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Record W2048174561 · doi:10.1080/10255840802010454

Repeated unit cell (RUC) approach for pure bending analysis of coronary stents

2008· article· en· W2048174561 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComputer Methods in Biomechanics & Biomedical Engineering · 2008
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsBendingBending stiffnessCurvatureBending momentMaterials scienceFinite element methodStentStiffnessStructural engineeringFlexibility (engineering)Pure bendingComposite materialGeometryMathematicsMedicineSurgeryEngineering

Abstract

fetched live from OpenAlex

Flexibility is one of the key properties of coronary stents. The objective of this paper is to characterize the bending behaviour of stents through finite element analysis with repeated unit cell (RUC) models. General periodic boundary conditions for the RUC under the pure bending condition are formulated. It is found that the proposed RUC approach can provide accurate numerical results of bending behaviour of stents with much less computational costs. Bending stiffness, post-yield bending behaviour and the relationship between moment and bending curvature are investigated for Palmaz-Schatz stents and stents with the V- and S-shaped links. It is found that the effect of link geometry on the bending behaviour of stent is significant. The behaviour of stents subjected to cyclic bending is also investigated.

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.

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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.951
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
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 head0.056
GPT teacher head0.348
Teacher spread0.293 · 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