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Record W2006861269 · doi:10.1520/jai19032

Spectrum Fatigue Testing and Small-Crack Life Prediction Analysis on a Coupon Similar to a Critical Design Detail of a CF188 Hornet Component

2004· article· en· W2006861269 on OpenAlexaff
Marko Yanishevsky, RA Everett

Bibliographic record

VenueJournal of ASTM International · 2004
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsFuselageStructural engineeringFatigue testingBulkhead (partition)Materials scienceFracture mechanicsAmplitudeEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Numerous studies have shown that small-crack methodology can be used to predict the total fatigue life of laboratory type (KT = 1 and 3) specimens under variable amplitude loading. Prior to investigating how well this fatigue life prediction capability could be extended to “real” aircraft structures, an intermediary step was taken where total fatigue life was predicted for a laboratory type specimen similar to a critical design detail in a fighter aircraft fuselage bulkhead. Using the small-crack analysis in the computer code called FASTRAN and assuming an initial crack size of 20 microns, the time to catastrophic failure of the test coupons was predicted to within 10% of the average test times.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.580
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.044
GPT teacher head0.257
Teacher spread0.213 · 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 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

Citations0
Published2004
Admission routes1
Has abstractyes

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