MétaCan
Menu
Back to cohort
Record W1959766425 · doi:10.24908/pceea.v0i0.3775

DESIGN OF IN-SITU RIVER KINETIC TURBINES TEST FACILITY IN COLD WATER

2011· article· en· W1959766425 on OpenAlexaffvenueabout
Eric Bibeau, Shamez Kassam, John Woods, Ani Gole, Farid Mosallat, Philippe Vauthier, Tom Molinski

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTurbineMarine engineeringWind powerRenewable energyGridSystems engineeringEngineeringComputer scienceReliability engineeringEnvironmental scienceMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

A river kinetic turbine testing program was initiated in collaboration with Manitoba Hydro and UEK Corporation in the Winnipeg River. The goal of this program is to determine if this renewable energy technology can economically generate power in remote and grid connected areas using river currents. Compared with other forms of power generation technology, kinetic turbines may be implemented with less infrastructure. Of importance is to implement engineering design solutions as part of the testing program subject to a fixed research budget, with operational and maintenance cost still unknown. This paper presents the design of the research project to develop a one-year demonstration of a UEK 60 kW turbine to assess its ability to produce power and determine annual operational and maintenance costs in cold weather applications. A research platform concept was developed to allow adjusting the turbine location to obtain different flow and turbulence conditions and be able to pull the turbine out of the water to perform maintenance work, all at minimal cost. A low cost anchoring system was also put into service to secure the research platform. Instrumentation of the turbine was designed to obtain power, voltage, pressures, flow, turbulence, turbine loads and vibration. In addition, a remote sensing system was implemented to monitor the turbine performance and condition. Innovative approaches to design and operational logistics may make kinetic turbine technology an economically efficient solution.

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 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 score0.271
Threshold uncertainty score0.655

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 head0.011
GPT teacher head0.174
Teacher spread0.163 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicCavitation Phenomena in PumpsFrench-language works237,207