A summary of the Lucy Ashton resistance prediction workshop
Bibliographic record
Abstract
• Numerical results underpredict the experimental resistance. • Scatter in the total resistance decreases as the Froude number is increased. • Spread of the total resistance is lower at full-scale than at model-scale. A blind full-scale CFD resistance prediction workshop was held in 2024, with the Lucy Ashton paddle steamer as its test case. Results from forty participants were received for the three different parts in which the workshop was organised, which consisted of a grid refinement study with common grids, full-scale simulations for varying Froude number, and model-scale simulations at a constant Froude number for varying model sizes. This paper presents a summary of the results gathered for the workshop along with its main findings, and the comparison with the results available from the experimental campaign carried out for the Lucy Ashton in the 1950s. The computational results led to lower ship resistance than the experimental data for all conditions, due to the simulations considering the ship to be hydrodynamically smooth and to not heave or pitch. The scatter of the resistance at full-scale showed a decreasing trend as the Froude number was increased with a median absolute deviation of at most 2.3 %. The spread in the numerical results obtained for the full-scale conditions was equivalent to that observed for the model-scale cases, building further confidence in full-scale CFD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".