Search Results (8)

To mitigate the risk of hydrogen leakage in ship fuel systems powered by internal combustion engines, a Bayesian network model was developed to evaluate the risk of hydrogen fuel leakage. In conjunction with the Bow-tie model, fuzzy set theory, and the Noisy-OR Gate model, an in-depth analysis was also conducted to examine both the causal factors and potential consequences of such incidents. The Bayesian network model estimates the likelihood of hydrogen leakage at approximately 4.73 × 10⁻⁴ and identifies key risk factors contributing to such events, including improper maintenance procedures, inadequate operational protocols, and insufficient operator training. The Bow-tie model is employed to visualize the causal relationships between risk factors and their potential consequences, providing a clear structure for understanding the events leading to hydrogen leakage. Fuzzy set theory is used to address the uncertainties in expert judgments regarding system parameters, enhancing the robustness of the risk analysis. To mitigate the subjectivity inherent in root node probabilities and conditional probability tables, the Noisy-OR Gate model is introduced, simplifying the determination of conditional probabilities and improving the accuracy of the evaluation. The probabilities of flash or pool fires, jet fires, and vapor cloud explosions following a leakage are calculated as 4.84 × 10⁻⁵, 5.15 × 10⁻⁵, and 4.89 × 10⁻⁷, respectively. These findings highlight the importance of strengthening operator training and enforcing stringent maintenance protocols to mitigate the risks of hydrogen leakage. The model provides a valuable framework for safety evaluation and leakage risk management in hydrogen-powered ship fuel systems. Full article

Safety barriers (SBs) are important means of reducing failure risks of process systems. As barriers vary in type and function, their effectiveness needs to be evaluated in order to find a more reasonable configuration strategy. However, in practice, there is often a lack of accurate and complete data relating to SBs, which poses a significant challenge in quantitatively assessing their effectiveness. To address this issue, in this study, we propose a semi-quantitative approach for evaluating the effectiveness of both preventive and protective barriers in process systems by integrating expert elicitation, interval-valued intuitionistic fuzzy numbers (IVIFNs), and a bow-tie model. In this approach, the bow-tie model is first applied to describe the system failure scenarios and the action phases of the barriers, and then IVIFNs with expert judgment are introduced to obtain the failure probabilities of basic events and the effects of SBs. Subsequently, the effectiveness of each barrier is measured by comparing the relative change in failure risk due to the addition of the barrier. To verify the feasibility of this approach, a natural gas storage tank with some barriers was analyzed. The results show that the regular inspection of the deformation or damage of the storage tank has the highest effectiveness, followed by the installation and regular maintenance of safety electrical equipment. Furthermore, compared to a single barrier, multiple barriers can significantly reduce the system risk. Full article

Fires are one of the main disasters in underground engineering. In order to comprehensively describe and evaluate the risk of underground engineering fires, this study proposes a UEF risk assessment method based on EPB-FBN. Firstly, based on the EPB model, the static and dynamic information of the fire, such as the cause, occurrence, hazard, product, consequence, and emergency rescue, was analyzed. An EPB model of underground engineering fires was established, and the EPB model was transformed into a BN structure through the conversion rules. Secondly, a fuzzy number was used to describe the state of UEF variable nodes, and a fuzzy conditional probability table was established to describe the uncertain logical relationship between UEF nodes. In order to make full use of the expert knowledge and empirical data, the probability was divided into intervals, and a triangulated fuzzy number was used to represent the linguistic variables judged by experts. The α-weighted valuation method was used for de-fuzzification, and the exact conditional probability table parameters were obtained. Through fuzzy Bayesian inference, the key risk factors can be identified, the sensitivity value of key factors can be calculated, and the maximum risk chain can be found in the case of known evidence. Finally, the method was applied to the deductive analysis of three scenarios. The results show that the model can provide realistic analysis ideas for fire safety evaluation and emergency management of underground engineering. The proposed EPB risk assessment model provides a new perspective for the analysis of UEF accidents and contributes to the ongoing development of UEF research. Full article

The study and analysis of safety, health and environmental indicators in the risk assessment of landfill sites are essential to improving performance and reducing injuries. This study is essential in identifying effective criteria and providing useful solutions for proper waste control and management. In Gilan province, 2200 tons of waste enter landfills every day, and this has created a lot of pollution in the area. The methodology of this research was chosen using the opinions of experts and the Delphi technique. Factors affecting the risk assessment in the construction and operation phases were investigated in two phases. The risks of a landfill project were identified by combining (FANP) and (FTOPSIS) using a multi-criteria decision bow tie technique to rank and prioritize criteria. The results show that urban landfills are one of the environmental risk factors in cities. They often contaminate water sources. This has caused a disturbance in the stability of ecological systems. Using the bow tie model can control and prevent environmental health-safety risks caused by urban waste disposal. This can be a threat and a big factor in the destruction of ecosystem resources and services. The integrated approach used in this study provides a flexible tool for evaluating and developing municipal landfills. The risk assessment study proves that the most involved areas in the landfill are environment and health-safety, respectively. Socio-economic and cultural fields are in the next categories. Due to their nature and working process, lancets face many environmental, safety and health risks. The integrated approach (FANP) and (FTOPSIS) with bow ties are suitable methods for risk assessment in landfills. It is very important to use the bow tie technique in analyzing, examining and prioritizing risk sources for management and also control measures such as preventing and limiting high-risk sources. Full article

