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Chen X, Bose N, Brito M, Khan F, Zou T. A copula-based method of risk prediction for autonomous underwater gliders in dynamic environments. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2024; 44:244-263. [PMID: 37105939 DOI: 10.1111/risa.14149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 10/06/2022] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
Autonomous underwater gliders (AUGs) are effective platforms for oceanic research and environmental monitoring. However, complex underwater environments with uncertainties could pose the risk of vehicle loss during their missions. It is therefore essential to conduct risk prediction to assist decision making for safer operations. The main limitation of current studies for AUGs is the lack of a tailored method for risk analysis considering both dynamic environments and potential functional failures of the vehicle. Hence, this study proposed a copula-based approach for evaluating the risk of AUG loss in dynamic underwater environments. The developed copula Bayesian network (CBN) integrated copula functions into a traditional Bayesian belief network (BBN), aiming to handle nonlinear dependencies among environmental variables and inherent technical failures. Specifically, potential risk factors with causal effects were captured using the BBN. A Gaussian copula was then employed to measure correlated dependencies among identified risk factors. Furthermore, the dependence analysis and CBN inference were performed to assess the risk level of vehicle loss given various environmental observations. The effectiveness of the proposed method was demonstrated in a case study, which considered deploying a Slocum G1 Glider in a real water region. Risk mitigation measures were provided based on key findings. This study potentially contributes a tailored tool of risk prediction for AUGs in dynamic environments, which can enhance the safety performance of AUGs and assist in risk mitigation for decision makers.
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Affiliation(s)
- Xi Chen
- Faculty of Engineering and Applied Science, Memorial University of Newfoundland, Canada
| | - Neil Bose
- Faculty of Engineering and Applied Science, Memorial University of Newfoundland, Canada
| | - Mario Brito
- Southampton Business School, University of Southampton, University Road, Southampton, UK
| | - Faisal Khan
- Mary Kay O'Connor Process Safety Center, Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas, USA
| | - Ting Zou
- Faculty of Engineering and Applied Science, Memorial University of Newfoundland, Canada
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2
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Ortega Chamorro LC, Cañón Barriga JE. Urban risks due to climate change in the Andean municipality of Pasto, Colombia: A Bayesian network approach. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:2017-2032. [PMID: 36646454 DOI: 10.1111/risa.14086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
The current trends of climate change will increase people's exposure to urban risks related to events such as landslides, floods, forest fires, food production, health, and water availability, which are stochastic and very localized in nature. This research uses a Bayesian network (BN) approach to analyze the intensity of such urban risks for the Andean municipality of Pasto, Colombia, under climate change scenarios. The stochastic BN model is linked to correlational models and local scenarios of representative concentration trajectories (RCP) to project the possible risks to which the municipality of Pasto will be exposed in the future. The results show significant risks in crop yields, food security, water availability and disaster risks, but no significant risks on the incidence of acute diarrheal diseases (ADD) and acute respiratory infections (ARI), whereas positive outcomes are likely to occur in livestock production, influenced by population growth. The advantage of the BN approach is the possibility of updating beliefs in the probabilities of occurrence of events, especially in developing, intermediate cities with information-limited contexts.
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3
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Zhang M, Zhang L, Cao X, Li B, Zhou A. FRAM-based causal analysis and barrier measures to mitigate dust explosions: A case study. PLoS One 2023; 18:e0287328. [PMID: 37319180 PMCID: PMC10270615 DOI: 10.1371/journal.pone.0287328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/02/2023] [Indexed: 06/17/2023] Open
Abstract
Both the number of dust explosion accidents and the resulting number of casualties have increased dramatically in recent years. To reduce this risk of dust explosions, we use the functional resonance analysis method (FRAM) to analyze the cause of the dust explosion accident at the Kunshan factory and propose barrier measures to prevent such accidents. The functional units that changed in the production system during the accident and how these functional units coupled to eventually cause the dust explosion were examined and explained. In addition, barrier measures were developed for functional units that changed during production and emergency systems defined to block the propagation of changes between functions and prevent resonance. Through case study, the identification of key functional parameters in both triggering the initial explosion and in then allowing its spread are key to define barriers to prevent a recurrence of such an event. FRAM uses system function coupling instead of traditional linear causality to explain the accident process, and develops barrier measures for changing function units, providing a novel thinking strategy and method for the analysis of accidents and their prevention.
