Predicting Liquefied Natural Gas (LNG) rollovers using Computational Fluid Dynamics
- Submitting institution
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Kingston University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12-024-1580
- Type
- D - Journal article
- DOI
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10.1016/j.jlp.2019.103922
- Title of journal
- Journal of Loss Prevention in the Process Industries
- Article number
- -
- First page
- 0
- Volume
- 62
- Issue
- -
- ISSN
- 0950-4230
- Open access status
- Access exception
- Month of publication
- -
- Year of publication
- 2019
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The subject area of this research encompasses fluid mechanics and computational methods. The topic of the study is to advance the understanding and computational methods to predict rollovers in liquefied natural gas (LNG) storage tanks. Such rollovers can lead to explosion and fires. This work is significant because, unlike existing approaches, it proposes an advanced computational fluid dynamics method which revealed new insights to explain the rollover phenomenon and can predict with good accuracy the onset time of rollover in tanks for risk assessment. The work attracted interest from National Grid (UK) and Engie (France), both involved in LNG safety.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -