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Record W2625919730 · doi:10.4050/f-0071-2015-10123

Shear Load Transfer for Corrosion Coated Clamped Joints

2015· article· en· W2625919730 on OpenAlexaff
M. McGlaun, Ryan Ehinger, Eric Sinusas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsBell Helicopter Textron (Canada)
Fundersnot available
KeywordsMaterials scienceCorrosionShear (geology)Structural engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

Rotorcraft transmission housings contain multiple joints that are typically held together by threaded fasteners. For many of these installations, the material surfaces are now coated with corrosion inhibitors that can change the strength of the joint. To identify these changes, Bell Helicopter has conducted coupon testing of coated materials in shear. Historically, the faying surfaces have been left bare with the perception that coatings would degrade the ability to transfer shear loads. Fastener and joint design has been based on assumed joint slip coefficients. A test effort to identify the shear load transfer characteristics of a clamped joint was undertaken. A double shear coupon test was used to measure the shear load capability of the clamped joint with bare material surfaces as well as with corrosion protection coated surfaces. Tests were run with calibrated bolt preloads to reduce variability. To simulate the gearbox temperature environment, the test coupons and mechanical grips were placed in an oven to maintain a temperature of 180°F. Testing showed that the addition of coating reduced the joint slip coefficient when compared to baseline bare materials.

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)0.001
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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