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Affiliation(s)
- Meng Zhang
- School of Environment and safety Engineering, North University of China, Taiyuan, P. R. China
| | - Lei Zhang
- School of Environment and safety Engineering, North University of China, Taiyuan, P. R. China
| | - Xiong Cao
- School of Environment and safety Engineering, North University of China, Taiyuan, P. R. China
| | - Baolin Li
- School of Environment and safety Engineering, North University of China, Taiyuan, P. R. China
| | - Aitao Zhou
- School of Emergency Management and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, China
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4
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Chen XL, Lin WD, Liu CX, Yang FQ, Guo Y, Li X, Yuan SQ, Reniers G. An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents. J Loss Prev Process Ind 2023. [DOI: 10.1016/j.jlp.2023.105027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
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5
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Jafari MJ, Pouyakian M, Mozaffari P, Laal F, Mohamadi H, Pour MT, Hanifi SM. A new approach to chemicals warehouse risk analysis using computational fluid dynamics simulation and fuzzy Bayesian network. Heliyon 2022; 8:e12520. [PMID: 36593826 PMCID: PMC9803688 DOI: 10.1016/j.heliyon.2022.e12520] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/14/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
This study aims to assess the risk of chemicals warehouse using a Bayesian networks (BNs) and computational fluid dynamics (CFD). A methodology combining Bow-Tie (BT), fuzzy set theory (FST), and Bayesian network was employed, in which the BT was drawn for chemical spill scenarios. FST was utilized for the estimation of the basic events (BEs) occurrence probability, and the probability of interaction among a set of variables was obtained using BNs. Pool fire scenario radiation heat flux was evaluated using CFD code, fire dynamic simulator (FDS), and the solid flame model (SFM). Fail in forklift brake system (BE1), was the most significant cause for a chemical spill. Based on the CFD model, the heat flux is 31 kW/m2 at a distance of 3.5 m from the fire, decreasing to 6.5 m gradually. The maximum safety distance of 4 m is predicted by the CFD for heat flux that exceeds 12.5 kW/m2; however, SFM predicts approximately 4.5 m. According to the results, the amount of posterior risk is higher than the prior value. The framework presented in the chemicals warehouse for consequence analysis and dynamic risk assessment (DRA) of pool fire could be used for preventing the accidents and domino effects in the chemicals warehouse.
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Affiliation(s)
- Mohammad Javad Jafari
- Department of Occupational Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mostafa Pouyakian
- Department of Occupational Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Parvaneh Mozaffari
- Department of Occupational Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereydoon Laal
- Social Determinants of Health Research Center, Department of Occupational Health Engineering, Birjand University of Medical Sciences, Birjand, Iran
| | - Heidar Mohamadi
- Department of Occupational Health and Safety, School of Health, Larestan University of Medical Sciences, Larestan, Iran
| | - Masoud Taheri Pour
- Department of Environment Tehran Branch Islamic Azad University, Tehran, Iran
| | - Saber Moradi Hanifi
- Department of Occupational Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran,Corresponding author.
