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The main objective of healthcare centers is to ensure a consistent and high-purity oxygen supply for the safety of patients. Pressure Swing Adsorption (PSA) is a commonly used technique for supplying medical oxygen by eliminating nitrogen from the ambient air. Due to the increased fire risk associated with oxygen, any malfunctions in the oxygen supply system can lead to serious hospital fires. This study aimed to assess the reliability of the oxygen supply system using Fault Tree Analysis (FTA) based on both the traditional method and Intuitionistic Fuzzy Analysis. FTA is a logical analysis method used to identify events that could result in an undesirable top event and calculate the probability of its occurrence. The FTA of the PSA system outlined the logical sequence of events that could lead to the release of oxygen as a top event. The study revealed that the failure of the pressure switch in the concentrator, inadequate sealing, and the use of inappropriate materials for the seals were the primary basic events that led to the release of oxygen. Additionally, this study utilized the Intuitionistic Fuzzy System to quantify experts' opinions, providing more flexibility in handling ambiguous situations and considering both membership and non-membership functions simultaneously.

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Mining is one of the most risky and dangerous sectors. It is impossible to ignore the losses of life and material experienced by occupational accidents, which take place in the field of mining. Risk analysis begins with a risk assessment to identify the probability and severity of workplace hazards. Hazards must be controlled by precautions according to the risk score levels. In this study, a fault tree analysis method was conducted to analyze spontaneous combustion hazards and to predict future risks in underground coal mines. Three main causes of the top event were defined and for each of these causes, risk scores were computed using a fault tree analysis. Finally, the causes of spontaneous combustion, which is an event that is frequently encountered in coal mines, were discussed, and the spontaneous combustion risk probability was calculated as 0.3012 in cases of air entry into the gob and failure to prevent coal-air contact in development drifts. As a result of the study, the fundamental causes of spontaneous combustion, the greatest hazard in underground coal mining worldwide, have been examined in detail. The innovative approach introduced by the study aims to increase the awareness and recognition of conditions that lead to spontaneous combustion among industry workers and engineers through detailed evaluation. By doing so, it seeks to minimize the occurrence of spontaneous combustion incidents.•This paper introduces a main flowchart and countermeasure algorithm to prevent spontaneous combustion.•This paper also analyzes events which trigger spontaneous combustion and mentioned preventive measures for this events.

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Inter-basin water transfer projects are a common method used to balance water resources and meet regional demand, particularly in the drinking water supply sector. The potential failure risk associated with inter-basin water transfer projects was examined using Fault Tree Analysis (FTA) and Fuzzy Fault Tree Analysis (FFTA) methodologies in this study. Additionally, the conversion of Fault Tree models into Bayesian Network (BN) and Fuzzy Bayesian Network (FBN) models was explored. Ten basic events were identified as factors that could affect the success of inter-basin water transfer plans, including socio-political, environmental, water resource, economic, and technical criteria. Fault Tree and Fuzzy Fault Tree models were utilized to conduct a risk analysis, which was then converted into crisp and fuzzy FTA-BN through an integrated approach. This approach was applied to evaluate inter-basin water transfer scenarios from the Great Karun basin to the Central Iran Plateau. The superior scenario among eight water transfer scenarios was found to be water transfer from the Behesht-Abad Basin to Isfahan province and from the Khersan Basin to Kerman and Yazd provinces, with a failure risk of 0.649 and 0.601 respectively, based on the crisp and fuzzy integrated models. Basic events were ranked based on their contribution to the occurrence of the top event using two FIM and BI indices in the Fault Tree model and two indices of MI and SI in the Bayesian Network. Furthermore, after considering the correlation between basic events and risk factors, the risk obtained by crisp and fuzzy integrated models was found to increase to 0.811 and 0.789 respectively. The results of this study demonstrate that an integrated approach can assist decision-makers and stakeholders in evaluating inter-basin water transfer projects.

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A comparative study was conducted to compare the accident cause analysis methods of fault tree analysis (FTA) and 24Model. A major accident - the Xinjia Hotel collapse accident - was selected as the research object, the causes of the accident were reanalysed and accident prevention countermeasures were designed based on 24Model and FTA, respectively, and the systematic characteristics of 24Model were summarized. The research shows that both 24Model and FTA can carry out risk assessment, accident cause analysis and preventive countermeasure design based on their own rules. Different from FTA, 24Model has static and dynamic structures of specific forms, the definition of causes and factors in the model is more comprehensive and the analysis method is more hierarchical and normative. 24Model can analyse the deep-level cultural and system causes, but the analysis process does not use quantitative methods, only qualitative methods. 24Model has eight systematic characteristics, such as integrity, hierarchy and dynamics.

