Abstract In this study, a comprehensive approach based on the Fuzzy Bayesian Network (FBN) was presented to reduce completeness, modeling, and parameter uncertainties and to analyze the risk of hazardous material release in floating roof storage tanks accurately. In this method, managerial, organizational, human and process factors, were investigated using human and process HAZOP technique before the occurrence of accident scenarios. These factors were examined after the intended scenario in a sequential modeling approach based on SHIPP methodology as a barrier model. Moreover, according to the initial probabilities and interference of barriers, the relevant conditional probability tables (CPTs) were modified by utilizing l -NOR gates, and the accident scenario model was developed using the Bow-tie (BT) model. Triangular fuzzy numbers and expert opinion incorporated into the Bayesian network to deal with the uncertainty in the occurrence probability of basic events and safety barriers. The methanol storage tank was selected to present the applicability potential of the proposed model. The results showed that the validation of the position and conditional probabilities (CPs) of barriers in the BT structure will reduce the uncertainties, and the combination of FBN and l -NOR gate is an appropriate way to evaluate the risk of tanks accurately.

中文翻译：

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分析浮顶储罐风险的综合方法

摘要 在本研究中，提出了一种基于模糊贝叶斯网络 (FBN) 的综合方法，以减少完整性、建模和参数不确定性，并准确分析浮顶储罐中有害物质释放的风险。在这种方法中，在事故情景发生之前，使用人为和过程 HAZOP 技术对管理、组织、人为和过程因素进行了调查。在基于 SHIPP 方法作为障碍模型的顺序建模方法中，在预期场景之后检查这些因素。此外，根据障碍物的初始概率和干扰，利用l-NOR门修改相关条件概率表（CPT），并利用Bow-tie（BT）模型建立事故情景模型。将三角模糊数和专家意见纳入贝叶斯网络，处理基本事件和安全屏障发生概率的不确定性。选择甲醇储罐来展示所提出模型的适用潜力。结果表明，对BT结构中障碍物的位置和条件概率（CPs）进行验证会降低不确定性，FBN和l-NOR门的结合是准确评估坦克风险的合适方法。