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6
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Zhao P, Li T, Wang B, Li M, Wang Y, Guo X, Yu Y. The Scenario Construction and Evolution Method of Casualties in Liquid Ammonia Leakage Based on Bayesian Network. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:16713. [PMID: 36554599 PMCID: PMC9779567 DOI: 10.3390/ijerph192416713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/01/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
In China, food-freezing plants that use liquid ammonia, which were established in the suburbs in the 1970s, are being surrounded by urban built-up areas as urbanization progresses. These plants lead to extremely serious casualties in the event of a liquid ammonia leakage. The purpose of this thesis was to explore the key factors of personnel protection failure through the scenario evolution analysis of liquid ammonia leakage. The chain of emergencies and their secondary events were used to portray the evolutionary process of a full scenario of casualties caused by liquid ammonia leakage from three dimensions: disaster, disaster-bearing bodies, and emergency management. A Bayesian network model of liquid ammonia leakage casualties based on the scenario chain was constructed, and key nodes in the network were derived by examining the sensitivity of risk factors. Then, this model was applied to a food-freezing plant in Beijing. The results showed that inadequate risk identification capability is a key node in accident prevention; the level of emergency preparedness is closely related to the degree of casualties; the emergency disposal by collaborative onsite and offsite is the key to avoiding mass casualties. A basis for emergency response to the integration of personnel protection is provided.
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Affiliation(s)
- Pengxia Zhao
- School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology (Beijing Municipal Institute of Labour Protection), Beijing 100077, China
| | - Tie Li
- School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Biao Wang
- School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
| | - Ming Li
- School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
| | - Yu Wang
- Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology (Beijing Municipal Institute of Labour Protection), Beijing 100077, China
| | - Xiahui Guo
- Safety Culture Research Center, Beijing Academy of Emergency Management Science and Technology, Beijing 100052, China
| | - Yue Yu
- Institute of Smart Ageing, Beijing Academy of Science and Technology, Beijing 100000, China
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7
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Modeling cause-and-effect relationships among variables affecting work stress based on fuzzy DEMATEL method. JOURNAL OF PUBLIC MENTAL HEALTH 2022. [DOI: 10.1108/jpmh-03-2022-0023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
Several variables can affect work stress. This study aims to model the cause-and-effect relationships among different variables that can predict work stress based on one of the most important fuzzy multicriteria decision-making methods used to investigate the cause-and-effect relationships among variables.
Design/methodology/approach
This study was conducted in 2020, including 17 experts in safety management, occupational health and work psychology, based on the fuzzy decision-making trial and evaluation laboratory method as a robust approach to identify the cause-and-effect relationships among different variables.
Findings
Shift work, lack of job satisfaction, mental health, mental overload, fatigue, job security, sleep disorders, environmental discomfort, work pressure, job knowledge (this could mean expertise/level of qualifications/familiarity with the job), work complexity and role conflict were found to be the most significant variables affecting work stress. Moreover, the cause-and-effect model of relationships among variables showed that shift work and lack of job satisfaction are root causes, and mental health, fatigue, mental workload, sleep disorder and environmental discomfort are direct causes.
Originality/value
Although the results of this study demonstrate that work stress can be influenced by 12 different variables, the modeling results show that some variables, such as shift work and lack of job satisfaction, can directly or indirectly impact other variables and thus result in work stress.
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8
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Zerrouki H. Risk assessment of a liquefied natural gas process facility using bow‐tie and Bayesian networks. PROCESS SAFETY PROGRESS 2022. [DOI: 10.1002/prs.12341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Hamza Zerrouki
- Department of Process Engineering University Amar Telidji of Laghouat Laghouat Algeria
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9
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Fire Parameters of Spruce (Picea abies Karst. (L.)) Dust Layer from Different Wood Technologies Slovak Case Study. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12020548] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
The issue of the formation of wood dust particles in the work environment is still an actual topic in terms of its impact on employee health and the risk of fire or explosion in a woodworking operation. This article deals with the characteristics of spruce dust (Picea abies Karst. (L.)), which was taken from several types of wood technology. Experimental samples of spruce dust were taken from four types of sawing technologies, including grinding, briquetting and from the suction device container. The physical parameters of the samples taken were monitored and the particle size analysis was determined. The granulometric composition of the samples is significantly different. The sample of spruce wood dust from sawing has the most numerous fraction (250 µm), while the sample from grinding has the most numerous fraction 63–250 µm (87%).The aim of the paper was to monitor the minimum ignition temperature of the settled spruce dust layer and to look for a significant dependence of the minimum ignition temperature and ignition time on the type of spruce dust sample. A significant dependence was not confirmed. Significant moisture dependence of the samples was confirmed; the highest humidity was observed in the container, the lowest in sawing.
