Study of Pulsatile Flow in Common Carotid Artery with Different Stenosis' Shapes within Various Wall Conditions
Bibliographic record
Abstract
Recently, due to the development of CFD techniques, many attempts have been made to simulate the initiation and progression of atherosclerosis. In recent works, various curves have been suggested to model the stenosis shape. However, little effort has been made to study the importance of the stenosis shape on the flow behavior. In this study, four types of stenosis with asteroid, Gaussian, semi-circle, and sinusoidal shapes were simulated in order to study the effect of the stenosis shape on flow behavior and diagnosis parameters. Shear stress and flow behavior were investigated in the common carotid artery with stenosis severities of 30%, 40%, and 50%. Flow was assumed to be unsteady and the inlet to be a pulsatile flow. Two cases of Newtonian and non-Newtonian fluids were simulated. The no-slip and permeable boundary conditions were imposed on the outer walls. To examine the effect of the location of stenosis, modeling was conducted at various locations. The results showed that the maximum shear stress occurs in the Gaussian stenosis at the opening of the stenosis. Semi-circle, sinus, and asteroid shapes had the next largest shear stress values. Additionally, the location of stenosis had a negligible effect on the maximum shear stress. However, flow resistance increased with increasing the stenosis’s distance from the beginning of the artery. This study indicates that stenosis shape highly affects the flow characteristics, and stenosis severity is not the only parameter that is important. Hence, the stenosis shape should be considered when simulating atherosclerosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".