Three dimensional finite-element modeling of blood flow in elastic vessels: effects of arterial geometry and elasticity on aneurysm growth and rupture
Bibliographic record
Abstract
An intracranial aneurysm (ICA) is the localized dilated of cerebral arterial segment due to a degenerative arterial disease causing local wall weakness. Sudden ICA rupture of cerebral aneurysms is the leading cause of subarachnoid haemorrhage (SAH) which is a serious disease associated with high mortality and morbidity. In this research work, we have developed and validated a finite-element fluid-structure interaction (FSI) 2-way coupling model using COMSOL Multiphysics® software package. We applied the model to three idealized intracranial elastic arteries under the Newtonian blood flow assumption. The blood flow was characterized as a steady flow velocity at the inflow and various values of blood pressure at the outflow, while the arterial wall was modeled as a hyperelastic neo-Hookean material. The result shows the significantly weakened wall shear stress (WSS) at the aneurysm fundus and intensified WSS at the distal side of aneurysm neck. The wall deformation and WSS may play an important role in the growth and rupture of ICAs. Moreover, based on these results we postulate that lateral saccular aneurysms located on highly curved arteries are subjected to higher hemodynamic stresses and are more prone to rupture.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".