Natural gas pipeline network (NGPN) accident is a kind of catastrophic disaster as the hazard of natural gas may present a large-scale extension in NGPN that can easily result in cascading accidents. ...In this paper, the Bayesian network (BN) was employed to probabilistically analyze natural gas pipeline network accidents. On the basis of case-studies of typical NGPN accidents, eleven BN nodes were proposed to represent the evolution process of natural gas pipeline network accidents from failure causes to consequences. The conditional probabilities of every BN node were determined by expert knowledge with weighted treatments by the Dempster-Shafer evidence theory. Through giving evidences of some BN nodes with certain state values, the probabilities of evolution stages and consequences of the natural gas pipeline network accident can be estimated. The results indicate that the combination of Bayesian network and Dempster-Shafer evidence theory is an alternative method for evaluating NGPN accident, and the proposed framework can provide a more realistic consequence analysis since it could consider the conditional dependency in the evolution process of the NGPN accident. This study could be helpful for emergency response decision-making and loss prevention.
•Natural gas pipeline network accident is evaluated using BN and Dempster-Shafer theory.•Eleven BN nodes for representing natural gas pipeline network accident evolution are proposed.•Secondary disasters in natural gas pipeline accident are probabilistically analyzed.•The framework is helpful for disaster response decision-making and loss prevention.
Studies examining the relation between climate and human conflict often focus on the role of temperature and have diverging views on the significance of other climatic variables. Using a 6-year (from ...2009 to 2014) dataset of crime statistics collected in a medium size city of Tangshan in China, we find strong, positive correlations between temperature and both violent and property crimes. In addition, relative humidity is also positively correlated with Rape and Minimal Violent Robbery (MVR). The seasonal cycle is a significant factor that induces good correlations between crime rates and climatic variables, which can be reasonably explained by the Routine Activity theory. We also show that the combined impacts of temperature and relative humidity on crime rates can be reasonably captured by traditional heat stress indices. Using an ensemble of CMIP5 global climate change simulations, we estimate that at the end of the 21st century the rates of Rape (violent crime) and MVR (property crime) in Tangshan will increase by 9.5±5.3% and 2.6±2.1%, respectively, under the highest emission scenario (Representative Concentration Pathway 8.5). The gross domestic product (GDP) is also shown to be significantly correlated with MVR rates and the regression results are strongly impacted by whether GDP is considered or not.
Display omitted We investigate herein whether violent and property crimes are associated with temperature, relative humidity and their combination, heat stress indices, using a 6-year dataset of crime statistics collected in a medium size city of Tangshan in China. Then we estimate that at the end of the 21st century the rates of Rape (violent crime) and Minimal Violent Robbery (property crime) in Tangshan will increase by 9.5±5.3% and 2.6±2.1%, respectively, under the highest emission scenario (Representative Concentration Pathway 8.5).
•There are strong, positive correlations between temperature and both violent and property crimes.•Relative humidity is also positively correlated with Rape and Minimal Violent Robbery (MVR).•The gross domestic product (GDP) is shown to significantly affect the MVR rates.•The seasonal cycle is a significant factor that induces good correlations between crimes and climatic variables.•At the end of the 21st century the rates of Rape and MVR in Tangshan will increase by about 9.5% and 2.6% under RCP8.5.
•A three-dimensional source term estimation (3D-STE) model for predicting natural gas leakage and dispersion in utility tunnels is proposed.•The proposed model is validated by experimental data and a ...3D full-scale case with good effectiveness.•A framework is elaborated to provide guidance for the application of the 3D-STE model.
