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Record W4400417476 · doi:10.2139/ssrn.6300045

Strength Optimisation of Hybrid Bolted/Bonded Composite Joints Based on Finite Element Analysis

2024· article· en· W4400417476 on OpenAlexaff
Raphael Blier, Leila Monajati, Masoud Mehrabian, Rachid Boukhili

Bibliographic record

VenueSSRN Electronic Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsPolytechnique MontréalRoyal Military College of Canada
Fundersnot available
KeywordsBolted jointMaterials scienceAdhesiveFinite element methodStructural engineeringComposite materialJoint (building)StiffnessWasherComposite numberUltimate tensile strengthLap jointComposite laminatesIsotropyStress (linguistics)Stress concentrationLayer (electronics)EngineeringFracture mechanicsMechanical engineering

Abstract

fetched live from OpenAlex

A finite element analysis (FEA) was conducted to examine the behaviour of single-lap quasi-isotropic (QI) and cross-ply (CP) hybrid bolted/bonded (HBB) configurations subjected to tensile shear loading. Several critical design factors influencing the composite joint strength, failure conditions, and load-sharing mechanisms that would optimise the joining performance were assessed. The study of the stress concentration around the holes and along the adhesive layer highlights the fact that the HBB joints benefit from significantly lower stresses compared to only bolted joints, especially for CP configurations. The simulation results confirmed the redundancy of the middle bolt in a three-bolt HBB joint. The stiffness and plastic behaviour of the adhesive were found to be important factors that define the transition of the behaviour of the joint from a bolted type, where load sharing is predominant, to a bonded joint. The load-sharing potential, known as an indicator of the joint's performance, is improved by reducing the overlap length, using a low-stiffness, high-plasticity adhesive, and using thicker laminates in the QI layup configuration. Enhancing both the ratio of the edge distance to the hole diameter and washer size proves advantageous in reducing stresses within the adhesive layer, thereby improving the joint strength.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.233
Teacher spread0.225 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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