Empirical modeling of force and temperature in drilling bone-simulating hybrid composites
Bibliographic record
Abstract
Hybrid polymer composites are utilized in biomechanical design and orthopedic surgery training to imitate the thermomechanical behavior of human bones. Despite extensive research on the mechanics of hybrid composites in biomechanical design, information on their thermomechanical response during orthopedic drilling operations is scarce. This paper presents a new experimental study to characterize the force and temperature generated during the drilling of hybrid composites that simulate human bones. To simulate the hybrid multi-layer structure of bones, the studied composite comprises a Polyurethane core sandwiched between Glass-Fiber Reinforced Polymer (GFRP) layers—the former resembling the cancellous part of the bone and the latter cortical layers. This study also identifies an empirical relationship between thrust force, temperature, drilling feed and speed, and composite composition. Empirical models are developed using multivariate polynomial regression (MPR) and artificial neural network (ANN) to predict the force and temperature during drilling. The models have a correlation coefficient of above 0.9 between predicted and measured results and can be used to improve orthopedic drilling design and control.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".