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Record W2021446930 · doi:10.1088/1755-1315/12/1/012050

New parameters influencing hydraulic runner lifetime

2010· article· en· W2021446930 on OpenAlexaffabout
Michel Sabourin, Denis Thibault, David-Alexandre Bouffard, Martin Lévesque

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2010
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsHydro-QuébecPolytechnique MontréalAlstom (Canada)
Fundersnot available
KeywordsReliability (semiconductor)Fracture (geology)Residual stressFracture mechanicsFatigue testingHydraulic fracturingResidual strengthStructural engineeringMaterials scienceMechanical engineeringForensic engineeringEngineeringMetallurgyGeotechnical engineeringComposite material

Abstract

fetched live from OpenAlex

Traditionally, hydraulic runner mechanical design is based on calculation of static stresses. Today, validation of hydraulic runner design in terms of reliability requires taking into account the fatigue effect of dynamics loads. A damage tolerant approach based on fracture mechanics is the method chosen by Alstom and Hydro-Québec to study fatigue damage in runners. This requires a careful examination of all factors influencing material fatigue behavior. Such material behavior depends mainly on the chemical composition, microstructure and thermal history of the component, and on the resulting residual stresses. Measurement of fracture mechanics properties of various steels have demonstrated that runner lifetime can be significantly altered by differences in the manufacturing process, although remaining in accordance with agreed practices and standards such as ASTM. Carbon content and heat treatment are suspected to influence fatigue lifetime. This will have to be investigated by continuing the current research.

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 score0.070
Threshold uncertainty score0.557

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 head0.007
GPT teacher head0.176
Teacher spread0.169 · 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

Citations14
Published2010
Admission routes2
Has abstractyes

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