Natural gas compartment accommodated in utility tunnels is beneficial in meeting the pressing demand of energy supply and sustainable urban environment. However, the leaking gas characterized by flammable and explosive can pose a huge threat to the safe operation of the utility tunnel. When an unexpected gas leakage accident happens in the actual situation, the prior information associated with the leakage source is commonly unclear or unknown. Therefore, the absence of an available tool for reasonable leakage and dispersion prediction in the above scenario precludes the timely and appropriate emergency response treatment. In this study, a three-dimensional source term estimation (3D-STE) model with the combination of the computational fluid dynamics (CFD) and ensemble Kalman filter (EnKF) algorithm is proposed to achieve spatiotemporal gas concentration prediction and gas emission source estimation. In the proposed approach, the observation data can be incorporated into the gas dispersion simulations continuously, thus the simulation results can be revised by the observation data and the source term estimation of gas leakage can be achieved by employing the EnKF algorithm. A twin experiment is employed to validate the effectiveness and practicability of the proposed model. The results show that the proposed model can revise the prior errors in the gas leakage rate significantly and obtain an accurate prediction of gas concentration distribution as well as gas leakage rate. A feasible framework is also proposed serving as a good paradigm for the 3D-STE model application. This study helps for consequence assessment and emergency response of gas leakage accidents in utility tunnels.
In this study, three types of rectangular pool fires with the same equivalent area were conducted in a simulated cargo compartment to investigate the effects of sidewall distance and ambient pressure ...on fire behavior. Three dimensionless distances (
λ
=
0
,
λ
=
0.25
, and
λ
=
0.25
) and three ambient pressures (50 kPa, 76 k Pa, 101 kPa) were used in the experiments. The results showed that the sidewall had a significant impact on the burning of
n
-heptane pool fires, with the flame height increasing as the sidewall distance decreased and lower ambient pressure intensifying this trend. The shape of the flame also directly affected the sidewall temperature, which showed a different trend in different test cases due to the combined effect of air entrainment limitation and radiation enhancement from the flame. In addition, models for calculating the burning rate and flame height were developed by modifying classical models using the dimensionless distance
λ
, entrainment coefficient
EF
, and equivalent diameter
D
eq
.
Urbanization has been speeding up social and economic transformations in urban communities, the smallest social units in a city. However, urbanization brings challenges to urban management and ...security. Therefore, a system of risk prediction of crimes may be essential to crime prevention and control in urban communities and its system improvement. To tackle crime-related problems in urban communities, this paper proposes a model of daily crime prediction by combining Long Short-Term Memory Network (LSTM) and Spatial-Temporal Graph Convolutional Network (ST-GCN) to automatically and effectively detect the high-risk areas in a city. Topological maps of urban communities carry the dataset in the model, which mainly includes two modules - spatial-temporal features extraction module and temporal feature extraction module - to extract the factors of theft crimes collectively. We have performed the experimental evaluation of the existing crime data from Chicago, America. The results show that the integrated model demonstrates positive performance in predicting the number of crimes within the sliding time range.
In this study, three-dimensional macroporous sponge/Nitrogen-doped-carbon nanotube/polyaniline/manganese dioxide (S/N-CNT/PANI/MnO2) anode was prepared.
Display omitted
Interfacial electron transfer ...between electroactive biofilm and the electrode was crucial step for microbial fuel cells (MFCs). A three-dimensional multilayer porous sponge coating with nitrogen-doped carbon nanotube/polyaniline/manganese dioxide (S/N-CNT/PANI/mnO2) electrode has been developed for MFC anode. Here, the S/N-CNT/PANI/MnO2 anode can function as a biocapacitor, able to store electrons generated from the degradation of organic substrate under the open circuit state and release the accumulated electrons upon requirement. Thus, the mismatching of the production and demand of the electricity can be overcome. Comparing with the sponge/nitrogen-doped carbon nanotube (S/N-CNT) bioanode, S/N-CNT/PANI/MnO2 capacitive bioanode displays a strong interaction with the microbial biofilm, advancing the electron transfer from exoelectrogens to the bioanode. The maximum power density of MFC with S/N-CNT/PANI/MnO2 capacitive bioanode is 1019.5 mW/m2, which is 2.2 and 5.8 times as much as that of S/N-CNT/MnO2 bioanode and S/N-CNT bioanode (470.7 mW/m2 and 176.6 mW/m2), respectively. During the chronoamperometric experiment with 60 min of charging and 20 min of discharging, the S/N-CNT/PANI/MnO2 capacitive bioanode was able to store 10743.9 C/m2, whereas the S/N-CNT anode was only able to store 3323.4 C/m2. With a capacitive bioanode, it is possible to use the MFC simultaneously for production and storage of electricity
Urban underground facilities tend to be vulnerable to flood that is generated by the breaking of a dam or a levee, or a flash flood after an exceptional rainfall. Rapid and dynamic assessment of ...underground flood evolution process is of great significance for safety evacuation and disaster reduction. Taking advantage of the Delphi method to determine the Bayesian conditional probabilities collected by expert knowledge, this paper proposes an integrated Bayesian Network (BN) framework for rapidly and dynamically assessing the flood evolution process and consequences in underground spaces. The proposed BN framework, including seventeen nodes, can represent the flood disaster drivers, flood disaster bearers, flood mitigation actions, and on-site feedback information. Given evidences to specific nodes, the risk distribution of typical flood scenarios can be quantitatively estimated. The results indicate that the proposed framework can be useful for dynamically evaluating underground flood evolution process and identifying the critical influencing factors. This BN-based framework is helpful for “Scenario-Response”-based predictive analyses to support decision that is related to flood disaster emergency response.
