Improving Accuracy of Frequency Estimation of Major Vapor Cloud Explosions for Evaluating Control Room Location through Quantitative Risk Assessment

摘要

Frequency estimation of vapor cloud explosions (VCE) are traditionally based on sparsernVCE incidents data analysis while process conditions that generate VCE's have a widernspectrum giving VCE's with different strengths. The present paper is focused onrndeveloping a systematic methodology to estimate the frequency of VCEs based onrnprocess and plant conditions in order to find optimal location of a control room usingrnquantitative risk assessment (QRA). In the presented approach, after classification ofrnplant areas according to variables likely to generate different release conditions, arncomprehensive release study is carried out to determine individual probable leakages.rnConsequently, only those leakages that meet the criteria to launch a strong enough VCErnare fed to an event tree in order to estimate the final VCE frequency. Compared torntraditional methods, the new proposed approach has the advantages of both beingrnsupported by a more populated database of leakage frequencies not explosion incidents,rnand that it features a multi-variable functionality of process/plant conditions. The firstrnadvantage guarantees the accuracy and the latter lets one to use the methodology torndifferentiate between process units with regard to VCE frequency.