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Record W2159277446 · doi:10.1109/oceans.2008.5152068

Progress in predicting the performance of ocean gliders from at-sea measurements

2008· article· en· W2159277446 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsMemorial University of NewfoundlandNational Research Council CanadaCommunity Sector Council Newfoundland and Labrador
Fundersnot available
KeywordsGliderUnderwater gliderParametric statisticsMarine engineeringOn boardOcean observationsRange (aeronautics)Computer scienceMeteorologyEnvironmental scienceGeologyRemote sensingEngineeringAerospace engineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

With over 100 commercially-available ocean gliders being used by researchers around the world, there is strong evidence that these platforms have become the tool of choice for those who require continuous sampling of ocean properties over a range of user-controllable depths. Researchers continue to add new sensors to these vehicles usually on the external surfaces where a sensor can work in an essentially unobstructed flow condition. These added sensors change the behaviour of the glider. For the purpose of improving our predictions of the behaviour of a glider during steady-state glides and course-changing manoeuvres, it is useful to have a simple analytical hydrodynamic model which can be validated quickly using at-sea measurements during several descending and ascending glides. The purpose of this paper is twofold: (i) to show how the hydrodynamic properties which govern steady-state gliding can be extracted from measurements made with on-board sensors, and, (ii) to show how these hydrodynamic properties can be used to predict the performance of ocean gliders (e.g. glide angle, glide speed, duration of voyage etc.). We describe a three-parameter model which has proved useful in representing the behaviour of an ocean glider during straight-line descents and ascents. This parametric model has been validated with at-sea measurements during multiple glides. Estimates for these parameters can be obtained from the measurements of four quantities on-board a Slocum ElectricTM glider, namely (i) the fore-and-aft position of the pitch-control battery, (ii) the volume of seawater which is ingested or expelled by the buoyancy engine, (iii) the glider pitch angle, and, (iv) the glider depth. We describe briefly a method for obtaining estimates for three of these parameters and show some results in terms of the glider drag and lift coefficients over a wide range of operating conditions. Additional work is outlined to obtain estimates for the parameters which determine the pitching moment behaviour of this ocean glider.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.162

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.040
GPT teacher head0.213
Teacher spread0.173 · 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