account of the scientific theory of disaster risk, the evaluation model and index system of coal mine flooding disaster induced by rainstorm covering exposure, fortification level, and resilience are constructed, while the vulnerability assessment method based on Tri-AHP method is proposed. Study results demonstrate that population exerts the greatest impact on exposure, wellhead elevation matters the most for fortification level, and the emergency plan has a dominant influence on resilience. Therefore, for coal mines, it is suggested to strengthen the special rainstorm emergency plan drill, improve the fortification level, and solidify the emergency duty during the rainy season. In this study, the rainstorm disaster vulnerability assessment method of coal mine is innovatively put forward, which is conducive to sustainable energy and environmental development.

Previously conducted studies have established that as a disaster-bearing body, a coal mine is vulnerable to flood disasters and their consequent impacts. The purpose of this study is to put forward a quantitative evaluation method of the risk of coal mine flood disaster. Based on the scientific theory of disaster risk, a risk assessment model and index system for coal mine flood disaster was constructed, and a risk assessment method was proposed based on the projection pursuit and fuzzy cluster analysis. The results show that the risk of coal mine flood disaster was mainly determined by the hazard of disaster-causing factors, the stability of the disaster-prone environment, and the vulnerability of disaster-bearing bodies. Further research shows that the maximum daily rainfall had the greatest impact the risk of coal mine flood disaster. Therefore, the early warning mechanism should be established between the coal mine and the meteorological department to improve the fortification level. A risk assessment method of coal mine flood disaster was proposed in this study, which is of great significance for energy sustainability.

In coal mine engineering, numerical software is used to analyze the behavior of coal rock damage and fluid migration. The order of the coefficient matrix used in numerical calculations is increasing, and this increases the computation steps in obtaining the coefficient matrix solution. The storage and solution of the coefficient matrix are key factors influencing the efficiency of the numerical software. Therefore, to save storage space and reduce the computation steps, the coefficient matrix must be effectively compressed and stored. In this work, the structural characteristics of different coefficient matrices are analyzed in detail, and we find that for different computational regions, as long as the nodes are numbered according to certain rules, the corresponding coefficient matrices will have similar structural characteristics. The nonzero elements are symmetrically distributed in the diagonal band, and all the elements on both sides outside the band are zero. Based on this, the coefficient matrix is compressed by a pivoting scheme, and the compressed matrix is directly eliminated by dislocation Gaussian elimination. Thus, a compressed storage method that integrates the compression and solution of the coefficient matrix is established. The compressed storage and calculation module is incorporated into our self-developed simulation software COMBUSS-3D to simulate the evolution of the temperature field in the goaf of Luling Coal Mine. Compared with the conventional method, the compressed storage module can significantly improve the computing rate of the simulation, by approximately 80%.