Using Bayesian Methodology to Estimate Liquefied Natural Gas Leak Frequencies

Technical Report · Thu Apr 01 04:00:00 EDT 2021

DOI:https://doi.org/10.2172/1782412· OSTI ID:1782412

Mulcahy, Garrett W. ^[1]; Brooks, Dusty Marie ^[1]; Ehrhart, Brian David ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

This analysis provides estimates on the leak frequencies of nine components found in liquefied natural gas (LNG) facilities. Data was taken from a variety of sources, with 25 different data sets included in the analysis. A hierarchical Bayesian model was used that assumes that the log leak frequency follows a normal distribution and the logarithm of the mean of this normal distribution is a linear function of the logarithm of the fractional leak area. This type of model uses uninformed prior distributions that are updated with applicable data. Separate models are fit for each component listed. Five order-of-magnitude fractional leak areas are considered, based on the flow area of the component. Three types of supporting analyses were performed: sensitivity of the model to the data set used, sensitivity of the leak frequency estimates to differences in the model structure or prior distributions, and sufficiency of sample sized used for convergence. Recommended leak frequency distributions for all component types and leak sizes are given. These leak frequency predictions can be used for quantitative risk assessments in the future.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1782412
• Report Number(s): SAND2021-4905; 695966
• Country of Publication: United States
• Language: English

Related Subjects

03 NATURAL GAS
42 ENGINEERING