High-quality LDH-SO
4
-CO
3
whiskers were synthesized via liquid precipitation method using MgSO
4
·7H
2
O and Al
2
(SO
4
)
3
·18H
2
O as precursors and Na
2
CO
3
-NaHCO
3
buffer solution as ...precipitant. The influence of buffer solution concentration on the characteristics of the samples was investigated. The as-grown whiskers were characterized by X-ray diffraction, transmission electron microscopy, and Brunauer-Emmett-Teller N
2
specific surface area measurements. The results show that the buffer solution concentration has significant impact on whiskers with intercalated structure. The LDH-SO
4
-CO
3
whiskers with well-defined geometry, distinct intercalated structure, decent quality, and excellent dispersing capability can be obtained under the following conditions: buffer solution volume ratio of 45%, reaction temperature of 83°C, and reaction time of 182 h. The obtained whiskers are well-crystallized and exhibit homogeneous morphology consisting of fber bars.
Accidents induced by natural disasters at sports sites may cause catastrophic loss of great concern. However, previous studies on risk assessments of sports sites have only focused on operational ...risk and equipment failure. With the frequent occurrence of extreme disasters, the risk of domino chains caused by natural disasters at large-scale events, such as large-scale winter sports sites, cannot be ignored. In this study, a natural disaster-induced accident-chain evolution analysis model (NAEA model) is proposed. Based on the results of the NAEA model, a fuzzy Bayesian network for domino accidents triggered by an earthquake at large-scale winter sports sites was established. Through sensitivity analysis and scenario analysis, it was found that fire and explosion accidents and crowded stampede accidents are the main causes of serious loss in domino disaster chains in large-scale sports sites. Simultaneously, improving the early warning capability, reliability of electrical equipment, and automatic sprinkler systems are the most effective ways to prevent and control major accidents. In addition, an optimal safety strategy improvement analysis was performed to facilitate the decision-making of safety managers to prevent serious accidents and reduce accident loss.
Quantitative analysis of school safety events in China Hu, Xiaofeng; Wu, Jiansong; Bai, Yiping ...
Journal of Safety Science and Resilience = An quan ke xue yu ren xing (Ying wen),
December 2020, 2020-12-00, 2020-12-01, Volume:
1, Issue:
2
Journal Article
Peer reviewed
Open access
Recent years have seen increasing school safety events along with growing numbers of students in China. In this paper, more than 400 serious school safety events between 2000 and 2018 in China were ...collected. The causes and characteristics of these events, taking into account the occurrence years, months, regions, education stages and types, were investigated. The results indicate that the number of school safety events has generally increased annually from 2000 to 2018 and can significantly vary each month, showing a higher frequency of occurrence during the “First Semester” (generally from September to December in China). Moreover, spatial distribution of school safety events is normally related to regional economic development; it was found that Guangdong, Jiangsu and Shandong is a first-level occurrence hotspots, followed by Zhejiang, Henan, Hebei and Sichuan, which are secondary occurrence hotspots. Furthermore, statistical analysis shows that the number of school safety events that occurred in kindergartens, primary schools and middle schools are approximately equal (around 1/3). Finally, it was found that the school safety events caused by “Accident” (such as school bus accidents, school fires, crowded stampedes and the collapses of school buildings) occupy a large proportion (57%).
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