Research

18 pages, 9174 KiB

Open AccessArticle

Creep Characteristics of Layered Rock Masses after Water Absorption Due to Structural Effects

by Huichen Xu, Xiaoming Sun, Yong Zhang, Chengwei Zhao, Chengyu Miao and Dong Wang

Int. J. Environ. Res. Public Health 2023, 20(5), 4055; https://doi.org/10.3390/ijerph20054055 - 24 Feb 2023

Viewed by 1148

Affected by the “three highs and one disturbance” (high ground pressure, high ground temperature, high permeability pressure, and strong mining disturbance), deep layered rock mass roadways often display large deformations, resulting in accidents and disasters from time to time. This paper aims to [...] Read more.

Affected by the “three highs and one disturbance” (high ground pressure, high ground temperature, high permeability pressure, and strong mining disturbance), deep layered rock mass roadways often display large deformations, resulting in accidents and disasters from time to time. This paper aims to study creep characteristics of layered rock masses after water absorption due to structural effects, combined with acoustic emission energy and dominant frequency value analysis. Experimental results show that as the water content decreases, the long-term strength of the rock sample increases, and the damage becomes more severe. Under the same water content state conditions, the rock samples with bedding angles of 0°, 30°, and 90° have high long-term strength and undergo severe failure, whereas rock samples with bedding angles of 45° and 60° have low long-term strength and undergo mild failure. Under the same water content, the initial energy release increases with the bedding angle. Under the same water content, the energy release during failure decreases first and then increases with the increasing bedding angle. The initial energy, the cumulative energy, the initial main frequency, and the main frequency at the time of failure tend to decrease with the increase in water content. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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14 pages, 1811 KiB

Open AccessArticle

Research on Evaluation of University Emergency Management Ability Based on BP Neural Network

by Ruili Hu, Ye Zhang and Longkang Wang

Int. J. Environ. Res. Public Health 2023, 20(5), 3970; https://doi.org/10.3390/ijerph20053970 - 23 Feb 2023

Viewed by 1099

Abstract

University emergency management ability is an important part of university safety management. To evaluate university emergency management ability scientifically, objectively, and accurately, this study constructs three first-level indexes, namely, pre-prevention ability, in-process control ability, and post-recovery ability, and 15 s-level indexes, including the [...] Read more.

University emergency management ability is an important part of university safety management. To evaluate university emergency management ability scientifically, objectively, and accurately, this study constructs three first-level indexes, namely, pre-prevention ability, in-process control ability, and post-recovery ability, and 15 s-level indexes, including the establishment of emergency management institutions; the construction of emergency plans; the allocation of emergency personnel, equipment, and materials; and the training and exercise of emergency plans. On the basis of the backpropagation (BP) neural network method and MATLAB platform, an evaluation model of university emergency management ability is constructed. The neural network evaluation model is trained with sample data, and a university in Beijing is adopted as an example to verify the good prediction effect of the model. The results show that applying the evaluation model based on the BP neural network to the emergency management ability of colleges and universities is feasible. The model provides a new method to evaluate the emergency management ability of colleges and universities. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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19 pages, 5470 KiB

Open AccessArticle

Suppression Characteristics and Mechanism of Molasses Solution on Coal Dust: A Low-Cost and Environment-Friendly Suppression Method in Coal Mines

by Jianguo Liu, Tianyang Wang, Longzhe Jin, Gang Li, Shu Wang, Yixuan Wei, Shengnan Ou, Yapeng Wang, Jingge Xu, Minglei Lin, Jiahui Wang and Xianfeng Liu

Int. J. Environ. Res. Public Health 2022, 19(24), 16472; https://doi.org/10.3390/ijerph192416472 - 08 Dec 2022

Cited by 5 | Viewed by 1518

Abstract

Coal dust pollution poses a serious public health threat. This study aimed to investigate the feasibility of creating a coal dust suppressant using molasses, a byproduct of the sugar industry. We studied the effects of a molasses solution of varying concentrations (i.e., ranging [...] Read more.