An innovative methodology is proposed to identify potential risk factors and possible accident escalation consequences, and to determine the evolution of an accident from cause to consequence, thereby to identify the most probable path and discover key risk factors along the path rapidly. Based on the principle of a directed weighted complex network (DWCN), the bow-tie (BT) model, risk entropy and the improved ant colony optimization (IACO) algorithm are integrated into this methodology. First, the qualitative analysis of risk evolution based on the BT model is carried out. The evolution development based on accident suppression can be divided into two stages: accident precursor stage and accident evolution stage. Then, a new method for mapping BT into DWCN is proposed. Lastly, the shortest path analysis of risk evolution based on the IACO algorithm is carried out, fuzzy set theory (FST) is introduced to calculate the failure probability of risk factors, and risk entropy is used to represent the uncertainty of risk propagation. Thus, the IACO algorithm can be used to calculate the shortest path of risk evolution. The proposed method is applied to oil and gas leakages in the FPSO oil and gas processing system. The results show that it is an effective method to identify the shortest evolution path and the most vulnerable risk factors. Full article

At present, the number of oil and gas gathering and transportation pipelines is numerous, and leakage accidents occur frequently. Each year, due to pipeline failure, there are immeasurable consequences for people and the environment around the affected pipelines. In order to reduce the risk of leakage accidents in heavy oil gathering pipelines and prevent the occurrence of major spills, it is of great significance to carry out safety assessments of them. However, failure data of these pipelines is seriously deficient and statistical methods used to evaluate pipeline safety are incompatible. Therefore, this paper proposes a risk assessment system for heavy oil gathering pipelines in the absence of failure data. Firstly, a Bayesian network (BN) for the leak safety evaluation of heavy oil gathering pipelines is established via mapping from a bow-tie (BT) model. Then, information diffusion theory is combined with fuzzy set theory to obtain the failure probability of each factor affecting the pipeline failure, and then the failure probability of the pipeline is obtained by the full probability formula. In addition, in order to assess the extent of consequences due to accidents, variable fuzzy set theory is used to comprehensively consider the consequences of the leakage of heavy oil gathering pipelines. Finally, the above two parts are combined to form a safety assessment system to realize risk management and control for pipelines, which is necessary to ensure the safety of heavy oil gathering pipelines. Full article

In view of the vegetation reduction caused by the continuous construction of oil and gas pipelines, the pipelines have been designed to be laid in one ditch to reduce land occupation. However, owing to the small spacing between the pipelines, the fault correlation between pipelines has been proven to increase the potential hazard of adjacent pipelines and routing environments. The neglect of failure correlation in existing risk assessment methods leads to inaccurate results, which will lead to errors in maintenance decisions. Therefore, this paper proposed a risk assessment system for pipelines using this laying method. In the risk assessment, pipelines laid in one ditch (PLOD) were regarded as a series system relative to the routing environment. Therefore, the functional relationship between the total risk of the pipeline system and the risk of each pipeline was obtained by combining the engineering system reliability theory with the mathematical induction method. In addition, fuzzy set theory combined with fault tree analysis was used to calculate the failure probability of each pipeline in the system. Event tree analysis was used to sort out all the possible consequences of pipeline failure, and then the consequences were unified into monetary units to evaluate the severity of failure consequences. Finally, the two parts were merged into a bow-tie diagram to realize the risk management and control of the pipeline. Meanwhile, risk acceptance criteria were formulated to analyze risks and to guide pipeline maintenance. This system provides a complete risk assessment system for the pipeline system laid in one ditch, including the methods of risk identification, risk assessment, and risk analysis, which are of great significance to ensure the safety of the pipeline and the surrounding environment using this laying method. Full article

The high hazard mechanical system (HHMS) has three characteristics in the petroleum and petrochemical industry (PPI): high risk, high cost, and high technology requirements. For a HHMS, part, component, and subsystem failures will result in varying degrees and various types of risk consequences, including unexpected downtime, production losses, economic costs, safety accidents, and environmental pollution. Thus, obtaining the quantitative risk level and distribution in a HHMS to control major risk accidents and ensure safe production is of vital importance. However, the structure of the HHMS is more complex than some other systems, making the quantitative risk analysis process more difficult. Additionally, a variety of uncertain risk data hinder the realization of quantitative risk analysis. A few quantitative risk analysis techniques and studies for HHMS exist, especially in the PPI. Therefore, a study on the quantitative risk analysis method for HHMS was completed to obtain the risk level and distribution of high-risk objects. Firstly, Fuzzy Set Theory (FST) was applied to address the uncertain risk data for the occurrence probability (OP) and consequence severity (CS) in the risk analysis process. Secondly, a fuzzy fault tree analysis (FFTA) and a fuzzy event tree analysis (FETA) were used to achieve quantitative risk analysis and calculation. Thirdly, a fuzzy bow-tie model (FBTM) was established to obtain a quantitative risk assessment result according to the analysis results of the FFTA and FETA. Finally, the feasibility and practicability of the method were verified with a case study on the quantitative risk analysis of one reciprocating pump system (RPS). The quantitative risk analysis method for HHMS can provide more accurate and scientific data support for the development of Asset Integrity Management (AIM) systems in the PPI. Full article