Abstract
The irrational mining of coal mines can cause damage to the geological environment, resulting in the frequent occurrence of geological disasters and high risk. In order to deeply explore the influence mechanism of coal mine geological disaster vulnerability, the three characteristic indicators of exposure, sensitivity, and adaptability proposed by the VSD vulnerability framework were taken as the starting point, and the indicator weights were determined by using the order graph method. The system dynamic model of coal mine geological disaster vulnerability was established and simulated. The results show that the exposure and sensitivity decrease gradually, and adaptability shows a gradual upward trend within one simulation period. When the parameter values of each subsystem were increased by 50%, the management subsystem was the key subsystem that affected the exposure and adaptability, and the exposure and adaptability variation decreased by 11.704% and 17.900%, respectively. The key subsystem affecting sensitivity was the equipment subsystem, and the sensitivity variation decreased by 18.958%.In order to reduce the vulnerability risk of geological disaster in coal mines and improve the safety management of the project.
1. Introduction
China is rich in coal resources. As the national economy continues to improve in form, some miners are pursuing short-term economic benefits and the exploitation of coal resources is growing at a high rate. In the mining process, the emergent behavior of the system causes accidents [1]. The occurrence of geological disaster in coal mines can be summarized as two reasons. On the one hand, unplanned and scientifically unguided blind mining has led to the loss of support for the roofs of hollow areas and shafts, causing more and more ground cracks and ground collapse disasters. On the other hand, mining causes large areas of mountain cracking, which will lead to landslide disasters in steep terrain and collapse disasters in steep cliff areas. At the same time, a large amount of waste slag produced by coal mining will accumulate along the hillside or valley, which is an important loose material leading to debris flow and landslide disasters. The most common forms of geological disasters in coal mines are land collapse, ground subsidence, landslide, gas explosion, and so on, which have a range of negative effects on coal production, miners’ life and property safety, resource, and geological environment. The research on geological disasters in coal mine is of great significance not only for coal mine safety but also for disaster management of other deep engineering [2–4].
Vulnerability is mostly applied to research on security management in various fields. In the field of natural disasters, Song et al. [5] studied the vulnerability of subway electrical fire system. Patricia et al. [6] evaluated the landslide risk by integrating vulnerability and vulnerability maps and analyzed the difference between socioeconomic vulnerability and ecological vulnerability of landslide events. In the field of petroleum, Wang and Guo [7] studied the security vulnerability of oil and gas stations. In the marine field, Jiang et al. [8] developed a system dynamic model of the safety vulnerability of marine platforms to address the extremes and complexity of the operating environment of marine platforms in order to provide an in-depth analysis of the safety vulnerability of marine platforms. In the field of urban security, Li et al. [9] integrate indicators related to vulnerability of land systems, assess the impact of urbanization on the urban environment, and analyze the temporal and spatial changes of exposure, sensitivity, adaptability, and vulnerability. Fan and Li [10] assessed the comprehensive vulnerability of urban earthquake disasters from seven aspects: natural, human, lifeline system, social conditions, economic conditions, engineering earthquake resistance, and resilience in the field of urban and natural disasters. In addition to the above dimension analysis, coal mine is also a hot spot in vulnerability research. Scholars, respectively, explored the vulnerability of underground coal mine safety system [11], ventilation system [12], underground tunnel construction personnel risk perception system [13], abandoned coal mine environment [14], groundwater [15], water inrush (assessment of water inrush and factor [16], overlying-aquifer water inrush [17]), industrial ecosystem [18], et al.
To sum up, at present, in the field of safety engineering, the research on vulnerability is mostly concentrated in emergency management and public safety. While in the field of coal mine safety, it is mostly concentrated on the vulnerability evaluation of a single system, such as ventilation, and there is a lack of dynamic research on the overall system. Therefore, under the perspective of system dynamics, the vulnerability of coal mine geological disaster is simulated and is based on the VSD model, which provides a reference for the management of coal mine geological disaster.
2. Analysis of Geological Hazards in Coal Mine
2.1. Analysis of Characteristics of Geological Hazards in Coal Mine
The cause of geological disasters in coal mines is that geological balance is destroyed due to excessive mining in coal mine production, which leads to changes in geological environment [19]. After summarizing, coal mine geological disasters have some common features, such as cluster occurrence, secondary, severity, and inevitability.
2.1.1. Cluster Occurrence
Cluster occurrence is a distinctive feature of geological disaster in coal mines. This is reflected in the fact that underground mining of coal mines will inevitably break down the original stable geological structure, destroy the surrounding rocks, and change the internal stress of the original stable rocks. With the development of underground mining, the destruction scope will continue to expand, causing widespread and continuous geological destruction.
