A Measurement System to Monitor Propulsion Performance and Ice-Induced Shaftline Dynamic Response of Icebreakers
Bibliographic record
Abstract
Polar navigation entails challenges that affect the continuation of ship operations in severe ice conditions. Due to ice-propeller interaction, propulsion shafting segments are often at a high risk of failure. Efficient methods for shaft line design are hence needed to ensure the safety of ice-going vessels and propulsion reliability. To this end, full-scale measurements have proven essential to support the development of ship-design tools and updated safety regulations for ice-going vessels. This paper presents a unique integrated measurement system that employs measuring equipment to monitor Polar-Class vessel performance and shaft line dynamics during ice navigation. The system was installed on board the Canadian Coast Guard (CCG) icebreaker Henry Larsen. This experimental concept aims to monitor the shaft’s torque and thrust fluctuations during ice navigation to obtain information about the ship’s propulsion efficiency. In the paper, we describe the arrangement of the measurement system and the components it features. Finally, we present preliminary datasets acquired during two icebreaking expeditions. This work is framed into a broader research project, which includes the long-term objective to determine a correlation between sea ice conditions and the dynamic response of shaft lines.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".