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Record W2474896588 · doi:10.1115/1.4033934

Effect of Reverse Yielding on the Residual Contact Pressure in Tube-to-Tubesheet Joints

2016· article· en· W2474896588 on OpenAlexaff
Abdel‐Hakim Bouzid, Mehdi Kazeminia

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
Keywordsvon Mises yield criterionTube (container)Materials scienceMechanicsStructural engineeringFinite element methodResidual stressExpansion jointHardening (computing)Joint (building)Strain hardening exponentContact mechanicsComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

The analytical prediction of the contact stress in tube-to-tubesheet joints subjected to hydraulic expansion is conducted without any consideration to reverse yielding that can occur inside the tube. Most existing models consider the tube and tubesheet to unload elastically when the expansion pressure is released. These models are therefore less conservative as they overestimate the contact pressure. An analytical model that considers strain-hardening material behavior of the tube and tubesheet and accounts for reverse yielding has been developed. The model is based on Henckey deformation theory and the Von Mises yield criteria. The paper shows that reverse yielding that is present in tubes during hydraulic expansion unloading makes the joint less rigid and causes a decrease in the contact pressure depending on the gap clearance and the materials used. A good correlation between the analytical and finite elements results is obtained on different treated cases which gives confidence on the developed model.

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)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.230
Teacher spread0.222 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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