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10
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Tang X, Shu Y, Liu W, Li J, Liu M, Yu H. An Optimized Weighted Naïve Bayes Method for Flood Risk Assessment. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2021; 41:2301-2321. [PMID: 33928661 DOI: 10.1111/risa.13743] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 08/03/2020] [Accepted: 04/05/2021] [Indexed: 06/12/2023]
Abstract
Floods occur frequently and cause considerable damage to local environments. Effectively assessing the flood risk contributes to reducing loss caused by such disasters. In this study, the weighted naïve Bayes (WNB) method was selected to evaluate flood risk, and the entropy weight method was employed to compute the weights. A sampling and verifying model was employed to generate the most accurate conditional probability table (MACPT) to calculate the probability of flooding. When using the framework integrating WNB with the sampling and verifying model, previous studies could not obtain a WNB-based MACPT and the WNB classification accuracy, for lacking WNB functions that could be called directly. Facing this issue, in this study we developed WNB functions with the MATLAB platform to directly integrate with the sampling and verifying model to generate a WNB-based MACPT, contributing to the greater interpretability and extensibility of the model. Shantou and Jieyang cities in China were selected as the study area. The results demonstrate that: (1) a WNB-based MACPT can reflect the real spatial distribution of flood risk and (2) the WNB outperform the NB when integrated with the sampling and verifying model. The resulting gridded estimation reveal a detailed spatial pattern of flood risk, which can serve as a realistic reference for decision making related to floods. Furthermore, the proposed method uses less data, which would be helpful in developing countries where long-term intensive hydrologic monitoring is limited.
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Affiliation(s)
- Xianzhe Tang
- School of Geography, South China Normal University, Guangzhou, 510631, China
| | - Yuqin Shu
- School of Geography, South China Normal University, Guangzhou, 510631, China
| | - Wei Liu
- School of Geography, South China Normal University, Guangzhou, 510631, China
| | - Jiufeng Li
- School of Geography, South China Normal University, Guangzhou, 510631, China
| | - Minnan Liu
- College of Horticulture and Landscape Architecture, Zhongkai University of Agriculture and Engineering, Guangzhou, Guangdong, 510225, China
| | - Huafei Yu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China
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11
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Hou WH, Wang XK, Zhang HY, Wang JQ, Li L. Safety risk assessment of metro construction under epistemic uncertainty: An integrated framework using credal networks and the EDAS method. Appl Soft Comput 2021. [DOI: 10.1016/j.asoc.2021.107436] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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12
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Real-time risk assessment of explosion on offshore platform using Bayesian network and CFD. J Loss Prev Process Ind 2021. [DOI: 10.1016/j.jlp.2021.104518] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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13
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Risk Assessment of Circuit Breakers Using Influence Diagrams with Interval Probabilities. Symmetry (Basel) 2021. [DOI: 10.3390/sym13050737] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
This paper deals with uncertainty, asymmetric information, and risk modelling in a complex power system. The uncertainty is managed by using probability and decision theory methods. More specifically, influence diagrams—as extended Bayesian network functions with interval probabilities represented through credal sets—were chosen for the predictive modelling scenario of replacing the most critical circuit breakers in optimal time. Namely, based on the available data on circuit breakers and other variables that affect the considered model of a complex power system, a group of experts was able to assess the situation using interval probabilities instead of crisp probabilities. Furthermore, the paper examines how the confidence interval width affects decision-making in this context and eliminates the information asymmetry of different experts. Based on the obtained results for each considered interval width separately on the action to be taken over the considered model in order to minimize the risk of the power system failure, it can be concluded that the proposed approach clearly indicates the advantages of using interval probability when making decisions in systems such as the one considered in this paper.
