摘要: |
为动态研究LNG储罐的失效风险,利用蝴蝶结模型和贝叶斯模型识别导致泄漏的关键因素,预测各主要事件,即泄漏和各事故的发生概率;根据异常事件历史记录,动态更新各主要事件发生概率;基于无环量圆柱体绕流的风速矫正模型对高频高危事故进行了情景模拟。将上述方法应用于某LNG接收站储罐,研究结果表明:在73个基本因素中,附属管道应力腐蚀、阀体与阀盖接触不良、外部超压冲击、台风和部分人为及管理因素等是导致LNG储罐泄漏的主要原因;考虑到事件的多态和相对性后,泄漏概率从8.42×10-3增至9.28×10-2,各事故风险亦呈逐年递加态势,根据历史数据,最终增长幅度均可达111.06%;高危事故中喷射火和闪火最有可能发生,在既定条件下影响范围最大分别可达93.7 m和436.0 m,很可能会形成多米诺事故,造成严重的危害。 |
关键词: 蝴蝶结 贝叶斯 动态风险分析 风速矫正 情景模拟 |
DOI:10.3969/j.issn.1007-3426.2020.04.019 |
分类号: |
基金项目:辽宁省科学技术计划面上项目“三维数字油库风险防控与应急响应系统构效”(2015020604) |
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Dynamic risk analysis of continuous leakage of LNG storage tank |
Yang Lingpeng1, Du Shengnan1, Wang Weiqiang1, Wang Bo1, Geng Xiaoheng2
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1. College of Petroleum Engineering of Liaoning Shihua University, Fushun, Liaoning, China;2. Department of Chemical Engineering and Safety of Binzhou University, Binzhou, Shandong, China
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Abstract: |
In order to dynamically study the failure risk of LNG storage tanks, the bow-tie model and the Bayesian model are firstly constructed and utilized to identify the key factors leading to leakage and predict the probability of occurrence of each main event, i.e. the leakage and accident; furthermore, the probability of occurrence of each main event is dynamically updated according to the history records of abnormal events; finally, the wind speed correction model based on acyclic flow around cylinder is utilized to simulate the high frequency and risk accidents. Through applying the above methods to the LNG storage tank of a receiving station, the results show that among the 73 basic factors, stress corrosion of auxiliary pipeline, poor contact between valve body and bonnet, external overpressure, typhoon and partly human and management factors are the main causes of leakage of LNG storage tanks; considering the polymorphism and relativity of events, the probability of leakage increased from 8.42×10-3 to 92.8×10-3 and accidents increased by 111. 06% yearly according to the history data; of all accidents, jet fire and flash fire are most likely to occur with a maximum impact of 93.7 m and 436.0 m. |
Key words: bow-tie Bayesian dynamic risk analysis correction of wind speed scenario simulation |