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Before introducing new treatment techniques, an investigation of hazards due to unintentional radiation exposures is a reasonable activity for proactively increasing patient safety. As dedicated software is scarce, we developed a tool for risk assessment to design a quality management program based on best practice methods, i.e., process mapping, failure modes and effects analysis and fault tree analysis. Implemented as a web database application, a single dataset was used to describe the treatment process and its failure modes. The design of the system and dataset allowed failure modes to be represented both visually as fault trees and in a tabular form. Following the commissioning of the software for our department, previously conducted risk assessments were migrated to the new system after being fully re-assessed which revealed a shift in risk priorities. Furthermore, a weighting factor was investigated to bring risk levels of the migrated assessments into perspective. The compensation did not affect high priorities but did re-prioritize in the midrange of the ranking. We conclude that the tool is suitable to conduct multiple risk assessments and concomitantly keep track of the overall quality management activities.

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The Internet of Things (IoT) is seen as the most viable solution for real-time monitoring applications. But the faults occurring at the perception layer are prone to misleading the data driven system and consume higher bandwidth and power. Thus, the goal of this effort is to provide an edge deployable sensor-fault detection and identification algorithm to reduce the detection, identification, and repair time, save network bandwidth and decrease the computational stress over the Cloud. Towards this, an integrated algorithm is formulated to detect fault at source and to identify the root cause element(s), based on Random Forest (RF) and Fault Tree Analysis (FTA). The RF classifier is employed to detect the fault, while the FTA is utilized to identify the source. A Methane (CH4) sensing application is used as a case-study to test the proposed system in practice. We used data from a healthy CH4 sensing node, which was injected with different forms of faults, such as sensor module faults, processor module faults and communication module faults, to assess the proposed model's performance. The proposed integrated algorithm provides better algorithm-complexity, execution time and accuracy when compared to FTA or standalone classifiers such as RF, Support Vector Machine (SVM) or K-nearest Neighbor (KNN). Metrics such as Accuracy, True Positive Rate (TPR), Matthews Correlation Coefficient (MCC), False Negative Rate (FNR), Precision and F1-score are used to rank the proposed methodology. From the field experiment, RF produced 97.27% accuracy and outperformed both SVM and KNN. Also, the suggested integrated methodology's experimental findings demonstrated a 27.73% reduced execution time with correct fault-source and less computational resource, compared to traditional FTA-detection methodology.

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BACKGROUND: One of the main problems that may put people's safety in danger is the lack of real-time detection, evaluation, and recognition of predictable safety risks. Current real-time risk identification solutions are limited to proximity sensing, which lack providing the exposed person with risk-specific information in real-time. Combined values of concurrently presented risks are either unrecognized or underestimated. OBJECTIVE: This study goes beyond the proximity sensing state-of-the-art by envisioning, planning, designing, developing, assembling, and examining an automated intelligent real-time risk (AIR) assessment system. METHODS: A holistic safety assessment approach is followed to include identification, prioritization, detection, evaluation, and control at risk exposure time. Multi-sensor technologies based on RFID are integrated with a risk assessment intelligent system. System prototype is developed and examined to prove the concept for on-foot building construction workers. RESULTS: The evaluation of AIR assessment system's performance proved its validity, significance, simplicity, representation, accuracy, precision, and timeliness. The reliability of providing quantitative proximity values of risk can be limited due to the signal attenuation; however, it can be reliable in providing risk proximity in a subjective linguistic fashion (Near/Far). CONCLUSION: The main contributions of the AIR assessment system are that the mobile wearable device can provide a linguistic meaningful risk assessment resultant value, the value represents the combined evaluation of concurrently presented risks, and can be sound delivered to the exposed person in real-time of exposure. Therefore, AIR system can be used as an effective prognostic risk assessment tool that can empower workers with real-time recognition and measurability of risk exposure.

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Strengthening the supervision of medical insurance funds is an important measure to promote the healthy and sustainable development of the medical security system. In January 2022, a tertiary general hospital in Beijing carried out risk identification and prevention and control practices for the use of medical insurance funds. By using such methods as fault tree analysis and risk matrix, the probability and impact of events were quantitatively evaluated, high-risk events during the use of medical insurance funds were identified, and corresponding risk prevention and control measures were developed, relying on intelligent regulatory systems. From January to November 2022, the hospital outpatient medical insurance refusal amount(20 080 yuan) caused by such high-risk events as exceeding drug instructions, exceeding medical insurance indications, and exceeding age limits decreased by 42.30% compared to the same period in 2021(11 585 yuan). The discharge and settlement time of medical insurance patients decreased from 3 working days to 1 working day. This practice had effectively improved the quality and efficiency of hospital medical insurance fund supervision, improved patients′ medical experience, and provided reference for strengthening the safe and standardized use of medical insurance funds by medical institutions.