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14
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Sun H, Wang H, Yang M, Reniers G. On the application of the window of opportunity and complex network to risk analysis of process plants operations during a pandemic. J Loss Prev Process Ind 2020; 68:104322. [PMID: 33071470 PMCID: PMC7552987 DOI: 10.1016/j.jlp.2020.104322] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 09/29/2020] [Accepted: 10/07/2020] [Indexed: 11/16/2022]
Abstract
To quantify the pandemic specific impact with respect to the risk related to the chemical industry, a novel risk analysis method is proposed. The method includes three parts. Firstly, the two types of “window of opportunity” (WO) theory is proposed to divide an accident life cycle into two parts. Then, a qualitative risk analysis is conducted based on WO theory to determine possible risk factors, evolution paths and consequences. The third part is a quantitative risk analysis based on a complex network model, integrating two types of WO. The Fuzzy set theory is introduced to calculate the failure probabilities of risk factors and the concept of risk entropy is used to represent the uncertainty. Then the Dijkstra algorithm is used to calculate the shortest path and the corresponding probability of the accident. The proposed method is applied to the SCR denitrition liquid ammonia storage and transportation system. The results show that it is a comprehensive method of quantitative risk analysis and it is applicable to risk analysis during the pandemic. The pandemic impact with regard to human errors and accident stages are analyzed. The concept of the Window of opportunity (WO) is proposed. A new risk analysis model based on WO and complex network is proposed. Risk entropy is used to represent edge weights between nodes of complex network. The difference between the proposed method and BT and BN are discussed.
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Affiliation(s)
- Hao Sun
- College of Mechanical and Electronic Engineering, China University of Petroleum (East China), Qingdao, China
| | - Haiqing Wang
- College of Mechanical and Electronic Engineering, China University of Petroleum (East China), Qingdao, China
| | - Ming Yang
- Safety and Security Science Section, Department of Values, Technology, and Innovation, Faculty of Technology, Policy, and Management, Delft University of Technology, the Netherlands
| | - Genserik Reniers
- Safety and Security Science Section, Department of Values, Technology, and Innovation, Faculty of Technology, Policy, and Management, Delft University of Technology, the Netherlands.,Faculty of Applied Economics, Antwerp Research Group on Safety and Security (ARGoSS), Universiteit Antwerpen, 2000, Antwerp, Belgium.,CEDON, KULeuven, 1000, Brussels, Belgium
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15
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Analysis Factors That Influence Escalator-Related Injuries in Metro Stations Based on Bayesian Networks: A Case Study in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17020481. [PMID: 31940854 PMCID: PMC7014387 DOI: 10.3390/ijerph17020481] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 12/27/2019] [Accepted: 12/31/2019] [Indexed: 11/17/2022]
Abstract
Escalator-related injuries have become an important issue in daily metro operation. To reduce the probability and severity of escalator-related injuries, this study conducted a probability and severity analysis of escalator-related injuries by using a Bayesian network to identify the risk factors that affect the escalator safety in metro stations. The Bayesian network structure was constructed based on expert knowledge and Dempster–Shafer evidence theory, and further modified based on conditional-independence test. Then, 950 escalator-related injuries were used to estimate the posterior probabilities of the Bayesian network with expectation–maximization (EM) algorithm. The results of probability analysis indicate that the most influential factor in four passenger behaviors is failing to stand firm (p = 0.48), followed by carrying out other tasks (p = 0.32), not holding the handrail (p = 0.23), and another passenger’s movement (p = 0.20). Women (p = 0.64) and elderly people (aged 66 years and above, p = 0.48) are more likely to be involved in escalator-related injuries. Riding an escalator with company (p = 0.63) has a relatively high likelihood of resulting in escalator-related injuries. The results from the severity analysis show that head and neck injuries seem to be more serious and are more likely to require an ambulance for treatment. Passengers who suffer from entrapment injury tend to claim for compensation. Severe injuries, as expected, significantly increase the probability of a claim for compensation. These findings could provide valuable references for metro operation corporations to understand the characteristics of escalator-related injuries and develop effective injury prevention measures.
