Dynamic risk assessment of storage tank using consequence modeling and fuzzy Bayesian network

Mohammadi, Heidar; Laal, Fereydoon; Mohammadian, Farough; Yari, Peyman; Kangavari, Mehdi; Moradi Hanifi, Saber

doi:10.1016/j.heliyon.2023.e18842

Cited by 9 publications

(3 citation statements)

References 41 publications

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“…These events were meticulously documented within the academic version of GeNIe software; the root node representing basic events, the middle node symbolizing intermediate events, and the central node embodying top events. Moreover, Conditional Probability Tables (CPTs) were formulated for various nodes and subsequently updated to assess their respective probabilities [ 46 , 47 ].…”

Section: Methodsmentioning

confidence: 99%

Providing a comprehensive approach to oil well blowout risk assessment

Satiarvand,

Orak,

Varshosaz

et al. 2023

PLoS ONE

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Drilling is one of the most dangerous activities in the oil and gas process industries. Therefore, a holistic approach was presented to prevent and control risks and reduce the uncertainty of blowouts, kick scenarios, and control layers based on the Fuzzy Bayesian Network (FBN). Four independent protection layers (IPLs) were used to evaluate the blowout outcome, and the failure probabilities of IPL1 and IPL2 were calculated with Fault Tree Analysis (FTA). Then, different events were transferred to the Bayesian Network (BN) in GeNIe software, and updated the probabilities. The Fuzzy Fault Tree (FFT) results reveal that the failure probabilities for IPL1 and IPL2 amount to 8.94×10−4 and 4.97×10−21, respectively. Also, the blowout probability results based on FFT were larger than FBN. According to FBN, the probability of the kick event was equal to 6.60×10−34. Sensitivity analysis showed that X1 (Mud volume/flow change) had the highest degree of importance in the blowout of oil wells. The results of this study can be used in both a preventive and reactive approach. Deductive and inductive reasoning, the dynamic nature and conditional dependencies, and causal relationships between events can make the model more realistic.

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Section: Methodsmentioning

confidence: 99%

Providing a comprehensive approach to oil well blowout risk assessment

Satiarvand,

Orak,

Varshosaz

et al. 2023

PLoS ONE

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“…Khoshakhlagh [ 12 ] presented a holistic model based on the Fuzzy Bayesian Network–Human Factor Analysis and Classification System (FBN-HFACS) to analyze the factors in the COVID-19 pandemic that related to risk management under uncertainty. Mohammadi [ 13 ] used an integrated approach including BT, fuzzy Bayesian networks, and consequence modeling to estimate risk in tank storage. Jabbari [ 14 ] presented a risk assessment method based on a fuzzy Bayesian network (FBN) and the William Fine method in low-voltage power distribution systems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic risk assessment of a coal slurry preparation system based on the structure-variable Dynamic Bayesian Network

Liu,

Wu,

Hou

2024

PLoS ONE

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In order to strengthen the safety management of coal slurry preparation systems, a dynamic risk assessment method was established by using the bow-tie (BT) model and the Structure-variable Dynamic Bayesian Network (SVDBN). First, the BT model was transformed into a static Bayesian network (BN) model of the failure of a coal slurry preparation system by using the bow-tie model and the structural similarity of the Bayesian cognitive science, based on the SVDBN recursive reasoning algorithm. The risk factors of the coal slurry preparation system were deduced using the Python language in two ways, and at the same time, preventive measures were put forward according to the weak links. In order to verify the accuracy and feasibility of this method, the simulation results were compared with those obtained using GeNIe software. The reasoning results of the two methods were very similar. Without considering maintenance factors, the failure rate of the coal slurry preparation system gradually increases with increasing time. When considering maintenance factors, the reliability of the coal slurry preparation system will gradually be maintained at a certain threshold, and the maintenance factors will increase the reliability of the system. The proposed method can provide a theoretical basis for the risk assessment and safety management of coal slurry preparation systems.

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“…Consequence modeling is mainly done using mathematical equations. Studies have recommended consequence modeling as an appropriate tool for designing the safety of hazardous industrial units 32 , 33 . Consequence modeling refers to the quantitative evaluation of the results or potential impact of a particular event or scenario.…”

Section: Introductionmentioning

confidence: 99%

Quantitative risk estimation of CNG station by using fuzzy bayesian networks and consequence modeling

Abbasi Kharajou,

Ahmadi,

Rafiei

et al. 2024

Sci Rep

Self Cite

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As one of the potential explosions and inflammation, compressed natural gas (CNG) stations in urban areas cause irreparable losses and casualties. Estimating risk assessment in gas stress based on coherent uses can reduce accidents in urban areas. The purpose of the present study was to estimate a small risk estimation at one of the CNG multipurpose stations, LPG, using combined models of the Fuzzy Bayesian Network, Bow-tie Diagram, and consequence modeling. This study was conducted based on the basic and 25 intermediate events. This study formed a seven-person safety team to identify the primary events and build the Bow-tie diagram. Then, because of the lack of a proper database, fuzzy theory was used to determine the probability of significant events. Bayesian networks were drawn based on the Bow-tie model using GeNLe software. Finally, the main events of the two Bow-tie, Bayesian network modeling, and risk estimation were performed with the help of PHAST/SAFETI (V8.22). The geographical information system software was used to zone the explosion effects. The Risk assessment result showed that the social risks and the Bayesian network model are more than Bow-tie, and the Bow-tie diagram is unacceptable. Therefore, using incompatible land uses in the vicinity of the CNG stations gives rise to the effects of accident scenarios in particular residential and administrative land uses, which decision-makers and city managers should consider. Based on the findings of this study, the obtained results can be utilized to implement effective control measures. These measures encompass devising a response plan tailored to address specific emergency conditions and conducting comprehensive training programs for the individuals and residents residing within the study area.

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Dynamic risk assessment of storage tank using consequence modeling and fuzzy Bayesian network

Cited by 9 publications

References 41 publications

Providing a comprehensive approach to oil well blowout risk assessment

Providing a comprehensive approach to oil well blowout risk assessment

Dynamic risk assessment of a coal slurry preparation system based on the structure-variable Dynamic Bayesian Network

Quantitative risk estimation of CNG station by using fuzzy bayesian networks and consequence modeling

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