Comparison of Cortical Bone Fracture Patterns Under Compression Loading Using Finite Element–Discrete Element Numerical Modeling Approach and Destructive Testing
Bibliographic record
Abstract
Finite element analysis may not be the only method by which bone fracture initiation and propagation may be analyzed. This study compares fracture patterns generated from compression testing of bone to fracture patterns generated using a combination of both the finite element method (FEM) and discrete element method (DEM) as defined by the finite discrete element method (FDEM). Before testing, a three-dimensional bone model was developed using CT. Force and displacement data were collected during testing. The tested specimen was reimaged using CT. The solid model was discretized and material properties adjusted such that finite element-discrete element macro behavior matched the force-displacement data. A qualitative comparison of the fracture patterns demonstrates that FDEM can successfully be used to simulate and predict fracturing in bone, with this study representing the first time this has been done and reported.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".