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Record W2942219242 · doi:10.1504/ijscom.2018.10020805

Numerical and experimental comparisons of pressed blades for large Francis turbine runners manufactured with a reconfigurable pressing setup and a conventional setup

2018· article· en· W2942219242 on OpenAlexaffabout
Zhengkun Feng, Henri Champliaud

Bibliographic record

VenueInternational Journal of Service and Computing Oriented Manufacturing · 2018
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsPressingFinite element methodHydraulic pressMechanical engineeringFrancis turbineTurbine bladeDie (integrated circuit)Range (aeronautics)Process (computing)HydropowerEngineeringTurbineDrumPower (physics)Structural engineeringComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Quebec hydraulic power plants are mainly operated with large Francis turbines due to their ability to comply with a wide range of rates of flow and falls' heights. The variation of hydraulic conditions from one site to another forced engineers to create each time a new design for the runners and consequently lead to different thicknesses, sizes and shapes for the blades. The unit production costs are inevitably high since the punch and die matrices are completely redesigned for the production of a specific batch of blades. In this paper, the authors focus on a reconfigurable setup of punch and die matrices for forming blades from very thick plates offering a flexible alternative to the conventional setup. First, in order to validate the numerical model, a finite element simulation of the pressing process with a continuous conventional punch and die pair is performed. Second, the methodology for setting up a reconfigurable punch and die pair, based on a dense distribution of spherical headed poles, is presented. The model is then inserted in the previous finite element procedure. Numerical results agree well with data collected on blades pressed for the rehabilitation of a hydropower plant in Quebec.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.535

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 head0.009
GPT teacher head0.244
Teacher spread0.236 · 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 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
Published2018
Admission routes2
Has abstractyes

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