Numerical and experimental justification of transcatheter aortic valve prosthesis design
Bibliographic record
Abstract
Objective: to justify the design of a self-expanding transcatheter aortic valve prosthesis based on a biomaterial stabilized with ethylene glycol diglycidyl ether using numerical simulation and a series of field experiments with working prototypes to determine the consistency of the proposed design solutions. Material and methods. Numerical computer models of a developed aortic valve prosthesis intended for transcatheter implantation, as well as prototypes of the most promising concepts for a series of field tests, were used in the work. Computer 3D models were subjected to numerical analysis in the Abaqus/CAE environment (Dassault Systemes, France) based on the finite element method with iterative design optimization and repeated numerical experiments. Physical prototypes of the transcatheter prosthesis were subjected to a series of mechanical tests for axial and radial compression, as well as tests on a Vivitro hydrodynamic stand (Vivitro Labs, Canada) under simulated normal flow. All studies were carried out in a comparative aspect with a similar transcatheter aortic valve prosthesis (control), the CoreValve™ bioprosthesis (Medtronic, Inc., USA). Results. Computer simulation demonstrates the stress-strain state values that do not significantly exceed the critical levels (628 and 756 MPa versus the threshold value 1080 MPa) for two basic concepts of support frames. The fatigue strength based on the calculation of the mean and alternating stresses corresponding to normo- and hypertensive states based on the Goodman diagrams, did not reveal any evidence that the threshold values (destruction area after 200 million cycles) were exceeded. The hydrodynamic characteristics of working prototypes made on the basis of computer models correspond to the testing data of CoreValve™ clinical bioprosthesis: the effective orifice area was 1.97 cm2, the mean transprosthetic gradient was 8.9 mm Hg, the regurgitant volume was 2.2–4.1 mL per cycle depending on the prototype model. Conclusion. Generally, experiments carried out showed the consistency of the concepts, including from the point of view of implementation of the leaflet apparatus based on xenogeneic tissues treated with ethylene glycol diglycidyl ether.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".