Structural Response of Cargo Containment Systems in LNG Carriers under Ice Loads
Bibliographic record
Abstract
Ship-ice interaction scenarios have been investigated for possible operation routes in Arctic areas and six scenarios were selected to study the structural response of Cargo Containment Systems (CCS) in both membrane and spherical types of LNG ships. For selected ship-ice interaction scenarios, ice loads and loading areas in the hull structure were determined based on the energy theory. For membrane-type LNG carriers, CCS is made of very different materials such as plywood, foam and mastic. A local FE model including the partial hull structure with one panel of individual CCS has been developed for analysis purposes. For Moss-type LNG carriers, the tank system consists of a spherical tank and a cylindrical supporting skirt structure. A local FE model including the partial hull structure with the skirt structure has also been developed for structural analysis. One critical loading location, where the ice load is applied to cause the maximum deflection of inner hull, is determined in the side shell for investigating the deformation behavior of CCS for all selected scenarios. Linear buckling analysis was performed to investigate the stability of hull structure. Nonlinear static FE analyses were conducted to obtain stress and displacement in membrane-type CCS and skirt structure, respectively. Critical locations where the maximum stresses occur in CCS were identified in both membrane and Moss types of LNG carriers. The strength of LNG carriers under the design ice load was evaluated based on FE results and assessment criteria. Finally, structural analysis procedures have been developed for assessing the strength of cargo containment systems in ice class LNG carriers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".