Design Conditions for Dolphin Berth by Tanker Fleet Analysis
Bibliographic record
Abstract
Energy acquisition due to the increase of oil price is one of the most important issues and policy for most countries. Various tankers have been built in the world and sent to the trade market. It is necessary to build the port infrastructure and facilities to give them proper services such as mooring, packing, storing, and transshipment, etc. However, the domestic guidelines or standards for design and construction for the dolphin berth among these facilities are out of date and do not meet the recent trend of tanker types. Therefore, it requires amendment on the guidelines or standards. In this study, a detailed analysis of the tanker fleet, covering 8,000 ships under operation and order to build, is made to estimate the proper PBL(Parallel Body Length) of each tanker class. After discussion and comparison on the dolphin berth design and construction codes of various countries, those are the leading countries of tanker operation and management, suggestion was made to amend on the design code. The referred codes are of Korea, Japan, UK, USA, and Canada. The analysis of tanker fleet shows the PBL as 0.45L under the normal ballast condition. In order to verify the deduced amendment on the domestic design code for dolphin berth, it was selected one of the domestic dolphin berth, located at the Yeosu oil terminal, which is almost completed to construct. The design criteria and expected tankers to moor in that terminal were analyzed and the appropriateness and countermeasure for deficiency were summarized.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".