Influence of material model and modeling space on the precision of a finite element simulation to predict the deformation of silicone rubber
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
"The realistic simulation of tool-tissue interactions is required for the development of surgical simulators. In this paper, we estimate the material properties of a silicone rubber with mechanical properties similar to brain tissue, by performinga standard compression test. Using the estimated parameters, we performed different finite element simulations of needle indentation into a block of the same tissue. We investigated the effect of material model (Neo-Hookean and Second Order Reduced Polynomial) and modeling space (3D and axisymmetric geometries) on the accuracy of the simulation. We demonstrated that material model, space and their interaction have a significant effect on the accuracy of the simulations. The most accurate combination corresponds to a 3D simulation using a Reduced Polynomial model. However, even for not-axisymmetric geometries, one can sacrifice some accuracy and use a simpler and faster modeling space (i.e. axisymmetric), at least for the simulations considered here, given a change in the modeling space has a smaller effect on accuracy than a change in the material model."
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it