The work presented in this paper used a quantitative analysis of relevant risks through the development of fault tree analysis and risk analysis methods to aid real time risk prediction and safety evaluation of leak in a storage tank. Criticality of risk elements and their attributes can be used with real time data to predict potential failures likely to occur. As an example, a risk matrix was used to rank risk of events that could lead to a leak in a storage tank and to make decisions on risks to be allowed based on past statistical data. An intelligent system that recognizes increasing level(s) and draws awareness to the possibility of additional increase before unsafe levels are attained was used to analyse and make critical decisions. After a visual depiction of relationships between hazards and controls had been actualized, dynamic risk modelling was used to quantify the effect controls can potentially have on hazards by applying historical and real-time data into a probabilistic model. The output of a dynamic risk model is near real-time quantitative predictions of risk likelihood. Results from the risk matrix analysis method mixed with RTD and FTA were analyzed, evaluated, and compared.

本文提出的工作通过故障树分析和风险分析方法的发展对相关风险进行定量分析，以帮助对储罐泄漏进行实时风险预测和安全评估。风险要素的严重程度及其属性可以与实时数据一起使用，以预测可能发生的潜在故障。例如，风险矩阵用于对可能导致储罐泄漏的事件风险进行排序，并根据过去的统计数据对允许的风险做出决策。一个智能系统可以识别增加的水平并在达到不安全水平之前引起人们对额外增加的可能性的认识，用于分析和做出关键决策。在对危害和控制之间的关系进行可视化描述后，通过将历史和实时数据应用到概率模型中，动态风险模型被用来量化控制可能对危害产生的影响。动态风险模型的输出是对风险可能性的近乎实时的定量预测。对风险矩阵分析方法与 RTD 和 FTA 混合的结果进行了分析、评估和比较。