The characterization of a non-Newtonian blood analog in natural- and shear-layer-induced transitional flow
Bibliographic record
Abstract
BACKGROUND: Although a blood analog of aqueous glycerol and xanthan gum was found to replicate the viscoelastic behavior of blood, measurements were restricted to laminar flow. OBJECTIVE: To expand the characterization of a non-Newtonian blood analog of aqueous glycerol and xanthan gum to transitional Reynolds numbers to quantify its behavior as a function of both natural and shear-layer-induced mechanisms. METHODS: A Newtonian analog and a shear-thinning aqueous glycerol, xanthan gum solution were circulated through an in vitro flow loop replicating both a straight and obstructed artery where transition was initiated through natural and shear-layer-induced mechanisms respectively. Steady and pulsatile pressure drop measurements for both fluids were acquired across a range of Reynolds numbers up to 7600 and Womersley numbers of 4 and 6. RESULTS: In steady and pulsatile straight flow, the non-Newtonian analog presented with reduced pressure drops and prolonged laminar flow to Reynolds numbers of 3200 and 3800 respectively. Upon blockage inclusion, non-Newtonian minor losses were comparable to Newtonian in steady flow and greater in pulsatile flow suggesting an elongation of downstream non-Newtonian recirculation. Although non-Newtonian total system pressure drops in both straight and obstructed flows were lower, the ratio of pressure drop difference between the two fluids decreased through shear-layer-induced transition. CONCLUSIONS: These findings not only demonstrated the suitability of using a xanthan gum analog to model blood flow in transitional regimes, but also presented the respective differences in analog behavior as a function of transition mechanism.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".