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A step forward: IEC 62097-Edition 2 - “Hydraulic Machines, Radial and Axial – Methodology for Performance Transposition from Model to Prototype”

2019· article· en· W2933841309 on OpenAlexaff
Nadine Pajean Wassong, Jacob Iosfin, Wolfgang Artner, K Tezuka

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsBC Hydro (Canada)
Fundersnot available
KeywordsScalabilityScalingComputer scienceTransposition (logic)Leakage (economics)Mechanical engineeringEngineeringMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Advances in the technology of hydraulic machines for hydroelectric power plants provided the background for updating and revising the efficiency scale effect methodology of IEC 60193. The fundamental step forward in IEC 62097 is the standardization of scalable losses in specific hydraulic energy, leakage losses and disk friction losses. The transposition of the hydraulic performance is driven by the dependence of friction losses on Reynolds number Re and the effect of surface roughness Ra. Since the roughness of the actual machine components differs from part to part, the performance scale effect is evaluated for each individual part separately and then is finally summed up to obtain the overall performance transposition for a complete machine. After the release of IEC 62097 Edition 1 in 2009, comments on this standard were received and open or unclear topics identified. As a result, the new innovative concepts were introduced and developed, and editorial changes were implemented in Edition 2. This paper presents the significant improvements implemented in the release of IEC 62097 Edition 2 related to the performance transposition methodology for hydraulic machines through: a) addressing the shift in nED and QED in the performance scaling from the model to prototype; b) identifying two-step efficiency transposition as the primary method for deriving prototype efficiency based on the model test results; c) specifying recommended roughness measurement techniques and minimum prototype roughness values; d) readjusting scalable losses and leakage losses for models with peak efficiency exceeding the assumed maximum hydraulic efficiency specified in the standard; e) improved structure of the IEC 62097 standard document and "Excel" workbook providing clear and user friendly guidelines for the performance transposition calculations. The release of Edition 2 is a clear step forward in advancing the performance transposition methodology for radial and axial hydraulic machines.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.580

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 communication0.0000.001
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 head0.019
GPT teacher head0.216
Teacher spread0.197 · 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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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