Coal and gas outbursts are severe accidents that can occur in coal mines. Half of coal and gas outburst accidents have occurred in China. Previous studies on coal and gas outburst accidents have ...focused on the mechanisms that result in accidents, gas extraction, accident prediction, and early warning. However, accidents involving coal and gas outbursts result from the combined effects of multiple factors. However, a systematic analysis of coal and gas outburst accidents is still lacking. In this study, 84 coal and gas outburst accidents occurred in China from 2008 to 2018 were used as a sample. The 24Model was used as the accident analysis theory, and the accident case data-driven method was used to analyse the causes of coal and gas outburst accidents. In particular, the reasons for behaviour were systematically studied. The following can be inferred from analysis: (1) The causes of unsafe conditions are primarily reflected in three aspects. (i) Gas factor. Coal mines with high gas content and pressure remain the focus of outburst prevention. (ii) Coal factors. The occurrence of coal and gas outburst accidents has no strictly positive correlation with the depth of a coal seam. 50% of coal and gas outburst accidents occur in medium-thick coal seams. (iii) Geological structural factors. Ground stress (30.95%), coal thickness change (22.62%), and faults (22.62%) are the most frequently occurring geological structural factors in outburst accidents. (2) The reasons for unsafe acts are primarily reflected in 151 unsafe acts, 17 key basic unsafe acts, nine key categories unsafe acts, and four key stages. The personnel and proportion of these unsafe acts are senior leaders (53.55%), middle managers (31.56%), and front-line miners (14.89%). (3) Reasons for individual safety capabilities. Insufficient safety knowledge is manifested in seven aspects, including insufficient anti-outburst knowledge. The performance and proportion of poor safety awareness are safety system awareness (60.66%), safety risk awareness (20.49%), and safety responsibility awareness (18.85%). From 151 unsafe acts, 90 habitual violations acts that caused coal and gas outburst accidents were categorised. The performance and proportion of poor safety psychology were fluke psychology (40.85%), adventure psychology (23.36%), convenient psychology (20.22%), and paralysis psychology (15.57%). (4) The deficiencies of the safety management system are reflected in the failure to comply with the safety policy, imperfect safety management organization structure, lack of professional and technical personnel, and lack of 29 safety procedures in seven systems. (5) The lack of safety culture is primarily reflected in 22 safety culture elements. Among these, there are 19 elements had a frequency of ≥ 50%. The systematic analysis of coal and gas outburst accidents conducted in this study can reveal the causes of such accidents more comprehensively and provide a reference and basis for both safety training and management.
Though the relationships between environment and crime have been studied a lot in many countries, this work is still a void in China. This work presents the study about how property crimes are ...influenced by the temporal and weather factors in China. With the crime data collected from police, the property crimes pattern by season of year, day of week and time of day are investigated firstly. Then the influence of the temporal variables—major holidays, school close days and weekends—and weather on the crimes are tested. The findings show that the robbery is significantly influenced by the temporal variables but has no correlations with weather, while burglary is not only affected by the temporal variables but also correlated with sun light hours.
