A Preliminary Biomechanical Assessment of a Polymer Composite Hip Implant Using an Infrared Thermography Technique Validated by Strain Gage Measurements
Bibliographic record
Abstract
With the resurgence of composite materials in orthopaedic applications, a rigorous assessment of stress is needed to predict any failure of bone-implant systems. For current biomechanics research, strain gage measurements are employed to experimentally validate finite element models, which then characterize stress in the bone and implant. Our preliminary study experimentally validates a relatively new nondestructive testing technique for orthopaedic implants. Lock-in infrared (IR) thermography validated with strain gage measurements was used to investigate the stress and strain patterns in a novel composite hip implant made of carbon fiber reinforced polyamide 12 (CF/PA12). The hip implant was instrumented with strain gages and mechanically tested using average axial cyclic forces of 840 N, 1500 N, and 2100 N with the implant at an adduction angle of 15 deg to simulate the single-legged stance phase of walking gait. Three-dimensional surface stress maps were also obtained using an IR thermography camera. Results showed almost perfect agreement of IR thermography versus strain gage data with a Pearson correlation of R(2) = 0.96 and a slope = 1.01 for the line of best fit. IR thermography detected hip implant peak stresses on the inferior-medial side just distal to the neck region of 31.14 MPa (at 840 N), 72.16 MPa (at 1500 N), and 119.86 MPa (at 2100 N). There was strong correlation between IR thermography-measured stresses and force application level at key locations on the implant along the medial (R(2) = 0.99) and lateral (R(2) = 0.83 to 0.99) surface, as well as at the peak stress point (R(2) = 0.81 to 0.97). This is the first study to experimentally validate and demonstrate the use of lock-in IR thermography to obtain three-dimensional stress fields of an orthopaedic device manufactured from a composite material.
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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 | 0.001 | 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 | 0.000 |
| 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".