Coal dust pollution poses a serious public health threat. This study aimed to investigate the feasibility of creating a coal dust suppressant using molasses, a byproduct of the sugar industry. We studied the effects of a molasses solution of varying concentrations (i.e., ranging from 0% (pure water) to 40%) on the moisture, bonding, and wind erosion properties of coal dust. Overall, the effectiveness of the molasses increased with their concentration, and it manifested itself in the following way: (1) the molasses improved the anti-evaporation ability of wet coal dust. For example, the evaporation mass of the coal dust wetted using a molasses solution decreased by 82.8%; (2) molasses effectively agglutinated coal dust; (3) molasses can effectively decrease the surface tension and increase the viscosity of the wetting solution. The surface tension of the molasses solution reached 41.37 mN/m and the viscosity increased to 6.79 mPa·s; (4) molasses can significantly suppress the wind erosion of deposited coal dust, with its wind erosion mass decreasing 99.1%; finally, (5) the effectiveness of molasses at suppressing coal dust was discussed at a molecular level. This study highlights the feasibility of a low-cost and environment-friendly dust suppressant in coal mines. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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11 pages, 321 KiB

Open AccessArticle

Comprehensive Evaluation of University Safety Culture Construction Level Based on “2–4” Model

by Ruili Hu, Ye Zhang and Beifang Gu

Int. J. Environ. Res. Public Health 2022, 19(23), 16145; https://doi.org/10.3390/ijerph192316145 - 02 Dec 2022

Viewed by 1093

Abstract

Based on the “2–4” model of accident causation, a comprehensive index system of the safety culture construction level in colleges and universities is set up. This system consists of 4 primary indicators and 28 secondary indicators. Taking a university as an example, applying [...] Read more.

Based on the “2–4” model of accident causation, a comprehensive index system of the safety culture construction level in colleges and universities is set up. This system consists of 4 primary indicators and 28 secondary indicators. Taking a university as an example, applying the analytic hierarchy process and fuzzy comprehensive evaluation method, this study establishes a comprehensive evaluation model to evaluate the construction level of the university’s safety culture. The results show that the construction level of the university’s safety culture is consistent with the actual situation. This study provides useful insights and feasible paths for promoting the safety and stability of colleges and universities and building a higher level of safety on campus. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

17 pages, 1822 KiB

Open AccessArticle

Changes in Air Quality during the Period of COVID-19 in China

by Xin Xu, Shupei Huang, Feng An and Ze Wang

Int. J. Environ. Res. Public Health 2022, 19(23), 16119; https://doi.org/10.3390/ijerph192316119 - 02 Dec 2022

Viewed by 1266

Abstract

This paper revisits the heterogeneous impacts of COVID-19 on air quality. For different types of Chinese cities, we analyzed the different degrees of improvement in the concentrations of six air pollutants (PM2.5, PM10, SO₂, NO₂, CO, and O₃ [...] Read more.

This paper revisits the heterogeneous impacts of COVID-19 on air quality. For different types of Chinese cities, we analyzed the different degrees of improvement in the concentrations of six air pollutants (PM2.5, PM10, SO₂, NO₂, CO, and O₃) during COVID-19 by analyzing the predictivity of air quality. Specifically, we divided the sample into three groups: cities with severe outbreaks, cities with a few confirmed cases, and cities with secondary outbreaks. Ensemble empirical mode decomposition (EEMD), recursive plots (RPs), and recursive quantitative analysis (RQA) were used to analyze these heterogeneous impacts and the predictivity of air quality. The empirical results indicated the following: (1) COVID-19 did not necessarily improve air quality due to factors such as the rebound effect of consumption, and its impacts on air quality were short-lived. After the initial outbreak, NO₂, CO, and PM2.5 emissions declined for the first 1–3 months. (2) For the cities with severe epidemics, air quality was improved, but for the cities with second outbreaks, air quality was first enhanced and then deteriorated. For the cities with few confirmed cases, air quality first deteriorated and then improved. (3) COVID-19 changed the stability of the air quality sequence. The predictability of the air quality index (AQI) declined in cities with serious epidemic situations and secondary outbreaks, but for the cities with a few confirmed cases, the AQI achieved a stable state sooner. The conclusions may facilitate the analysis of differences in air quality evolution characteristics and fluctuations before and after outbreaks from a quantitative perspective. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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19 pages, 2910 KiB

