An infrared thermography-based method for the evaluation of the thermal response of tooling for composites manufacturing
Bibliographic record
Abstract
The manufacture of large complex aircraft structures made of advanced composites is done by heating the parts on complex, thermally massive tools using convective heating inside autoclaves. In recent years, numerical simulation of the process has shown great value, but lack of knowledge of the convective heat transfer boundary conditions remains a major obstacle to widespread adoption. An infrared thermography method is presented, suitable for evaluating the thermal response of these processing conditions. The method is based on increasing the emissivity of a tool surface with a painted vacuum bag before thermal imaging. Accurate readings with an average temperature difference of 1.1℃ compared to thermocouple data were achieved. The benefit of the thermography method is the highly detailed surface temperature map. Three tools with very similar geometries but made of Invar, aluminum and carbon fibre composite, respectively, were tested, and results interpreted using analytical solutions for the different tooling feature and convective boundary condition combinations. Analytical simulations, which were validated by comparison to numerical models, explain well the effect of autoclave airflow, tooling material and sub-structure variation on the temperature profiles measured by this infrared thermography method.
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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 | 0.004 | 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".