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Record W2137726208 · doi:10.1088/0964-1726/14/5/035

A novel smart adhesively bonded joint system

2005· article· en· W2137726208 on OpenAlexaff
Jinquan Cheng, Farid Taheri‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

Bibliographic record

VenueSmart Materials and Structures · 2005
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsDalhousie University
Fundersnot available
KeywordsJoint (building)Structural engineeringMaterials scienceComposite materialSmart materialEngineeringComputer scienceForensic engineering

Abstract

fetched live from OpenAlex

A new smart adhesive joint system was developed by integrating (surface bonding) electromechanical piezoelectric patches. The bending moments in this joint system could be adaptively controlled by adjusting the electric field applied to the surface bonded piezoelectric patches. As a result, the stress distribution in the adhesive layer is more uniformly redistributed, thus reducing the stress concentration in the ends of the interface bond line. A detailed theoretical model was developed for the analysis of a single-strap adhesive joint system to study the influence of the surface bonding of piezoelectric patches and the distribution of the stress in the adhesive layer. The integrity of the proposed solution was verified by analyzing the joint with a finite element method. The comparison of the results demonstrated the viability of the proposed smart joint system, as well as validating the accuracy of our proposed solution.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.011
GPT teacher head0.191
Teacher spread0.180 · 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

Citations19
Published2005
Admission routes1
Has abstractyes

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