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Record W2916786181 · doi:10.1139/tcsme-2018-0042

Modeling and analysis of a bolted joint under tension and shear loads

2019· article· en· W2916786181 on OpenAlexaffvenue
Mohamed Tahar Nasraoui, Jamel Chakhari, Boubaker Khalfi, Mustapha Nasri

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsStructural engineeringFinite element methodShear (geology)Bolted jointStiffnessStiffness matrixJoint (building)Connection (principal bundle)Direct stiffness methodMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

In this paper, a prismatic bolted joint subjected to tensile and shear loads is studied. The two applied forces are in the same symmetry plane of the connection. A simplified numerical model is developed, which is constructed from unidirectional finite elements and contact elements. The elastic contact layer of connected parts is represented by a succession of springs. An algorithm computing both the free structure stiffness matrix and the contact stiffness matrix is developed. Due to the shear load, static or kinetic friction can occur at contact surfaces between assembled parts. In each iteration, tangential contact forces are calculated and taken into account in problem solving. A program in C language is developed and used to calculate the model unknowns. Three-dimensional finite element simulations are performed using ANSYS software to verify results obtained by the developed model. The model results are also compared with experimental test data.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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 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

Citations5
Published2019
Admission routes2
Has abstractyes

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Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicEngineering Structural Analysis MethodsFrench-language works237,207