2.1.2. Secondary
In the underground mining process of coal mines, secondary is another characteristic of geological disasters in coal mines, reflected in the recurrence of geological disasters in different places and at different times, with serious impact on the surrounding environment.
2.1.3. Severity
Once a geological hazard occurs in a coal mine, the intensity is generally high and the consequences are severe and difficult to control. In the majority of cases, when geological hazards such as gas explosions, water damage, roof collapses, and landslides occur, there is a threat to the lives of the personnel involved, resulting in casualties. At the same time, it will cause serious damage to coal mine’s facilities, which can be difficult to repair, due to the long and difficult maintenance cycle, and it makes maintenance of the facilities difficult and consequences of the disaster severe.
2.1.4. Inevitability
Although coal mining technology and safety measures have been improved, disaster resistance has been strengthened, but in general, it is impossible to eliminate the occurrence of geological disasters in coal mines. A large number of studies have shown that certain conditions are required for the occurrence of geological disasters in coal mines. Therefore, specific measures should be formulated according to the characteristics of geological disasters in coal mines, so as to prepare for various disasters in advance and reduce the impact of geological disasters in coal mines on life safety, production life, and environment.
2.2. Coal Mine Geological Disaster Vulnerability Framework
Vulnerability theory originates from the study of natural disasters and reflects the degree of change of the system under internal and external disturbances and the ability to recover normal operation from negative impacts [20]. At present, vulnerability theory has developed into an interdisciplinary and comprehensive research perspective and has been applied in many fields. Many scholars and institutions put forward vulnerability framework from different perspectives to analyze. Representative vulnerability frameworks are shown in Table 1. Representative vulnerability frameworks include Pressure and Release (PAR), Hazards of Place (HOP), Risk-Hazards (R-H), MOVE, Vulnerability Scoping Diagram (VSD), BBC, Airlie House Vulnerability (AHV), and Agent Differential Vulnerability (ADV) framework.
2.3. Vulnerability Analysis of Coal Mine Geological Disaster
The application of vulnerability theory to coal mine geological disaster can better reflect the change and recovery of the system under the disturbance of different factors. Therefore, this study adopts the widely recognized VSD vulnerability model to analyze coal mine geological disaster vulnerability, which divides vulnerability into three characteristic elements: exposure, sensitivity, and adaptability.
Exposure refers to the degree of exposure of a system to a disturbance situation, including exposure location, exposure time, and exposure frequency. In the field of safety engineering, it can be understood as the degree of potential accident, reflecting the probability of the system being affected by external disturbance. The higher the exposure, the greater the risk of harm, the higher the vulnerability of the system, and the greater the probability of the occurrence of accidents.
Sensitivity reflects the response degree of the system when it is disturbed, that is, the response time, amplitude, and limit. In the vulnerability analysis of coal mine geological disasters, it is reflected in the impact on accident casualties and accident economic losses. The higher the sensitivity, the higher the vulnerability of the system and the greater the impact of the accident.
Adaptability refers to the ability of the system to resist external disturbances, including recovery speed, recovery time, and recovery degree. In the analysis of coal mine geological disaster vulnerability, it is reflected in the influence of system completeness, emergency rescue effectiveness, and accident handling cost. The greater the adaptability, the smaller the vulnerability of the system, and the smaller the impact on the system.
In this paper, the interdisciplinary and interdisciplinary research advantages of vulnerability and coal mine safety are combined, and the application of vulnerability to geological disasters in coal mines in four subsystems, personnel, equipment, environment, and management, is analyzed.
The personnel subsystem includes factors, such as the individual’s own education level, psychology, physiology, and work experience accumulated over time span, in addition to the well-known coal mine underground ventilation, monitoring machinery. The equipment subsystem includes personal protective devices; the environmental subsystem includes both natural environmental factors, such as pollution density, and social environment such as population density; and the management subsystem is the management of the other three subsystems.
There may be cross-coupling between influencing factors within subsystems and between subsystems. Therefore, studying the causal relationship between multiple subsystems is of great practical significance for correctly understanding the development trend of vulnerability to geological disasters in coal mines. By analyzing the influencing factors within each subsystem, the theoretical model of coal mine geological disaster vulnerability is constructed, as shown in Figure 1.
3. Model Building
3.1. Boundary Determination and Basic Assumptions
System dynamics advocates that “the structure of the system determines the behavior of the system” [29], which is an important branch of system science and management science. It takes the analysis of the relationship between variables in the causal loop as the basic content, reveals the positive and negative feedback relationship and interaction between variables, and is suitable for solving periodic and long-term problems [30]. It is applied to a number of fields such as network public opinion communication and construction safety other fields. For the complex coal mine geological hazard system, it is reasonable to apply system dynamics to analyze its vulnerability.