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Background: In the near future, the rapid adoption of electric vehicles is inevitable, driven by environmental concerns and climate change awareness. However, this progressive trend also brings forth safety concerns and hazards, notably regarding the risk of EV fires, which have garnered significant media attention. This necessitates the need to study for comprehensive fire risk assessment strategies aimed at preventing and mitigating such incidents. Methods: This study presents a framework for assessing fire risks in EVs using Fault Tree Analysis (FTA). By integrating disparate data sources into a unified dataset, the proposed methodology offers a holistic approach to understanding potential hazards. The study embarked on a comprehensive exploration of EV fire causes through qualitative FTA. Results: Through this approach, the work discerned five major causes: human factors, vehicle factors, management factors, external factors, and unknown factors. Using a meticulous weighted average approach, the annual EV fire frequency for each country was deduced, revealing an average annual EV fire rate of 2.44 × 10 -4 fires per registered EV. This metric provides a significant benchmark, reflecting both the probability and inherent risk of such incidents. However, uncertainties in data quality and reporting discrepancies highlight the imperative of continued research. Conclusions: As EV adoption surges, this study underscores the importance of comprehensive, data-driven insights for proactive risk management, emphasizing the necessity for vigilant and adaptive strategies. The findings emphasize the pivotal role of this assessment in shaping response strategies, particularly for first responders dealing with EV fires. In essence, this research not only elevates the understanding of EV fire risks but also offer a foundation for future safety measures and policies in the domain.

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Hazardous material road transportation is one of the most challenging procedures performed by large trucks and trailers. In this study, after examining and analyzing road hazardous material transportation accidents, occurred over 5 years in Iran, the contributing factors of road hazardous material transportation accidents were determined. Subsequently, the introduced factors were prioritized using fault tree analysis and the Dempster-Shafer evidence theory. The results revealed that the frequency of accidents has significantly increased in recent years. It is shown that the three pivotal factors in road hazardous material transportation accidents were transport vehicle, packaging and loading of hazardous materials, and human factors. These findings provide an empirically supported theoretical basis for transportation corporations to take corrective and preventative measures to reduce the accident risks. A novel technique has been introduced for analyzing the causes of road hazardous material transportation accidents. Finally, the absence of hazardous material transportation companies in Iran is introduced as a critical reason for the higher frequency of such accidents in Iran compared to other countries.

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Clarifying the causes of subway construction accidents has an important impact on reducing the probability of accidents and protecting workers' lives and public property to a greater extent. A total of 138 investigation records of subway construction accidents from 2000 to 2020 were collected in this study. Based on a systemic analysis of 29 well-known accident causation models and the formative process of the subway construction accidents, we extracted the causative factors of subway construction accidents from the collected records. Furthermore, a causation analysis index system of subway accidents was proposed based on fault tree analysis (FTA), where we considered subway construction accidents as the top event and the five dimensions, i.e., human, equipment, environment, management, and safety culture, as first-level intermediate events. Moreover, 17 causative factors were considered to be related to the severity of subway construction accidents. It is found that human factors are prone to be critical to high-risk accidents. Finally, a Bayesian network (BN) was formed to explore the causative factors of high-risk subway construction accidents. Based on the combined application of FTA and BN, this study discusses the complex influence factors and their action routes to unsafe accidents in subway construction sites, and makes efforts to correspond safety decision basis for the management of China subway construction.

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A metro collapse accident is the main type of metro construction accidents. How to scientifically analyze the key cause factors and their interaction coupling mechanism of the existing metro collapse accidents is crucial to reduce the occurrence of metro collapse. Based on the Fault Tree Analysis (FTA) and the Behavior security "2-4" Model (24Model), the FTA-24Model accident cause analysis framework was constructed by combing their respective characteristics. To be more specific, a logical analysis program was developed to analyze the accident causes by the four-module analysis method. An empirical study was carried out by taking the "12.1" major cave-in accident at the construction site of the Metro Line 11 in Guangzhou as an example. Compared with the case accident report, the FTA-24Model framework analysis method can not only systematically deduce the logical relationship between the accident causes and provides a panorama of the accident cause chain and its evolution process, but also identify the key causes of accidents and their coupling risk effects. For a metro construction accident, this method can not only effectively investigate the accident causes, but also provide a reference for the formulation of prevention strategies.