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16
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Risk Analysis of Chemical Plant Explosion Accidents Based on Bayesian Network. SUSTAINABILITY 2019. [DOI: 10.3390/su12010137] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Many chemical plant explosion accidents occur along with the development of the chemical industry. Meanwhile, the interaction and influence of various factors significantly increase the uncertainty of the evolution process of such accidents. This paper presents a framework to dynamically evaluate chemical plant explosion accidents. We propose twelve nodes to represent accident evolution and establish a Bayesian network model for chemical plant explosion accidents, combining historical data with expert experience to support the prevention, management, and real-time warning. Hypothetical scenarios and catastrophic explosion scenarios were analyzed by setting different combinations of states for nodes. Moreover, the impacts of factors such as factory type, material form, accident equipment, the emergency response on casualty and property loss are evaluated. We find that sensitivity of property loss and casualties to factory type and ongoing work are less significant; the equipment factors result in more casualties than that from personnel factors; the impact of emergency response on the accident results is significant; equipment safety management and personnel safety training are the most important measures to prevent chemical plant explosion risks.
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17
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Spatial–Temporal Analysis of Land Cover Change at the Bento Rodrigues Dam Disaster Area Using Machine Learning Techniques. REMOTE SENSING 2019. [DOI: 10.3390/rs11212548] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Disasters are an unpredictable way to change land use and land cover. Improving the accuracy of mapping a disaster area at different time is an essential step to analyze the relationship between human activity and environment. The goals of this study were to test the performance of different processing procedures and examine the effect of adding normalized difference vegetation index (NDVI) as an additional classification feature for mapping land cover changes due to a disaster. Using Landsat ETM+ and OLI images of the Bento Rodrigues mine tailing disaster area, we created two datasets, one with six bands, and the other one with six bands plus the NDVI. We used support vector machine (SVM) and decision tree (DT) algorithms to build classifier models and validated models performance using 10-fold cross-validation, resulting in accuracies higher than 90%. The processed results indicated that the accuracy could reach or exceed 80%, and the support vector machine had a better performance than the decision tree. We also calculated each land cover type’s sensitivity (true positive rate) and found that Agriculture, Forest and Mine sites had higher values but Bareland and Water had lower values. Then, we visualized land cover maps in 2000 and 2017 and found out the Mine sites areas have been expanded about twice of the size, but Forest decreased 12.43%. Our findings showed that it is feasible to create a training data pool and use machine learning algorithms to classify a different year’s Landsat products and NDVI can improve the vegetation covered land classification. Furthermore, this approach can provide a venue to analyze land pattern change in a disaster area over time.
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18
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Fang W, Wu J, Bai Y, Zhang L, Reniers G. Quantitative risk assessment of a natural gas pipeline in an underground utility tunnel. PROCESS SAFETY PROGRESS 2019. [DOI: 10.1002/prs.12051] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Weipeng Fang
- Department of Safety Technology and ManagementChina University of Mining & Technology Beijing 100083 China
| | - Jiansong Wu
- Department of Safety Technology and ManagementChina University of Mining & Technology Beijing 100083 China
| | - Yiping Bai
- Department of Safety Technology and ManagementChina University of Mining & Technology Beijing 100083 China
| | - Laobing Zhang
- Safety and Security Science GroupDelft University of Technology Delft The Netherlands
| | - Genserik Reniers
- Safety and Security Science GroupDelft University of Technology Delft The Netherlands
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19
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Abstract
Urban dirty bomb attacking is a type of unconventional terrorism threatening the urban security all through the world. In this paper, a Bayesian network of urban dirty bomb attacking is established to analyze the risk of urban dirty bomb attacking. The impacts of factors such as occurrence time, location, wind fields, the size of dirty bomb, emergency response and defense approaches on casualty from both direct blast and radiation-caused cancers are examined. Results show that sensitivity of casualty from cancers to wind fields are less significant; the impact of emergency response on the direct casualty from blast is not large; the size of the dirty bomb results in more casualties from cancers than that from bomb explosions; Whether an attack is detected by the police is not that related to normal or special time, but significantly depends on the attack location; Furthermore, casualty from cancers significantly depends on the location, while casualty from blast is not considerably influenced by the attacking location; patrol and surveillance are less important than security check in terms of controlling the risk of urban dirt bomb, and security check is the most effective approach to decreasing the risk of urban dirty bomb.
