MétaCan
Menu
Back to cohort
Record W2987924347 · doi:10.1115/gt2019-90979

Untwist Creep Analysis of Gas Turbine First Stage Blade

2019· article· en· W2987924347 on OpenAlexaff
Anthony Jarrett, Veda V. Erukulla, Ashok K. Koul

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsLife Prediction Technologies (Canada)
Fundersnot available
KeywordsCreepTurbine bladeBlade (archaeology)Materials scienceStress (linguistics)Distortion (music)Structural engineeringFinite element methodMechanicsTurbineMechanical engineeringComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract During operation, turbine blades subjected to high temperatures will experience permanent geometric distortion due to creep. The principal form of this distortion is blade elongation due to the centrifugal load, but the blade can also straighten or ‘untwist’. The magnitude of the untwist can be used to track the accumulated creep strain damage in a blade, and so measurements of blade untwist over time are often recorded. If the relationship between untwist and creep strain damage can be expressed, then it will be possible to make more informed maintenance decisions. This study describes a finite element creep analysis of a first stage turbine blade using a calibrated creep material model, and compares the calculated untwist to records kept by the operator. The creep model used in this study is a physics based model using the microstructural properties of the blade alloy, and is calibrated using a single creep test at representative stress and temperature. An important objective of this study is to demonstrate that application of the creep model in a component with non-uniform stress and temperature will lead to representative results. The analysis was repeated with two materials that correspond to different blade versions. The material with superior high temperature properties exhibited less untwist, and the analysis of both variants were comparable to the recorded blade measurements.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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.

Study designSimulation or modeling
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

Citations5
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicHigh Temperature Alloys and CreepFrench-language works237,207