Based on the above analysis of the coal mine geological hazard system, the following assumptions are proposed before the system dynamic simulation model is constructed: (1)The variables in the hypothesis model only take into account the values within the cycle range, not the increment of coal mine safety input, and ensure that the safety input at the present stage is sufficient to meet the task of safety production(2)It is assumed that when determining the boundary of the system, the major and key issues involved in the system are considered, while other factors with relatively minor effects are ignored [31]
3.2. Causal Analysis
Referring to the above analysis of influencing factors of coal mine geological disaster vulnerability, the system dynamic (SD) method was applied to construct the causal loop of coal mine geological disaster vulnerability model through Vensim software, as shown in Figure 2.
As can be seen from Figure 2, there are two positive feedback loops and two negative feedback loops. These are described as follows: (1)Disaster loss−→coal mine geological conditions+→psychological level+→violations−→coal mine geological disaster vulnerability−(2)Disaster loss−→safety regulations+→safety education training+→safety awareness level+→coal mine geological disaster vulnerability−(3)Safety awareness level+→safety production responsibility system+→safety supervision+(4)Safety supervision+→personal protective equipment+→personal equipment usage+→violations-
3.3. Simulation Model Construction
As can be seen from the above, the simulation model of vulnerability of coal mine geological disaster system is divided into 4 subsystems, including personnel, equipment, environment, and management, and 36 auxiliary variables, including the level of education and physiological quality, including 4 factors affecting disaster results, such as the frequency of accidents. There were three flow rate variables, including exposure variation, sensitivity variation, and adaptability variation and three state variables: exposure, sensitivity, and adaptability. According to the causal loop, the dynamic simulation model of coal mine geological disaster vulnerability system was established, as shown in Figure 3. The same color lines in Figure 3 form a subsystem, with the blue connecting lines showing the action of factors across the subsystem.
4. Simulation
4.1. Simulation Parameter Determination
According to the characteristics of long duration of coal mine project, the dynamic simulation model of coal mine geological disaster vulnerability system was constructed. In months, , , and .
Referring to relevant literature [32], the index relations of three state variables are obtained as shown in Table 2.
In 1955, Mutti, an American operation researcher, first proposed the method of order diagram in his book Decision Making. The core of the method is that pair-wise comparison is easy to operate, inspection methods and data processing are simple, and managers can easily master it. Therefore, this study uses the order graph method to determine the index weight.
Let be the number of comparison indexes, and the order graph is a table similar to checkerboard [33]. The respondents compare indexes in horizontal and vertical indexes one by one. If index is more important than index , gets 1 point. If both indicators are equally important, gets 0.5. If index is more important than index , then gets 0. Due to the limitation of the length of the article, the relationship is calculated only by taking the violations as an example, and the calculation process of other factors is similar and will not be repeated in the next time.
First, the results of the 10 experts’ scoring of the influencing factors are summarized, as shown in Table 3.
Secondly, the mean values of the scoring results for each influencing factor are calculated and compared between two using the mean size, as shown in Table 4.
Finally, according to Table 4, the scores of each influencing factor are calculated and synthesized, and the weight of the optimal sequence chart is obtained according to the proportion of results, as shown in Table 5.
As can be seen from Table 5, the relation of violations is
4.2. Simulation Output
The simulation was carried out by increasing 50% of the values of different parameters of the four subsystems of personnel, equipment, environment, and management in the dynamic simulation model of the coal mine geological disaster vulnerability system. The simulation results are obtained, as shown in Figure 4. Where the initial state is current, corresponding to the purple curve in the figure, and corresponding to the black, red, blue, and green curves in the figure of environment, equipment, personnel, and management subsystem, respectively.
(a) Exposure simulation of coal mine geological disaster vulnerability
(b) Sensitivity simulation of coal mine geological disaster vulnerability
(c) Adaptability simulation of coal mine geological disaster vulnerability
In order to further explore the effect of each subsystem on the vulnerability of coal mine geological disasters, the numerical simulation of the change in exposure, sensitivity, and adaptability variation during the simulation process is shown in Tables 6–8. According to Tables 6–8, the change rates of exposure, sensitivity, and adaptability of each subsystem are shown in Table 9.
5. Results Analysis
5.1. Exposure Analysis
It can be seen from Figure 4(a) that in a simulation period, the exposure of coal mine geological disaster vulnerability itself shows a declining trend. The influence of the four subsystems on exposure is different, the management subsystem has the most significant influence, followed by personnel subsystem and environment subsystem, and the equipment subsystem has little effect.