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20
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Chen M, Wang K. A bow-tie model for analyzing explosion and fire accidents induced by unloading operation in petrochemical enterprises. PROCESS SAFETY PROGRESS 2018. [DOI: 10.1002/prs.11990] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Mengmeng Chen
- Beijing Key Laboratory for Precise Mining of Intergrown Energy and Resources; China University of Mining and Technology (Beijing); Beijing 10083 China
- School of Resource & Safety Engineering; China University of Mining & Technology (Beijing); Beijing 10083 China
| | - Kai Wang
- Beijing Key Laboratory for Precise Mining of Intergrown Energy and Resources; China University of Mining and Technology (Beijing); Beijing 10083 China
- School of Resource & Safety Engineering; China University of Mining & Technology (Beijing); Beijing 10083 China
- Hebei State Key Laboratory of Mine Disaster Prevention; North China Institute of Science and Technology; Beijing 101601 China
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21
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Ji J, Tong Q, Khan F, Dadashzadeh M, Abbassi R. Risk-Based Domino Effect Analysis for Fire and Explosion Accidents Considering Uncertainty in Processing Facilities. Ind Eng Chem Res 2018. [DOI: 10.1021/acs.iecr.8b00103] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jie Ji
- State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, China
| | - Qi Tong
- State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, China
| | - Faisal Khan
- Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador A1B 3X5, Canada
| | - Mohammad Dadashzadeh
- Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador A1B 3X5, Canada
- Hydrogen Safety Engineering and Research Centre (HySAFER), Ulster University, Newtownabbey, Northern Ireland BT37 0QB, U.K
| | - Rouzbeh Abbassi
- National Centre for Maritime Engineering and Hydrodynamics, Australian Maritime College, University of Tasmania, Launceston, Tasmania 7250, Australia
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22
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Zarei E, Azadeh A, Aliabadi MM, Mohammadfam I. Dynamic safety risk modeling of process systems using bayesian network. PROCESS SAFETY PROGRESS 2017. [DOI: 10.1002/prs.11889] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Esmaeil Zarei
- Center of Excellence for Occupational Health Engineering; Research Center for Health Sciences, Faculty of Health, Hamadan University of Medical Sciences; Hamadan Iran
| | - Ali Azadeh
- Center of Excellence for Intelligent-Based Experimental Mechanic; School of Industrial and Systems Engineering, University of Tehran; Tehran Iran
| | - Mostafa Mirzaei Aliabadi
- Center of Excellence for Occupational Health Engineering; Research Center for Health Sciences, Faculty of Health, Hamadan University of Medical Sciences; Hamadan Iran
| | - Iraj Mohammadfam
- Center of Excellence for Occupational Health Engineering; Research Center for Health Sciences, Faculty of Health, Hamadan University of Medical Sciences; Hamadan Iran
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23
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Wu J, Zhou R, Xu S, Wu Z. Probabilistic analysis of natural gas pipeline network accident based on Bayesian network. J Loss Prev Process Ind 2017. [DOI: 10.1016/j.jlp.2017.01.025] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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24
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Zarei E, Azadeh A, Khakzad N, Aliabadi MM, Mohammadfam I. Dynamic safety assessment of natural gas stations using Bayesian network. JOURNAL OF HAZARDOUS MATERIALS 2017; 321:830-840. [PMID: 27720467 DOI: 10.1016/j.jhazmat.2016.09.074] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Revised: 09/29/2016] [Accepted: 09/30/2016] [Indexed: 06/06/2023]
Abstract
Pipelines are one of the most popular and effective ways of transporting hazardous materials, especially natural gas. However, the rapid development of gas pipelines and stations in urban areas has introduced a serious threat to public safety and assets. Although different methods have been developed for risk analysis of gas transportation systems, a comprehensive methodology for risk analysis is still lacking, especially in natural gas stations. The present work is aimed at developing a dynamic and comprehensive quantitative risk analysis (DCQRA) approach for accident scenario and risk modeling of natural gas stations. In this approach, a FMEA is used for hazard analysis while a Bow-tie diagram and Bayesian network are employed to model the worst-case accident scenario and to assess the risks. The results have indicated that the failure of the regulator system was the worst-case accident scenario with the human error as the most contributing factor. Thus, in risk management plan of natural gas stations, priority should be given to the most probable root events and main contribution factors, which have identified in the present study, in order to reduce the occurrence probability of the accident scenarios and thus alleviate the risks.
