Flooding probability in temporal risk assessment for LNG vaporizer unit established in West Coast Malaysia
In the Liquid Natural Gas (LNG) processing field, accidents can be caused by various natural occurrences. Lightning and flooding scenarios are common triggering agents for industrial accidents, and there is a chance that LNG units could sustain significant damages in such an event. This study integr...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en |
| Published: |
IDRiM Society
2025
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/123768/1/123768.pdf http://psasir.upm.edu.my/id/eprint/123768/ https://www.idrimjournal.com/article/129129-flooding-probability-in-temporal-risk-assessment-for-lng-vaporizer-unit-established-in-west-coast-malaysia |
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| Summary: | In the Liquid Natural Gas (LNG) processing field, accidents can be caused by various natural occurrences. Lightning and flooding scenarios are common triggering agents for industrial accidents, and there is a chance that LNG units could sustain significant damages in such an event. This study integrates these two natural phenomena into the temporal model and analysis. The principle of temporal failure has been applied to an LNG`s SCV (Submerged Combustion Vaporizer) unit affected by floods and lightning, which are considered correlated natural phenomena. This work proves and applies a new dimension (temporal) to risk analysis in chemical process safety engineering for the first time. As a result of the simulation, Sequential (Temporal) failures 1, 2, and 3 comprise 31.25%, 47.9%, and 13.5% of the total failures, respectively, and together make up 92.65% of the total failures, which cannot be detectable by conventional approaches. Meanwhile, classical failures contribute to only 6.8% of the total failures. For a safety-critical system, these values are crucial. Using Monte Carlo Simulation (MCS), we provide information on the occurrence of failures for the vaporizer based on operational hours. From the results, the vaporizer can be expected to fail 29 times over 300,000 service hours, with only 2 of these being conventional failures. After total failure frequency was obtained Event Tree Analysis (ETA) was performed, and negative consequence probability was found 3.25x10-6(/h). |
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