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Record W2527556647 · doi:10.1017/jfm.2016.582

Effects of bileaflet mechanical heart valve orientation on fluid stresses and coronary flow

2016· article· en· W2527556647 on OpenAlexaff
Laura Haya, Stavros Tavoularis

Bibliographic record

VenueJournal of Fluid Mechanics · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceTurbulenceBlood flowBody orificeAortic valveAortaMechanicsCardiologyAnatomyMedicinePhysics

Abstract

fetched live from OpenAlex

The effects of the orientation of a bileaflet mechanical heart valve on the viscous and turbulent stresses in the flow past it and on the flow rate in the right coronary artery were investigated in vitro in a mock circulation loop, using a fluid that matched the kinematic viscosity of blood and the refractive index of the aorta model. Measurements were made past the valve mounted in three orientations at the base of an anatomical aorta model, within physiological aortic flow conditions. At peak flow, the turbulent stresses were on average 21 % higher and viscous stresses exceeding 10 Pa (namely of a level that has been associated with blood cell damage) were 30 % more frequent when the valve was oriented with its plane of symmetry normal to the aorta’s plane of curvature than when it was parallel to it. This was attributed to the impingement of a lateral jet on the concave wall of the aorta and to steeper velocity gradients resulting from the geometrical imbalance of the sinuses relative to the valve’s central jet when the valve was in the ‘normal’ orientation. Very high levels of turbulent stresses were found to occur distal to the corners of the valve’s lateral orifices. The bulk flow rate in the right coronary artery was highest when the valve was positioned with its central orifice aligned with the artery’s opening. The coronary flow rate was directly affected by the size, orientation and time evolution of the vortex in the sinus, all of which were sensitive to the valve’s orientation.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.296
Teacher spread0.288 · 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 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

Citations24
Published2016
Admission routes1
Has abstractyes

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