Analyzing the causes of accidents, excavating accident paths, and applying accident prevention are important tasks in safety management. Focusing on coal and gas outburst accidents, this study ...examined the primary accident path and conducted applied research on the reasoning of the accident case. First, combined with the obtained accident causes, a coupling analysis of the causes of coal and gas outburst accidents was conducted. Second, using the method of data mining coupled with Apriori algorithm, the coupling relationship between each cause module of the coal and gas outburst accident was obtained, and consequently, a path map of the coal and gas outburst accident was drawn. Third, a Bayesian network model for the causes of coal and gas outburst accidents was established based on the accident path map and the probability of occurrence of each cause. Finally, considering the safety concept element (SC1) as an example, the Bayesian network model was used to conduct a sensitivity analysis of accident causes. Thereafter, considering the coal and gas outburst accident of the Sanjia Coal Mine in Guizhou Province as an example, probabilistic reasoning research on the cause of the accident was conducted. The application results showed that (1) under normal conditions, there are approximately 797,280 accident paths for coal and gas outbursts. Following data mining, 188 main accident paths were found. (2) Sensitivity analysis determined 19 factors that were sensitive to safety concept elements (SC1), of which the three most sensitive factors were (i) resource management system procedures (SM7), (ii) safety policy (SM1), and (iii) safety training system procedure (SM8). 13 paths exhibited a sensitivity ≥0.5%, of which 7 exhibited strong sensitivity. (3) The absolute accuracy rate of accident cause reasoning in the Sanjia Coal Mine in Guizhou Province was 71.43%, while the relative accuracy rate was close to 100%. Thus, it was concluded that: (1) the accident path mining method proposed in this paper is feasible for main accident path mining. (2) The Bayesian network model for the causes of coal and gas outburst accidents established in this study can be practically applied for the sensitivity analysis of accident causes and exhibits high reliability in the probabilistic reasoning of accident causes. The results of this study is expected to aid in the prevention of coal and gas outburst accidents, and provide reference and help for the path mining of other accident causes and the probabilistic reasoning of accident causes.
The content and methods of traditional safety training can no longer meet the needs of the industry or accident-targeted safety training. To solve this problem, this study proposes an accidental case ...data accident causing model-driven safety training method (ACDACM method) based on an analysis of the content and methods of China's safety training. This method is theoretically driven by the accident causation model and data-driven by the accident case information. Through data analysis of historical accident cases, basic information and comprehensive reasons for accidents can be obtained. Using data mining algorithms, the causes and combinations of high-frequency and high-risk accidents can be mined, supported by accident data, and a path map of the accident causes can then be obtained. The developed safety training project is more targeted by comparing accident causes with industry standards and regulations. This study considers coal and gas outburst accidents as an example and uses 24Model to analyze 84 coal and gas outburst accidents in China. The targeted safety training plan had eight parts of training content, and supporting PPTs, handbooks, and videos were produced. The application shows that this method can provide targeted safety training designs for industries or accidents and has industry universality. Finally, the advantages and development of the ACDACM method are elaborated and the future of safety training is discussed. This study provides theoretical and methodological support for targeted safety-training programs.
The specific risk assessment of informal settlements (IS) is important for the management of IS and protection of environmental safety and public health. In this paper, we introduced the different ...types of IS in China, and conducted the fire risk assessment on 26 burning buildings in these IS, providing a semi-quantitative and scenario fire risk perception of IS in China for the readers. Two methods, the risk index and the Bayesian network, are proposed and adopted for the fire risk assessment in IS. First, a risk index system with a total of 69 factors is used to assess the degree of fire risk of buildings in IS semi-quantitatively, and the result shows that fire equipment and fire safety management on IS are seriously lacking. Then, a Bayesian network of building fire risk with a total of 66 nodes was established to assess the fire risk from ignition to spread as well as the safety evacuation. Overall, the possibility of ignition is high, but due to the role of fire equipment and fire protection design, the possibilities of fire from ignition to spread is gradually reduced. Finally, we also put forward some feasible suggestions for occupants in IS, community organizations and emergency managers to reduce the fire risk from the aspects of fire equipment and fire safety management.
