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On variations in turbine runner dynamic behaviours observed within a given facility

2019· article· en· W2995037851 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

VenueIOP Conference Series Earth and Environmental Science · 2019
Typearticle
Languageen
FieldEngineering
TopicMechanical Failure Analysis and Simulation
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsTurbineReliability (semiconductor)Point (geometry)Flow (mathematics)WonderEngineeringStructural engineeringMathematicsMechanical engineeringMechanicsPhysicsGeometryPsychology

Abstract

fetched live from OpenAlex

Abstract When confronted with cracks or high stresses in turbine runners, we often wonder if the behaviour observed on one specific runner will be present on all other similar runners. In this case, we have a facility with 19 runners having the same blade geometry. In order to answer the question, we selected three runners for measurement campaigns. First, the runners were divided in groups using band length, materials and wicket gate geometries. We then examined two runners with different wicket gate geometries and were thus able to explain why one runner exhibited recurrent fatigue damage problems and not the other. However, even within a given group, significant reliability differences were found when comparing with a third runner. The observed data shows that an important turbine characteristic was overlooked. Our conclusions point toward eccentricities and imperfections in the discharge ring attributable to only the upper part of the labyrinth seal being refurbished in this facility. This may generate a significant imbalance in the force produced by the flow in the runner side chamber. The paper underscores the impact of such imbalance, which could be present in older refurbished facilities.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.477

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 head0.012
GPT teacher head0.194
Teacher spread0.182 · 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