A Method for Matching the Refractive Index and Kinematic Viscosity of a Blood Analog for Flow Visualization in Hydraulic Cardiovascular Models
Bibliographic record
Abstract
In this work, we propose a simple method to simultaneously match the refractive index and kinematic viscosity of a circulating blood analog in hydraulic models for optical flow measurement techniques (PIV, PMFV, LDA, and LIF). The method is based on the determination of the volumetric proportions and temperature at which two transparent miscible liquids should be mixed to reproduce the targeted fluid characteristics. The temperature dependence models are a linear relation for the refractive index and an Arrhenius relation for the dynamic viscosity of each liquid. Then the dynamic viscosity of the mixture is represented with a Grunberg-Nissan model of type 1. Experimental tests for acrylic and blood viscosity were found to be in very good agreement with the targeted values (measured refractive index of 1.486 and kinematic viscosity of 3.454 milli-m2/s with targeted values of 1.47 and 3.300 milli-m2/s).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".