In modern safety management, it is very important to study the influence of the whole safety system on unsafe acts in order to prevent accidents. However, theoretical research in this area is sparse. ...In order to obtain the influence law of various factors in the safety system on unsafe acts, this paper used system dynamics simulation to carry out theoretical research. First, based on a summary of the causes of the coal and gas outburst accidents, a dynamic simulation model for unsafe acts was established. Second, the system dynamics model is applied to investigate the influence of various safety system factors on unsafe acts. Third, the mechanism and the control measures of unsafe acts in the enterprise safety system are studied. This study's main result and conclusions are as follows: (1) In the new coalmines, the influence of the safety culture, safety management system, and safety ability on the safety acts were similar. The order of influence on the safety acts in production coalmines is as follows: safety management system > safety ability > safety culture. The difference is most evident in months ten to eighteen. The higher the safety level and safety construction standard of the company, the greater the difference. (2) In the construction of the safety culture, the order of influence was as follows: safety measure elements > safety responsibility elements = safety discipline elements > safety concept elements. It shows the difference in influence from the 6th month and attains its maximum value from the 12th month to the 14th month. (3) In the construction of the safety management system, the degree of influence in new coalmines was as follows: safety policy > safety management organization structure > safety management procedures. Among them, especially in the first 18 months, the impact of the safety policy was most apparent. However, in the production mine, the degree of influence was as follows: safety management organization structure > safety management procedures > safety policy, but the difference is very small. (4) The degree of influence on the construct of safety ability was as follows: safety knowledge > safety psychology = safety habits > safety awareness, but the difference on the impact was small.
This paper focusses on real-time detection and abnormal state prediction through a set of wireless equipment of fire water system to provide a better solution for fire inspection. The main goal of ...this research is to improve the fire extinguishing efficiency. Firefighting and rescue operations are urgent, and concealed or dry fire hydrants may cause failure cases of firefighting. To prevent this situation, this paper proposed the wireless equipment of fire water system to monitor the multiple indicators of outdoor hydrant, indoor hydrant, and sprinkler network. The objective of the experiment is to realize the real-time monitoring and obtain the data information of the state of the fire water system. Also, the multiple linear regression analysis method is adopted to analyze the monitored water pressure data to achieve rapid identification of abnormal water pressure value. The results indicate that the data transmission of the wireless equipment of fire water system is reliable, the pressure is accurately monitored below 0.40 MPa, and the average relative error of abnormal water pressure monitoring results is less than 6%. The new equipment and algorithm are used not only to monitor the state of water supply system, but also to depict the change of water consumption in the monitoring environment and predict the unconventional state, which provides directional help for fire patrol and inspection.
•Common study on fire risk are conducted in 283 Chinese cities.•Seven socioeconomic determinants are identified to have a strong correlation with urban fire risk.•Cities are clustered by per capita ...GRP to get better models.•Multivariate models for urban fire risk are well validated.
The traditional storage method of fire accident cases is mainly in the form of text, and it is difficult to effectively conduct comprehensive analysis due to the limited ability to display key ...information and fire knowledge. In this paper, a structured storage form of building fire cases was proposed based on knowledge graph, which can comprehensively describe and visualize the fire causes, the dynamic fire development process and evacuation process. It enables readers to get information and knowledge from building fire cases intuitively, and supports the comprehensive analysis for building fire prevention strategies. The knowledge graphs are constructed for two common building types (residential and public buildings), and have the capacity to reflect the dynamic development law of fires from ignition to spread in different buildings. Meanwhile, as the occupants’ evacuation is the first concern when a fire occurs, the knowledge graphs also visualize the relationship among various conditions in the evacuation process. Different application scenarios are displayed in the paper, including case query, root-cause analysis and consequence forecasting, which shows the advantages and applicability of building fire knowledge graph.
Summary
The traditional research of building fire probability analysis is from statistics or fire science. This paper combines the two methods and aims to improve the statistical method of building ...ignition probability determination according to the research conclusion of fire science. The specific factors that affect the ignition probability are divided into three aspects: humans, ignition sources and combustibles and environments. On this basis, the Bayesian network of building ignition probability is constructed, the nodes and conditional probability table in the Bayesian network are introduced in detail, according to which the ignition probability of building can be calculated quantitatively and objectively. Then some typical buildings are chosen as examples for the application of the method, the posterior probability value is calculated by obtaining the relevant building information and substituting them into the Bayesian network. The ignition probability is dynamic, and the comparison with the statistical data of building fire also proves its rationality.