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Affiliation(s)
- Esmaeil Zarei
- Center of Excellence for Occupational Health Engineering, Research Center for Health Sciences, Faculty of Health, Hamadan University of Medical Sciences, Hamadan, Iran.
| | - Ali Azadeh
- School of Industrial and Systems Engineering, Center of Excellence for Intelligent-Based Experimental Mechanic, College of Engineering, University of Tehran, Iran
| | - Nima Khakzad
- Safety and Security Science Section, Delft University of Technology, Delft, The Netherlands
| | - Mostafa Mirzaei Aliabadi
- Center of Excellence for Occupational Health Engineering, Research Center for Health Sciences, Faculty of Health, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Iraj Mohammadfam
- Center of Excellence for Occupational Health Engineering, Research Center for Health Sciences, Faculty of Health, Hamadan University of Medical Sciences, Hamadan, Iran.
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25
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Erbis S, Ok Z, Isaacs JA, Benneyan JC, Kamarthi S. Review of Research Trends and Methods in Nano Environmental, Health, and Safety Risk Analysis. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2016; 36:1644-1665. [PMID: 26882074 DOI: 10.1111/risa.12546] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Despite the many touted benefits of nanomaterials, concerns remain about their possible environmental, health, and safety (EHS) risks in terms of their toxicity, long-term accumulation effects, or dose-response relationships. The published studies on EHS risks of nanomaterials have increased significantly over the past decade and half, with most focused on nanotoxicology. Researchers are still learning about health consequences of nanomaterials and how to make environmentally responsible decisions regarding their production. This article characterizes the scientific literature on nano-EHS risk analysis to map the state-of-the-art developments in this field and chart guidance for the future directions. First, an analysis of keyword co-occurrence networks is investigated for nano-EHS literature published in the past decade to identify the intellectual turning points and research trends in nanorisk analysis studies. The exposure groups targeted in emerging nano-EHS studies are also assessed. System engineering methods for risk, safety, uncertainty, and system reliability analysis are reviewed, followed by detailed descriptions where applications of these methods are utilized to analyze nanomaterial EHS risks. Finally, the trends, methods, future directions, and opportunities of system engineering methods in nano-EHS research are discussed. The analysis of nano-EHS literature presented in this article provides important insights on risk assessment and risk management tools associated with nanotechnology, nanomanufacturing, and nano-enabled products.
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Affiliation(s)
- Serkan Erbis
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA
| | | | - Jacqueline A Isaacs
- Department of Mechanical and Industrial Engineering and Center for High-Rate Nanomanufacturing, Northeastern University, Boston, MA, USA
| | - James C Benneyan
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA
| | - Sagar Kamarthi
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA
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26
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Yu H, Khan F, Garaniya V. Modified Independent Component Analysis and Bayesian Network-Based Two-Stage Fault Diagnosis of Process Operations. Ind Eng Chem Res 2015. [DOI: 10.1021/ie503530v] [Citation(s) in RCA: 64] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Hongyang Yu
- National Centre for Maritime
Engineering and Hydrodynamics, Australian Maritime College, University of Tasmania, Launceston, TAS 7250, Australia
| | - Faisal Khan
- National Centre for Maritime
Engineering and Hydrodynamics, Australian Maritime College, University of Tasmania, Launceston, TAS 7250, Australia
| | - Vikram Garaniya
- National Centre for Maritime
Engineering and Hydrodynamics, Australian Maritime College, University of Tasmania, Launceston, TAS 7250, Australia
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