A comparative bibliometric study of the transport risk considerations of liquefied natural gas and liquefied petroleum gas
Bibliographic record
Abstract
Abstract Prevailing safety guidance for the transportation of liquefied natural gas (LNG) is based on the guidance for liquefied petroleum gas (LPG) transportation; therefore, the safety considerations for LNG and LPG transport must be compared. A literature review was performed to understand and compare the development of research into LNG and LPG, their transportation, and the safety considerations involved. The literature review revealed key hazard differences, as well as the lack of transport safety studies compared to the vast field of research for both substances. With the scientific background established, the chemical and physical properties of LNG and LPG are compared, then the hazards related to their properties. Finally, with knowledge of the properties and hazards of both LNG and LPG, the available risk analyses are discussed. LNG transport has undergone minimal accident frequency analysis compared to LPG transport. Most of these frequency analyses have been for marine transport and contain high uncertainties in the determined probabilities due to sparse available data. It is also apparent that consequence analysis studies have not been adequately explored; however, modelling software provides consequence understanding via simulation. LNG transportation lacks the knowledge base from research and practice that LPG transportation has, and due to limited incident history, the lack of research into boiling liquid expanding vapour explosion (BLEVE) potential of LNG and the lack of understanding of the severity, likelihood, and repeated explosions of rapid phase transition limit understanding of the risk of LNG transportation. Potential future research is recommended to address these vital knowledge gaps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".