화학공학소재연구정보센터
Journal of Loss Prevention in The Process Industries, Vol.43, 629-653, 2016
Quantitative risk analysis of loading and offloading liquefied natural gas (LNG) on a floating storage and regasification unit (FSRU)
Natural Gas is becoming an important energy source option and the capacity of the world to produce it is surging. Large reserves of natural gas exist worldwide, particularly in areas where the resources exceed the demand. Therefore, natural gas is liquefied for shipping; and its storage and regasification process usually occurs in onshore facilities. Recently, Liquefied Natural Gas (LNG) offshore terminals have been proposed as an attractive alternative solution. This paper presents a complete quantitative risk analysis (QRA) of undesired events that may occur during the loading and unloading of Liquefied Natural Gas (LNG) considering a typical LNG carrier and an offshore terminal similar to those operating in Brazil. Initially, a historical survey of accidents at LNG facilities, along with a detailed study of LNG carriers and LNG offshore terminals, is presented to support hazard identification. Once the potential hazardous events are categorized in some possible scenarios, a probabilistic potential hazard assessment is performed; moreover, the frequencies of occurrence of the undesired events are estimated. Afterwards, traditional consequence models are briefly discussed aiming to identify the weakness of each one that supports the specification of the model used in the consequence analysis of a specified case, which is evaluated by providing the data to estimate the total risk of the installation. The risk is evaluated in terms of social and individual risk. Lastly, possible control measures able to reduce the frequency of occurrence, or mitigate the impacts associated with the analyzed scenarios, are proposed and new risks levels are estimated by considering those control measures. The paper presents a complete QRA, presenting the tools and the models chosen to perform the analysis as well as some of the advantages and limitations regarding the use of these tools and models. (C) 2016 Elsevier Ltd. All rights reserved.