Uncertainty techniques in liquefied natural gas (LNG) dispersion calculations

被引:25
|
作者
Siuta, Dorota [1 ,2 ]
Markowski, Adam S. [1 ]
Mannan, M. Sam [2 ]
机构
[1] Tech Univ Lodz, Fac Proc & Environm Engn, Safety Engn Dept, PL-90924 Lodz, Poland
[2] Texas A&M Univ, Mary Kay Oconnor Proc Safety Ctr, Fac Proc & Environm Engn, College Stn, TX 77843 USA
关键词
LNG; Uncertainty; Source term; Dispersion; Fuzzy arithmetic; Monte Carlo simulation; EVAPORATION;
D O I
10.1016/j.jlp.2012.07.020
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The dynamic development of the LNG sector increases the risk of major accidents. Uncontrolled releases of LNG during the processes of manufacturing, distribution, storage, and regasification can pose a serious threat to people, facilities, and the environment. Therefore, an important goal is to determine hazard zones and the extent of potential consequences associated with a release of LNG. The key issue is to estimate these with the least level of uncertainty. The largest part of uncertainty comes from the modeling of LNG release sources and performing dispersion calculations. It is connected with the application of different mathematical models, the adoption of a number of simplifying assumptions, approximations, empirical relations, constants, and a lack of knowledge. This paper proposes a general procedure for calculating the release rate and duration time of the LNG release, pool spreading, vaporization, as well as dispersion, taking into consideration the uncertainty. The procedure consists of two parts. The first part concerns the sensitivity analysis to identify the most uncertain parameters of the LNG source term and dispersion models. The second part applies to two techniques used to include the uncertainty aspects of fuzzy sets and the Monte Carlo method for calculating hazard zones. In order to provide a basis for comparison between these two approaches, the shape of the membership functions used in the fuzzy methods are the same as the shape of the probability density function used in the Monte Carlo simulation. The case study, concerning an LNG release, illustrates the application of the proposed techniques. (c) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:418 / 426
页数:9
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