Uncertainty analysis of NSERC-NRC pod dynamometer system
Bibliographic record
Abstract
The report presents a detailed uncertainty analysis for a podded propulsor open water test. A brief overview of the uncertainty analysis methodology has been provided, with a particular focus on the elements that are unique to the experiments with podded propulsors. The method used follows that of the American National Standards Institute (ANSI) and American Society of Mechanical Engineers (ASME) standard on Measurement uncertainty and the approach described by Coleman and steele in their 1999 book Experimental and Uncertainty Analysis for Engineers. The variables of interest in the podded propulsors uncertainty analysis were propeller thrust, unit thrust, propeller torque, forces and moments on the propulsor in the three orthogonal directions, propeller shaft rotational speed, carriage advance speed, azimuthing angle, water density (function of water temperature) and propeller diameter. The uncertainty analysis results of the experiments conducted using the NSERC-NRC dynamometer system were compared to that of a very high quality, well-established equipment (tests done in the IOT towing tank) used to measure the performance of some bare podded propellers and the results from the previous similar tests using the same equipment. Comparison of the results showed that the podded propulsor tests using the NSERC-NRC pod instrumentation in the current phase of tests provided the level of accuracy comparable with the established equipment. The uncertainty levels observed in the propeller thrust and unit thrust in the podded propulsor tests were found to be higher than the thrust uncertainty for the baseline tests, but less than the corresponding uncertainties found in the previous tests done on the same podded propulsors with same operating conditions with the same equipment. For majority of the cases, the primary element of the uncertainty of the performance coefficients was the bias error (90% or more on the total uncertainty). To reduce the overall uncertainty in the final results, the primary focuses should be to reduce the bias error in the equipment. The uncertainty analysis results provided strong evidence that the experimental data obtained using the NSERC-NRC dynamometer system presented the true performance characteristics of the model scale podded propulsors under consideration.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".