Comparison of numerical methods for cerebrospinal fluid representation and <scp>fluid–structure</scp> interaction during transverse impact of a finite element spinal cord model
Why this work is in the frame
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Bibliographic record
Abstract
Spinal cord impacts can have devastating consequences. Computational models can investigate such impacts but require biofidelic numerical representations of the neural tissues and fluid-structure interaction with cerebrospinal fluid. Achieving this biofidelity is challenging, particularly for efficient implementation of the cerebrospinal fluid in full computational human body models. The goal of this study was to assess the biofidelity and computational efficiency of fluid-structure interaction methods representing the cerebrospinal fluid interacting with the spinal cord, dura, and pia mater using experimental pellet impact test data from bovine spinal cords. Building on an existing finite element model of the spinal cord and pia mater, an orthotropic hyperelastic constitutive model was proposed for the dura mater and fit to literature data. The dura mater and cerebrospinal fluid were integrated with the existing finite element model to assess four fluid-structure interaction methods under transverse impact: Lagrange, pressurized volume, smoothed particle hydrodynamics, and arbitrary Lagrangian-Eulerian. The Lagrange method resulted in an overly stiff mechanical response, whereas the pressurized volume method over-predicted compression of the neural tissues. Both the smoothed particle hydrodynamics and arbitrary Lagrangian-Eulerian methods were able to effectively model the impact response of the pellet on the dura mater, outflow of the cerebrospinal fluid, and compression of the spinal cord; however, the arbitrary Lagrangian-Eulerian compute time was approximately five times higher than smoothed particle hydrodynamics. Crucial to implementation in human body models, the smoothed particle hydrodynamics method provided a computationally efficient and representative approach to model spinal cord fluid-structure interaction during transverse impact.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it