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The control of the risks associated with major hazard events is critical to the safe and continuous operation of the process industry. Over the last decades, the process industry has been successful at establishing and implementing robust Process Safety Management (PSM) systems to prevent and mitigate the consequences of such major hazard events. While there exist some industry guidelines developed relatively recently for events initiated by natural disasters and security-related threats, for initiating events like outbreaks of pathogens and pandemics, there is currently a clear lack of understanding of the impact of the restrictions and disruption caused by a pandemic on the ability of companies operating major hazard facilities to keep controlling the risks associated to their hazardous operations. Moreover, there is no industry guideline on how to account for such an impact in PSM systems for process safety hazards. The recent COVID-19 outbreak caused serious disruptions to normal operations that have challenged industry in their ability to control risks. The objective of this paper is to perform an analysis of the impact of a pandemic situation on the implementation of selected elements of PSM systems related to the identification and evaluation of the risks of a major hazard and their control. The approach chosen involves the analysis of the root causes of the failure of the selected PSM elements using a Fault Tree Analysis method. The findings provide the first steps in the establishment of recommendations for the upgrade of PSM systems to face events such as pandemics.

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BACKGROUND: Although hydraulic support can help enterprises in their production activities, it can also cause fatal accidents. METHODS: This study established a composite risk-assessment method for hydraulic support failure in the mining industry. The key basic event of hydraulic support failure was identified based on fault tree analysis and gray relational analysis, and the evolution mechanism of hydraulic support failure was investigated based on chaos theory, a synthetic theory model, and cause-and-effect-layer-of-protection analysis (LOPA). RESULTS: After the basic events of hydraulic support failure are identified based on fault tree analysis, structure importance (SI), probability importance (PI), critical importance (CI), and Fussell-Vesely importance (FVI) can be calculated. In this study, we proposed the Fussell-Vesely-Xu importance (FVXI) to reflect the comprehensive impact of basic event occurrence and nonoccurrence on the occurrence probability of the top event. Gray relational analysis was introduced to determine the integrated importance (II) of basic events and identify the key basic events. According to chaos theory, hydraulic support failure is the result of cross-coupling and infinite amplification of faults in the employee, object, environment, and management subsystems, and the evolutionary process has an obvious butterfly effect and inherent randomness. With the help of the synthetic theory model, we investigated the social and organizational factors that may lead to hydraulic support failure. The key basic event, jack leakage, was analyzed in depth based on cause-and-effect-LOPA, and corresponding independent protection layers (IPLs) were identified to prevent jack leakage. IMPLICATIONS: The implications of these findings with respect to hydraulic support failure can be regarded as the foundation for accident prevention in practice.

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As an important part of the global shipping industry, hazardous cargo transportation at ports is concerned by countries around the world due to the great hazards and high risks during its operations. However, multiple hazardous cargo accidents have occurred at ports in recent years. The explosion accident of hazardous cargoes at Tianjin Port, China, in 2015 is a typical case. It is a topic worth in-depth study to figure out how to analyze the causation factors of such accident and propose effective governance strategies against them. This article takes the hazardous cargo explosion at Tianjin Port of China as the subject and systematically analyzes the causation factors of the accident based on the Fault Tree Analysis (FTA) method. It proposes a strategy for governing hazardous cargoes at the port. The analysis results show that the hazardous cargo explosion at the port has complicated causation factors, among which management and human factors play a predominant role in the overall accident causation structure. Other factors include environmental factors and cargo & facility factors. Finally, the corresponding safety governance strategy is proposed based on the structural relationship of various accident causation factors in the above analysis. This study can offer guidance for port enterprises to reduce hazardous cargo accidents at ports and provide an important basis for port authorities to formulate strategies on emergency management and emergency decision-making of hazardous cargo accidents at ports.

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This paper proposes a methodology to perform risk analysis of the virus spread. It is based on the coupling between CFD modelling of bioaerosol dispersion to the calculation of probability of contact events. CFD model of near-field sneeze droplets dispersion is developed to build the SARS-CoV-2 effect zones and to adequately capture the safe distance. The most shared classification of droplets size distribution of sneezes was used. Droplets were modeled through additive heating/evaporation/boiling laws and their impact on the continuous phase was examined. Larger droplets move behind the droplet nuclei front and exhibit greater vertical drop due to the effect of gravity. CFD simulations provided the iso-risk curves extension (i.e., the maximum distance as well as the angle) enclosed by the incident outcome effect zone. To calculate the risk indexes, a fault tree was developed and the probability of transmission assuming as of the top event "COVID-19 infection" was calculated starting from the virus spread curve, as main base case. Four phases of virus spread evolution were identified: initiation, propagation, generalised propagation and termination. For each phase, the maximum allowable close contact was computed, being fixed the values of the acceptable risk index. In particular, it was found that during the propagation case, the maximum allowable close contacts is two, suggesting that at this point lockdown should be activated. The here developed methodology could drive policy containment design to curb spread COVID-19 infection.