Open AccessArticle

Comparative Study on International Research Hotspots and National-Level Policy Keywords of Dynamic Disaster Monitoring and Early Warning in China (2000–2021)

by Jie Gao, Wu Zhang, Chunbaixue Yang, Rui Wang, Shuai Shao, Jiawei Li, Limiao Zhang, Zhijian Li, Shu Liu and Wentao Si

Int. J. Environ. Res. Public Health 2022, 19(22), 15107; https://doi.org/10.3390/ijerph192215107 - 16 Nov 2022

Cited by 1 | Viewed by 1420

Abstract

For more than 20 years, disaster dynamic monitoring and early warning have achieved orderly and sustainable development in China, forming a systematic academic research system and top-down policy design, which are inseparable from the research of China’s scientific community and the promotion of [...] Read more.

For more than 20 years, disaster dynamic monitoring and early warning have achieved orderly and sustainable development in China, forming a systematic academic research system and top-down policy design, which are inseparable from the research of China’s scientific community and the promotion of government departments. In the past, most of the research on dynamic disaster monitoring and early warning focused on specific research in a certain field, scene, and discipline, while a few studies focused on research review or policy analysis, and few studies combined macro and meso research reviews in academia with national policy analysis for comparative analysis. It is necessary and urgent to explore the interaction between scholars’ research and policy deployment, which can bring theoretical contributions and policy references to the top-down design, implementation promotion, and academic research of China’s dynamic disaster monitoring and early warning. Based on 608 international research articles on dynamic disaster monitoring and early warning published by Chinese scholars from 2000–2021 and 187 national policy documents published during this period, this paper conducts a comparative analysis between the knowledge maps of international research hotspots and the co-occurrence maps of policy keywords on dynamic disaster monitoring and early warning. The research shows that in the stage of initial development (2000–2007), international research articles are few and focused, and research hotspots are somewhat alienated from policy keywords. In the stage of rising development (2008–2015), after the Wenchuan earthquake, research hotspots are closely related to policy keywords, mainly in the fields of geology, engineering disasters, meteorological disasters, natural disasters, etc. Meanwhile, research hotspots also focus on cutting-edge technologies and theories, while national-level policy keywords focus more on overall governance and macro promotion, but the two are gradually closely integrated. In the stage of rapid development (2016–2021), with the continuous attention and policy promotion of the national government, the establishment of the Ministry of Emergency Management, and the gradual establishment and improvement of the disaster early warning and monitoring system, research hotspots and policy keywords are integrated and overlapped with each other, realizing the organic linkage and mutual promotion between academic research and political deployment. The motivation, innovation, integration, and transformation of dynamic disaster monitoring and early warning are promoted by both policy and academic research. The institutions that issue policies at the national level include the State Council and relevant departments, the Ministry of Emergency Management, the Ministry of Water Resources, and other national ministries and commissions. The leading affiliated institutions of scholars’ international research include China University of Mining and Technology, Chinese Academy of Sciences, Wuhan University, Shandong University of Science and Technology, and other institutions. The disciplines involved are mainly multidisciplinary geosciences, environmental sciences, electrical and electronic engineering, remote sensing, etc. It is worth noting that in the past two to three years, research and policies focusing on COVID-19, public health, epidemic prevention, environmental governance, and emergency management have gradually increased. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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12 pages, 5058 KiB

Open AccessArticle

Microseismic Precursors of Coal Mine Water Inrush Characterized by Different Waveforms Manifest as Dry to Wet Fracturing

by Rui Yu, Jiawei Qian, Liang Liu, Huasheng Zha and Nan Li

Int. J. Environ. Res. Public Health 2022, 19(21), 14291; https://doi.org/10.3390/ijerph192114291 - 01 Nov 2022

Cited by 3 | Viewed by 1239

Abstract

Microseismic monitoring systems have been widely installed to monitor potential water hazards in limestone of the coal floor. The temporal and spatial distribution of rock fracture-induced microseismic events can be used as early warning indicators of potential water inrush from the coal floor. [...] Read more.

