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Record W2118965316 · doi:10.1177/0957650911417958

Developing an empirical model for ducted tidal turbine performance using numerical simulation results

2011· article· en· W2118965316 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

VenueProceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy · 2011
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDiffuser (optics)Computational fluid dynamicsInletTurbineMechanicsMarine engineeringOverall pressure ratioComputer simulationFlow (mathematics)Flow separationEnvironmental scienceSimulationEngineeringTurbulenceMechanical engineeringPhysicsOptics

Abstract

fetched live from OpenAlex

This article studies the effects of viscous loss, flow separation, and base pressure for ducted turbine designs using computational fluid dynamics (CFD) simulations. Analytical model coefficients for inlet and diffuser efficiency and base pressure coefficient parameterize these effects and have been identified from CFD results. General trends are that the inlet efficiency is nearly unity for the simulated designs; the diffuser efficiency has a significant impact on performance and is degraded by flow separation; and that the base pressure effect can provide a significant performance enhancement. Geometric features influencing each of the aforementioned parameters are identified and a regression-based model has been developed to predict ducted turbine performance.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.410

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 head0.053
GPT teacher head0.266
Teacher spread0.213 · 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