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Record W2912060886 · doi:10.14311/app.2018.20.0034

THE EFFECT OF NOTCHES ON THE FATIGUE LIFE OF A NICKEL-BASE GAS TURBINE DISK MATERIAL

2018· article· en· W2912060886 on OpenAlexaff
Robert Eriksson, Johan Moverare, Zhe Chen, Kjell Simonsson

Bibliographic record

VenueActa Polytechnica CTU Proceedings · 2018
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsEngineering Link (Canada)
FundersEuropean Commission
KeywordsGas turbinesMaterials scienceStructural engineeringTension (geology)Low-cycle fatigueFatigue testingStress (linguistics)TurbineStress concentrationComposite materialEngineeringMechanical engineeringFracture mechanicsUltimate tensile strength

Abstract

fetched live from OpenAlex

Gas turbine disks carry significant load under high temperatures and may be subject to fatigue failure. Disks contain several notches in the form of the fir tree blade attachments. Low cycle fatigue tests were performed on blunt notch compact tension specimens made from alloy 718. The results indicated that notch support needed to be incorporated not to cause an overly conservative life prediction. The notch support diminished as the plastic strain range decreased, indicating that notch support is only present in the low cycle fatigue regime. A critical distance approach was applied to account for the notch support. An equation relating the critical distance to the notch root stress was derived. The chosen life model was formulated in terms of a variation on the Smith–Watson–Topper (SWT) parameter. The modified SWT parameter taken at the critical distance was used in a life model calibrated for smooth specimens to successfully predict the fatigue life of notched specimens.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2018
Admission routes1
Has abstractyes

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Same venueActa Polytechnica CTU ProceedingsSame topicFatigue and fracture mechanicsFrench-language works237,207