Microseismic monitoring systems have been widely installed to monitor potential water hazards in limestone of the coal floor. The temporal and spatial distribution of rock fracture-induced microseismic events can be used as early warning indicators of potential water inrush from the coal floor. We established a microseismic monitoring system in the working face of Wangjialing coal mine. Besides traditional fluid-independent rock fracture-induced microseismic waveforms, fluid-dependent hybrid-frequency microseismic waveforms also play important roles in determining the microseismic precursors of water inrush. Hybrid-frequency microseismic waveforms have a sharp P wave and no obvious S wave phase. We infer that the first high-frequency signal is caused by the brittleness of the rock in the floor under the influence of the water pressure. The second low-frequency signal is caused by the water oscillations in the fractures. These hybrid-frequency waveforms represent the development of fracturing. In addition, the lifting height of the complete aquiclude above the confined water is very limited, and the water inrush from the floor is often closely related to these hidden faults. Therefore, the activation signal of hidden faults in the working face of coal mining can be monitored to effectively warn about the water inrush from the coal seam floor caused by faults. By analyzing different microseismic events, the monitoring and early warning of water disaster in the coal mine floor can be improved. This will help in taking measures in advance within the mine to ensure personnel safety and to reduce property losses. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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17 pages, 6485 KiB

Open AccessArticle

Enhancing Methane Recovery with Cryogenic Liquid CO₂ Cyclic Injection: Determination of Cyclic Injection Parameters

by Duo Zhang and Shixing Fan

Int. J. Environ. Res. Public Health 2022, 19(20), 13155; https://doi.org/10.3390/ijerph192013155 - 13 Oct 2022

Viewed by 1330

Abstract

Carbon dioxide (CO₂) is both a primary greenhouse gas and a readily available energy source. In this study, a new underground coal permeability enhancement technique utilizing cryogenic liquid CO₂ (L-CO₂) cyclic injection is proposed. The key parameters that [...] Read more.

Carbon dioxide (CO₂) is both a primary greenhouse gas and a readily available energy source. In this study, a new underground coal permeability enhancement technique utilizing cryogenic liquid CO₂ (L-CO₂) cyclic injection is proposed. The key parameters that determine the feasibility of this technique are cycle period and cycle number within a fixed working period. The optimal value of these two parameters mainly depends on the pore structure evolution law of coal cores before and after cryogenic L-CO₂ cyclic freeze–thaw. Accordingly, nuclear magnetic resonance (NMR) was employed to study the evolution characteristics of the fracture networks and pore structures in coal cores subjected to different freeze–thaw cyclic modes. The results demonstrated that the amplitude and width of all peaks of the T₂ spectra of the three coal cores (lignite, gas coal, and 1/3 coking coal) increased with an increase in the number of injection cycles. Additionally, as the number of freeze–thaw cycles (N_c) increased, the total porosity and effective porosity of the coal cores increased linearly before stabilizing, while the residual porosity first steadily diminished and afterwards became constant. Furthermore, the variation in the total porosity and residual porosity of the coal cores continuously diminished with an increase in the level of metamorphism. The NMR permeability of the coal cores showed a similar pattern to the porosity. Accordingly, the optimal parameters for cryogenic L-CO₂ cyclic injection during a complete working time were determined to be N_c = 4 and P_c = 30 min. A field test demonstrated that after L-CO₂ cyclic freeze–thaw treatment, the average gas drainage concentration of a single borehole in the test region increased by 1.93 times, while the pure flow of a single gas drainage borehole increased by 2.21 times. Finally, the gas attenuation coefficient decreased from 0.036 to 0.012. We concluded that the proposed permeability enhancement technique transformed coal seams from hard-to-drain to drainable. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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20 pages, 5414 KiB

Open AccessArticle

Forecasting and Planning Method for Taxi Travel Combining Carbon Emission and Revenue Factors—A Case Study in China

by Lixin Yan, Bowen Sheng, Yi He, Shan Lu and Junhua Guo

Int. J. Environ. Res. Public Health 2022, 19(18), 11490; https://doi.org/10.3390/ijerph191811490 - 13 Sep 2022

Cited by 3 | Viewed by 1237

Abstract

The efficiency and emission levels of taxi operations are influenced by taxi drivers’ empirical judgments of hotspot travel areas. In this study, we exploited vehicle specific power (VSP) approaches and taxi trajectory data in a 1000 × 1000 m grid to calculate emission [...] Read more.

