Designing Navy Hull Forms for Fuel Economy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT During initial hull form design, a multitude of requirements need to be met. Among these are mission, ship size, armament, communications, stability, speed, sea keeping, etc. Tools such as ASSET are used to arrive at a design solution that will satisfy all these requirements. However, at this early design stage, attention needs to be given to the hull form shape, and its impact upon fuel consumption. Rising fuel costs and the need to conserve energy have mandated that Navy designs become more “energy efficient.” This paper documents a new design metric “C PE ” for evaluating the resistance of any hull design. A C PE database is developed from historic model test data residing in the U.S. Navy Hull Design Database System (HDDS). C PE compares the resistance of a hull form to that of a similar Taylor Standard Series hull form. The paper also introduces a new hull form optimization computer program developed by Naval Surface Warfare Center (NSWC) and applies this program to show the potential for hull form improvement and fuel cost savings.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it