Experimental Investigation of Pulsatile Flow Through Prosthetic Heart Valves
Bibliographic record
Abstract
Qualitative and quantitative flow visualization study was conducted for the case of a biomimetic pulsatile flow through an artificial heart valve placed into an asymmetric model of an aortic root with sinuses of Valsalva. A prototype trileaflet valve was tested alongside with a tilted disk valve and a bileaflet valve. The study was conducted in test conditions corresponding to 70 beats/min, 5.5 l/min target cardiac output and a mean aortic pressure of 100 mmHg. Flow visualization data obtained using digital particle image velocimetry (PIV) was phase-averaged in order to provide accurate, time-resolved patterns of flow velocity and viscous shear stress values. In the case of the tri-leaflet valve, during systole, a stable jet emanates from the valve, with vortical structures forming on the sides of the jet. These vortical structures entrain the surrounding fluid into the jet, which leads to development of a shear flow instability downstream of the valve. For all considered valve types, a recirculating flow was observed in the sinus area during both the systole and the diastole. No indication of a stagnating flow region was observed, as the fluid was completely washed out from the aortic sinus within each cardiac cycle.
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 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".