The efficiency and emission levels of taxi operations are influenced by taxi drivers’ empirical judgments of hotspot travel areas. In this study, we exploited vehicle specific power (VSP) approaches and taxi trajectory data in a 1000 × 1000 m grid to calculate emission and revenue efficiency-related indicators and explored their spatial and temporal characteristics. Then, the entropy weight TOPSIS method was employed to identify the grids with the top comprehensive ranking of the indicators in the period to replace the driver experience. Finally, the k-means clustering method was utilized to identify the recommended road segments in the hotspot grid. The data from Nanchang City in China showed the following. (1) The study area was divided into 7553 grids, and the main travel and emission areas were located in the West Lake, Qingyunpu and Qingshan Lake districts (less than 200 grids). However, revenue efficiency-related indicators in this region are at a moderately low level. For example, the order revenue was about 0.9–1.2 RMB/min, and the average was 1.3–1.5 RMB/min. Areas with high trip demand had low revenue efficiency. (2) Five indicators related to emissions and revenue efficiency were selected. Of these, grid boarding points (G-bp) maintained the highest weight, reaching a maximum of 0.48 from 7:00 a.m. to 9:00 a.m. The ranking of secondary indicators was time varying. Hotspot grids and road segments were identified within each period. For example, from 1:00 a.m. to 3:00 a.m., (66,65), (68,65) were identified as hotspot grids. People’s Park North Gate near the road was identified as the recommended section from 1:00 a.m. to 3:00 a.m. This study can provide recommended grids and sections for idle cruising taxis. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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15 pages, 5071 KiB

Open AccessArticle

Response Characteristics of Electric Potential and Its Relationship with Dynamic Disaster during Mining Activities: A Case Study in Xuehu Coal Mine, China

by Yue Niu, Zhonghui Li, Enyuan Wang, Tiancheng Shan, Heng Wang, Shilong Xu, Wenyang Sun, Guanteng Wang, Xingzhuo Xue and Junqi Liu

Int. J. Environ. Res. Public Health 2022, 19(15), 8949; https://doi.org/10.3390/ijerph19158949 - 23 Jul 2022

Cited by 5 | Viewed by 1518

Abstract

Across the world, coal resource is widely utilized in industrial production. During coal mining activities, dynamic disasters may be induced, such as coal and gas outbursts, or rock burst, resulting in serious accidents or disasters. Previous studies have shown that electric potential (EP) [...] Read more.

Across the world, coal resource is widely utilized in industrial production. During coal mining activities, dynamic disasters may be induced, such as coal and gas outbursts, or rock burst, resulting in serious accidents or disasters. Previous studies have shown that electric potential (EP) signals can be produced during the deformation and fracture process of coal and rock mass under load. The abnormal response characteristics of EP can reveal the damage evolution and failure feather of coal mass. In this paper, the response characteristics of EP signals are analyzed with high gas testing during mining activities within deep coal seams, and the relationship between the EP response and outburst disaster hazard is studied. The results show that: (1) Under the comprehensive action of mining stress and gas effect, the coal mass was damaged and fractured, which can produce abundant EP signals, while the temporal EP response characteristics can reflect the loading state and damage evolution process inside the coal seam. (2) When coal cannon and a sudden increase of gas concentration occurred in the coal mass, the EP signal was at a high level and fluctuated violently. This can be regarded as precursory information for an outburst risk, which was verified by monitoring the results of mining stress and electromagnetic radiation (EMR). (3) Based on the unilateral inversion imaging method, EP spatial distribution law was studied and abnormal zones with high-value were identified. The zone is close to, or coincident with, the high value interval of EMR intensity and count indexes, which revealed the distribution characteristics of coal damage localization. Hence, EP monitoring results can forecast precursor information of outburst hazards temporally, and identify local zones with outburst hazard spatially. This study provides a new idea and application basis for using the EP method to monitor and prevent coal and rock dynamic disaster hazards in the field. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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17 pages, 4331 KiB

