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Record W7034103656

Study of podded propulsors with varied bub angle and configurations

2009· article· en· W7034103656 on OpenAlexfundvenueno aff

Bibliographic record

VenueNPARC · 2009
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDynamometerThrustPropulsorTorquePropellerRange (aeronautics)
DOInot available

Abstract

fetched live from OpenAlex

This paper presents an experimental study on the effects of tapered hub on the propulsive characteristics of puller and pusher podded propulsors in straight course and static azimuthing conditions while operating in open water. The propulsive performance of two model pod units having the same pod-strut shape and propeller blade geometry with different hub shapes were measured using a custom designed pod dynamometer. The dynamometer system consisted of a six-component global dynamometer and a three-component pod dynamometer. The measurements consisted of the forces and moments of the units in the three co-ordinate directions and thrust and torque of the propellers for a range of advance coefficients from 0 to 1.2 combined with the range of static azimuthing angles from +30° to –30° in 15° increments in pusher and puller configurations. The variations in the propulsive performance due to the change in hub geometry in straight ahead conditions were examined first, followed by a study on the effects in different static azimuthing angles. Comparison of the results of the two pod units illustrated that in both pusher and puller configurations, the effect of hub taper angle is more significant at lower advance coefficients while the effects increased with increasing azimuthing angle.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.020
GPT teacher head0.269
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes2
Has abstractyes

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