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Record W2260292170 · doi:10.1115/gt2015-42156

Dominant Damage Factors Determining for Single Crystal Nickel Superalloys Under Cyclic Loading Based on Principal Component Analysis

2015· article· en· W2260292170 on OpenAlexaff
Rongqiao Wang, Kanghe Jiang, Fulei Jing, Dianyin Hu, Jun Song

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsMcGill University
Fundersnot available
KeywordsSuperalloyPrincipal component analysisMulticollinearityMaterials scienceMesoscopic physicsSingle crystalStructural engineeringMetallurgyMathematicsEngineeringStatisticsAlloyChemistryCrystallographyPhysicsCondensed matter physics

Abstract

fetched live from OpenAlex

A critical plane approach in combination with principal component analysis (PCA) for determining dominant damage factors (DDFs) was developed for single crystal nickel superalloys at elevated temperature. Maximum resolved shear stress (RSS), maximum slip rate and other 2 mesoscopic parameters on the critical plane, defined as the preferential slip plane, were selected as damage parameters. Correlation analysis results indicated that there were strong correlations (i.e. multicollinearity) among the selected parameters. To address this issue, PCA was performed to eliminate the effect of multicollinearity and the DDFs were determined as well. Based on the DDFs a life model was proposed and then validated by the fatigue experimental results. Most of the experimental lives are within the factor three of the predicted ones. The life model has a relatively simple form with reliable constants which facilitates the application in industry design.

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 categoriesMeta-epidemiology (narrow)
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 score0.282
Threshold uncertainty score1.000

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 head0.033
GPT teacher head0.244
Teacher spread0.211 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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