Open AccessArticle

Analysis of the Characteristics of CH₄ Emissions in China’s Coal Mining Industry and Research on Emission Reduction Measures

by Anyu Zhu, Qifei Wang, Dongqiao Liu and Yihan Zhao

Int. J. Environ. Res. Public Health 2022, 19(12), 7408; https://doi.org/10.3390/ijerph19127408 - 16 Jun 2022

Cited by 10 | Viewed by 2376

Abstract

CH₄ is the second-largest greenhouse gas and has a significant impact on global warming. China has the largest amount of anthropogenic coal mine methane (CMM) emissions in the world, with coal mining emissions (or gas emissions) accounting for 90% of total energy [...] Read more.

CH₄ is the second-largest greenhouse gas and has a significant impact on global warming. China has the largest amount of anthropogenic coal mine methane (CMM) emissions in the world, with coal mining emissions (or gas emissions) accounting for 90% of total energy industry emissions. The results of CH₄ emission inventories from previous studies vary widely, with differences in the spatial and temporal dimensions of gas emission factors of belowground mining being the main points of disagreement. Affected by the policies of “eliminating backward production capacity” and “transferring energy base to the northwest”, China’s coal production layout has changed greatly in the past ten years, but the closely related CH₄ emission factors have not been dynamically adjusted. This paper investigated 23 major coal producing provinces in China, obtained CH₄ emission data from coal mining, calculated CH₄ emission factors in line with current production conditions, and studied the reduction measures of coal mine gas emission. According to the CH₄ emission data of China’s coal mines in 2018, 15.8 Tg of methane is released per year in the coal mining industry in China, and 11.8 Tg after deducting recycling. Shanxi Province’s CH₄ emissions are much higher than those of other provinces, accounting for 35.5% of the country’s total emissions. The weighted CH₄ emission factor of coal mining in China is 6.77 m³/t, of which Chongqing is the highest at approximately 60.9 m³/t. Compared with the predicted value of the IPCC, the growth trend of CCM has slowed significantly, and the CH₄ utilization rate has gradually increased. This change may be aided by China’s coal industry’s policy to resolve excess capacity by closing many high-gas and gas outburst coal mines. In addition, the improvement of coal mine gas extraction and utilization technology has also produced a relatively significant effect. This paper determines the distribution of methane emissions and emission sources in China’s coal mining industry, which is useful in formulating CCM emission reduction targets and adopting more efficient measures. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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27 pages, 3416 KiB

Open AccessArticle

Modeling the Evolution of Major Storm-Disaster-Induced Accidents in the Offshore Oil and Gas Industry

by Gaogeng Zhu, Guoming Chen, Jingyu Zhu, Xiangkun Meng and Xinhong Li

Int. J. Environ. Res. Public Health 2022, 19(12), 7216; https://doi.org/10.3390/ijerph19127216 - 13 Jun 2022

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Abstract

Storm disasters are the most common cause of accidents in offshore oil and gas industries. To prevent accidents resulting from storms, it is vital to analyze accident propagation and to learn about accident mechanism from previous accidents. In this paper, a novel risk [...] Read more.

Storm disasters are the most common cause of accidents in offshore oil and gas industries. To prevent accidents resulting from storms, it is vital to analyze accident propagation and to learn about accident mechanism from previous accidents. In this paper, a novel risk analysis framework is proposed for systematically identifying and analyzing the evolution of accident causes. First, accident causal factors are identified and coded based on grounded theory (GT). Then, decision making trial and evaluation laboratory (DEMATEL) is integrated with interpretative structural modeling (ISM) to establish accident evolution hierarchy. Finally, complex networks (CN) are developed to analyze the evolution process of accidents. Compared to reported works, the contribution is threefold: (1) the demand for expert knowledge and personnel subjective influence are reduced through the data induction of accident cases; (2) the method of establishing influence matrix and interaction matrix is improved according to the accident frequency analysis; (3) a hybrid algorithm that can calculate multiple shortest paths of accident evolution under the same node pair is proposed. This method provides a new idea for step-by-step assessment of the accident evolution process, which weakens the subjectivity of traditional methods and achieves quantitative assessment of the importance of accident evolution nodes. The proposed method is demonstrated and validated by a case study of major offshore oil and gas industry accidents caused by storm disasters. Results show that there are five key nodes and five critical paths in the process of accident evolution. Through targeted prevention and control of these nodes and paths, the average shortest path length of the accident evolution network is increased by 35.19%, and the maximum global efficiency decreases by 20.12%. This indicates that the proposed method has broad applicability and can effectively reduce operational risk, so that it can guide actual offshore oil and gas operations during storm disasters. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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18 pages, 8966 KiB

