Analysis of Liquefied Natural Gas Storage Tanks under Different Applications
Bibliographic record
Abstract
Liquefied natural gas (LNG) is increasingly used in marine propulsion and transport, with cargo tanks being a critical component affecting vessel safety and efficiency. Existing studies on conventional LNG carriers and LNG dual-fuel vessels have focused on typical independent tank types (A, B, and C), examining their structural characteristics, load-bearing mechanisms, and application scenarios. LNG carrier tanks are designed for large-volume, long-term storage with emphasis on low-temperature performance, fatigue resistance, and deformation control, whereas dual-fuel vessel tanks prioritize safety, compactness, and flexible arrangement for fuel supply. Current research combines theoretical analysis, numerical simulation, and regulatory comparison to evaluate tank mechanical responses and thermal behavior under low-temperature, pressure, and wave-induced loads[1]. Type C tanks, particularly the bi-lobe double-tank configuration, are highlighted for their excellent pressure resistance, insulation performance, and space utilization, making them the preferred choice for small- and medium-sized dual-fuel vessels. These studies provide important references for tank structural optimization, material selection, and safety assessment, while also offering methodological guidance for future integrated LNG fuel system design and lightweighting research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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".