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The provision of sanitation services for fast-growing urban populations is one of the world's urgent challenges. Hutong neighborhoods in Beijing, capital of China, cannot be rebuilt due to the protection of historical heritage, while residents still need to keep the habit of defecating in public toilets. One hundred public toilets with non-sewered sanitation in the Hutong neighborhoods of Beijing were visited to investigate the actual operating status in response to the "toilet revolution" campaign. The fault tree approach was used to identify the barriers toward a decent and environment-friendly public toilet and evaluate potential risks from the malfunction of various components. Four subsystems are defined and elaborated to calculate the fault possibility. These subsystems are environment- and user-friendly, regarded as ancillary facilities, and used for fecal sludge (FS) management. Statistical analysis of targeted cases indicated that fault probabilities of environmental considerations, user-friendly considerations, ancillary facilities, FS management are calculated as 0.79, 0.96, 0.96, and 0, respectively. The subsystems were weighted using a Delphi method concept. Results showed that the well operation ratio of Beijing Hutong public toilets is only 32%, and the sanitation service value chain can be further optimized. This study also provides references for other countries, which are dedicated to promoting urban sanitation and public health.

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Risk assessment is an essential component of the occupational health and safety event prevention activity.The purpose of this study is to choose the most appropriate risk assessment method for hospitals. The main methods were compared. There are many assessment methods, each with its advantages and disadvantages, but none has been adapted to the specificities of hospital activity. We adapted the workplace assessment sheet from the INCDPM (National Research and Development Institute for Labor Protection Bucharest) method to the specific of the hospital units and used this method at the level of jobs, within the hospital's departments, calculating the global risk level per job position, workplace (department), and hospital. The clinical departments global risk level exceeds the average (3.00) for all jobs, but does not exceed, however, 3.50, representing an acceptable security level. For assess the psychosocial risks we used the ELVIE method. Looking ahead, the methods should be adapted to allow both numerical presentation of the results and graphic.

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This paper focuses on the fire risk assessment for commercial complex, as the variety of fire accidental triggers inside could be a big threat to the public fire safety, leading to catastrophic loss in human lives and properties. Both the qualitative and quantitative analysis were imposed on a typical large commercial complex to recognize the potential fire-causative factors in this paper. Applying the fault tree analysis, the basic events leading to fire are acquired, and they are then further reclassified based on the analytic hierarchy process. Taking the damage of the accident as the target layer and the fire-causative factors, the equipment operation factors and firefighting factors as the criterion layer, the assessment index is well established. The risk of each factor is quantitatively evaluated, and the effect of each factor on the target layer is analyzed. The result of the fault tree analysis and analytic hierarchy process shows good consistency, in which human behavior is the main factor leading to the fire occurrence, followed by the combustible material, the rescue speed and the staff assignment factors. The results are beneficial for general decisions and measures in public fire safety management.

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Organic dust explosions were and are still today a critical issue in the food, pharmaceutical, and fine chemical industry. Materials such as flour, corn starch, sugar and APIs represent a cause of severe accidents. In this framework, we investigated a modified version of Recursive Operability Analysis-Incidental Sequence Diagrams (ROA-ISD), called ROA Plus-ISD, specifically tailored to describe industrial processes involving organic combustible dusts. Compared to more classical techniques such as Hazard and Operability (HazOp), ROA-ISD allows for a direct generation of fault trees, providing a useful tool to connect Qualitative with Quantitative Risk Analysis (QRA). ROA Plus-ISD is very similar to ROA-Cause Consequence Diagrams (CCD), which has already proven to be an effective tool to perform both risk assessment on existing plants and reconstructing already occurred accidents, given its logical structure and width of the application fields. In this work, we modified specific parts of the standard ROA-CCD method: (1) the Failure Mode and Operability Analysis (FMEA) database has been structured in order to retrieve the well-known explosion pentagon (for dusts) and all the instruments, devices, apparatuses and controllers typical of industries which process organic dusts; (2) a new comprehensive list of process variables has been compiled. In this way, it is possible to tailor the information required for the generation of the fault trees concerning top events involving mainly dust explosions and fires. This method has been implemented in order to reconstruct the dynamics of the February 2008 Imperial Sugar refinery plant accident (Port Wentworth, GA, USA). Results demonstrated the applicability of the enhanced method by highlighting the criticalities of the process already showed by a previously detailed reconstruction performed by the Chemical Safety Board.

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