Automated Assessment of Ultimate Hull Girder Strength
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
An automated approach to ultimate hull girder strength assessment using DRDC’s ultimate strength analysis suite (ULTSAS) is described. The analysis suite improves the ability to perform rapid ultimate strength assessments by providing access to UK and Canadian analysis codes and databases under a single user interface. The interface also allows for automatic cross-sectional model generation from three-dimensional ship finite element models with the MGDSA program. The main features of the ULTSAS system are described, including cross-sectional modelling, and the use of load-shortening curve databases. The paper also provides a review of the progressive collapse method for determining ultimate strength, which is now used in both the UK and Canadian analysis codes. Two numerical approaches are described, one based on curvature incrementing and the other on moment incrementing. It is shown that the moment incrementing procedure produces more accurate bi-axial interaction curves in some instances. Results are obtained for two damage configurations of the HALIFAX class frigate.
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) | 0.000 | 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 it