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Record W2052241347 · doi:10.2514/1.30895

Bending of Bonded Composite Repairs for Aluminum Aircraft Structures: A Design Study

2007· article· en· W2052241347 on OpenAlexaff
R.J. Clark, D.P. Romilly

Bibliographic record

VenueJournal of Aircraft · 2007
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFinite element methodStructural engineeringBendingComposite numberMaterials scienceDamage toleranceBucklingFastenerEpoxyComposite materialEngineering

Abstract

fetched live from OpenAlex

This paper describes an experimental and finite element study of a bonded composite repair applied to a metallic aircraft structure. The experimental study involves the fatigue testing and fractographic examination of 2024-T3 aluminum plates repaired with boron/epoxy composite patches. The two plates are tested simultaneously in a sandwich panel configuration with and without an aluminum honeycomb spacer to provide bending restraint The specimen was heavily instrumented, with strains being measured on the surface of the patch at many locations, thus allowing the validation of a three-dimensional finite element model and an assessment of the effects of geometrically nonlinear bending, buckling, and crack closure on the mechanical response and strength of the repair. The experimental and finite element results illustrate the important influence of bending and composite failure modes on the life and strength of the repair. The authors use the experimental results and the validated finite element analysis to evaluate the effectiveness of the methods and data currently available in the open literature for damage-tolerance substantiation, and then, by applying probabilistic methods and the principle of compounded conservatism to the findings, propose a new process for classifying bonded repairs and assigning requirements for testing and inspections.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.525
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.265
Teacher spread0.243 · 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 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

Citations16
Published2007
Admission routes1
Has abstractyes

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