Open AccessArticle

Experimental Study on Panic during Simulated Fire Evacuation Using Psycho- and Physiological Metrics

by Kaifeng Deng, Meng Li, Guanning Wang, Xiangmin Hu, Yan Zhang, Huijie Zheng, Koukou Tian and Tao Chen

Int. J. Environ. Res. Public Health 2022, 19(11), 6905; https://doi.org/10.3390/ijerph19116905 - 05 Jun 2022

Cited by 5 | Viewed by 2180

Abstract

Under circumstances of fire, panic usually brings uncertainty and unpredictability to evacuation. Therefore, a deep understanding of panic is desired. This study aims to dig into the underlying mechanism of fire evacuation panic by measuring and analysing psycho- and physiological indicators. In the [...] Read more.

Under circumstances of fire, panic usually brings uncertainty and unpredictability to evacuation. Therefore, a deep understanding of panic is desired. This study aims to dig into the underlying mechanism of fire evacuation panic by measuring and analysing psycho- and physiological indicators. In the experiment, participants watched a simulated train station within which three sets of stimuli were triggered separately. Eye movement and brain haemodynamic responses were collected during the watch, while questionnaires and interviews of emotions were conducted after. The analysed physiological indicators include the amplitude of pupil dilation, the time ratios of fixation and saccade, the binned entropy of gaze location, and the brain activation coefficients. The results of this research indicate that fire evacuation panic can be broken down into two elements. (1) Unawareness of situation: less knowledge of the situation leads to a higher level of panic; (2) Intensity of visual stimulation: the panic level is escalated with increased severity of fire that is perceived. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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9 pages, 4753 KiB

Open AccessArticle

Experimental Study on Dust Suppression Effect and Performance of New Nano-Composite Dust Suppressant

by Ming Li, Xinzhu Song, Gang Li, Jiao Tang and Zhi Li

Int. J. Environ. Res. Public Health 2022, 19(10), 6288; https://doi.org/10.3390/ijerph19106288 - 22 May 2022

Cited by 4 | Viewed by 2048

Abstract

In this paper, a nano-composite dust suppressant has been proposed to make up for the deficiency in wettability and moisturizing performance of a nanofluid dust suppressant. The nanometer material Al₂O₃, super absorbent polymer, carboxyl methyl starch sodium, and polyacrylamide [...] Read more.

In this paper, a nano-composite dust suppressant has been proposed to make up for the deficiency in wettability and moisturizing performance of a nanofluid dust suppressant. The nanometer material Al₂O₃, super absorbent polymer, carboxyl methyl starch sodium, and polyacrylamide were selected as effective components of it. The surface tension of the solution, evaporation resistance, and uniaxial compressive strength (UCS) were chosen as evaluation index to compare the suppression performance, these dust suppressants include the water, nanofluid dust suppressant and nano-composite dust suppressant, and the surface morphology of each tested material was observed by micro image analysis system. It was found that the surface tension and water loss rates of the nano-composite dust suppressants, respectively, decreased by 31.96% and 7.1%, and the maximum UCS increased by 31.82% compared with data of nanofluid dust suppressants. Since the nano-composite dust suppressant has good dispersion, permeability and bond performance, the suppressant film has fewer micro-cracks from the photos of microscopic image; it can improve the compactness and integrity of dust consolidation to prevent the evaporation of water and dust re-entrainment. Full article

(This article belongs to the Special Issue New Theory and Technology of Disaster Monitoring and Prevention)

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