It can be seen from Table 9 that within 10 months of the simulation cycle, when the parameter values of personnel, equipment, environment, and management subsystem all increase by 50%, the exposure variation of coal mine geological disaster vulnerability shows a decreasing trend. Among them, the increase of the value of management subsystem and personnel subsystem resulted in a decrease of 11.704% and 10.316%, respectively, in ten months, which may be due to the fact that the management subsystem plays a greater role in the personnel subsystem, and the unsafe behavior of people is the main cause of accidents [34]. For example, the illegal operation of coal miners and the improper use of protective equipment will lead to an increase in the degree of accident hazards, the degree of accident exposure will increase, and the exposure of the whole system will increase. The increase of the value of the environment subsystem and the equipment subsystem led to the overall decrease effect of exposure variation less than that of the management subsystem and the personnel subsystem, and the decrease rate was 8.928% and 3.423%, respectively.
5.2. Sensitivity Analysis
It can be seen from Figure 4(b) that in a simulation period, the sensitivity of coal mine geological disaster vulnerability itself shows a declining trend. The four subsystems have different effects on sensitivity. The equipment subsystem has the most significant effect, followed by the environment subsystem and management subsystem, and the personnel subsystem has no significant effect.
It can be seen from Table 9 that within 10 months of the simulation cycle, when the parameter values of personnel, equipment, environment, and management subsystem increase by 50%, the sensitivity changes of coal mine geological disaster vulnerability all show a decreasing trend. Numerical equipment subsystem of increased exposure to the degree of variation in the first 10 months fell 18.958%, which had the most significant effect on sensitivity; the reason for this could be some of the equipment at the operation site increase the resistance of the whole system response capacity, and the facility system can be more perfect. The better the performance of security system, the lower the sensitivity of geological disaster vulnerability. For example, in the process of underground mining, the use of monitoring and monitoring equipment can quickly find hidden dangers before the accident, so as to “move the pass forward,” effectively avoid the occurrence of accidents, help to do a good job of emergency treatment after the accident, and reduce economic losses. The overall decrease in the amount of sensitivity variation due to the increase in the values of the environment, personnel, and management subsystems is less than that of the equipment subsystem. The reduction rate of the sensitivity variation under the effect of the environment subsystem and the personnel subsystem was 11.750% and 8.594%, respectively, and the personnel subsystem was only 2.617%.
5.3. Adaptability Analysis
It can be seen from Figure 4(c) that in a simulation period, the adaptability of geological disaster vulnerability of a coal mine presents an upward trend. The four subsystems have different effects on adaptability. The management subsystem has the most significant effect, followed by the equipment subsystem and personnel subsystem, and the environment subsystem has little effect.
It can be seen from Table 9 that, within 10 months of the simulation cycle, when the parameter values of personnel, equipment, environment, and management subsystem all increase by 50%, the change in adaptability of coal mine geological disaster vulnerability shows a decreasing trend. Among them, the increase in the value of management subsystem resulted in a 17.900% decrease in the adaptability variation in October, which may be due to the positive promotion effect of management. When an accident occurs, managers should investigate the emergency rescue process and the cause of the accident, carry out safety education and training in response to the accident investigation report, improving the adaptability of the whole system in the process of continuous accumulation. The increase of environment subsystem, equipment subsystem, and personnel subsystem resulted in the overall decrease effect of adaptability change, which was less than that of management subsystem, and the decrease rates were 1.911%, 11.311%, and 3.351%, respectively.
6. Conclusion
Using the three indicators of exposure, sensitivity, and adaptability in the VSD vulnerability framework as entry points, the theoretical model of coal mine geological disaster vulnerability was constructed by analyzing the interactions with the four internal influencing factors of personnel, equipment, environment and management subsystems.
The results of the simulation show that exposure and sensitivity of the vulnerability of coal mine geological disaster gradually decrease, in one simulation period, while the degree of adaptability, on the contrary, gradually increases.
With a 50% increase in the value of each subsystem parameter, the key subsystem affecting the exposure and adaptability of coal mine geological disaster vulnerability is the management subsystem, respectively, with 11.704% and 17.900% reductions in the amount of change in exposure and adaptability variation, compared to the initial state. The key subsystem affecting sensitivity is the equipment subsystem, and sensitivity variation is reduced by 18.958% compared with the initial state. The results provide a scientific reference for the management of geological disaster and contribute to the sustainable development of coal mining enterprises.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The authors declare no conflicts of interest.
Authors’ Contributions
Conceptualization was handled by Lei Li and Mei Zhi; investigation, methodology, and project administration were worked on by Mei Zhi; supervision was taken care of by Lei Li and Ruihan Li; and writing the original draft and reviewing and editing the study were managed by Mei Zhi, Siwei Wang, and Lirong Cao.
Acknowledgments
This work was supported by grants from the National Natural Science Foundation of China (no. 52074214) and the Xi’an Science and Technology Plan Projects (no. 21SFSF0010) for financial support. Also, the authors are grateful for the participation of the academic and industrial experts who provided responses for the index weight survey.