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Record W2079494492 · doi:10.1115/1.4027330

Numerical Investigation of Fluid Flow in a Chandler Loop

2014· article· en· W2079494492 on OpenAlexaff
Hisham Touma, Iskender Sahin, Tidimogo Gaamangwe, Maud Gorbet, Sean D. Peterson

Bibliographic record

VenueJournal of Biomechanical Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLaminar flowMechanicsStrain rateNewtonian fluidCurvatureVolumetric flow ratePhysicsRotation (mathematics)Classical mechanicsGeometryMathematicsThermodynamics

Abstract

fetched live from OpenAlex

The Chandler loop is an artificial circulatory platform for in vitro hemodynamic experiments. In most experiments, the working fluid is subjected to a strain rate field via rotation of the Chandler loop, which, in turn, induces biochemical responses of the suspended cells. For low rotation rates, the strain rate field can be approximated using laminar flow in a straight tube. However, as the rotation rate increases, the effect of the tube curvature causes significant deviation from the laminar straight tube approximation. In this manuscript, we investigate the flow and associated strain rate field of an incompressible Newtonian fluid in a Chandler loop as a function of the governing nondimensional parameters. Analytical estimates of the strain rate from a perturbation solution for pressure driven steady flow in a curved tube suggest that the strain rate should increase with Dean number, which is proportional to the tangential velocity of the rotating tube, and the radius to radius of curvature ratio of the loop. Parametrically varying the rotation rate, tube geometry, and fill ratio of the loop show that strain rate can actually decrease with Dean number. We show that this is due to the nonlinear relationship between the tube rotation rate and height difference between the two menisci in the rotating tube, which provides the driving pressure gradient. An alternative Dean number is presented to naturally incorporate the fill ratio and collapse the numerical data. Using this modified Dean number, we propose an empirical formula for predicting the average fluid strain rate magnitude that is valid over a much wider parameter range than the more restrictive straight tube-based prediction.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.006
GPT teacher head0.182
Teacher spread0.175 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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