Heated tool processing of out-of- autoclave composite materials
Bibliographic record
Abstract
As aerospace manufacturers continue to incorporate Out-of-Autoclave (OoA) materials into their aircraft designs, the shortcomings of the convection oven become more and more apparent.Similar to the autoclave, the traditional oven for OoA processing relies on convective heat transfer, which induces thermal lag and limits heating rates, thereby increasing cycle times.This research investigates the manufacturing of OoA composites using heated tooling where the mould surface itself is heated via conduction, resulting in improved thermal control.The heating system studied here is the TCX™ heating element, produced by ThermoCeramix inc.Two prototype systems were developed, and used to benchmark both laminate quality and energy consumption, as well as to explore alternate material forms and part structures to expand the tools' processing flexibility.Quality benchmarking studies showed that TCX™ heated tools are capable of producing laminates of similar quality to a traditional oven cure in terms of void content, short-beam strength, and glass transition temperature.The tools' rapid heating capability was also explored, and was shown to have to no negative effect on part quality at heating rates up to 50 °C/min.Energy trials demonstrated the potential for 26.1 to 91.6 percent savings, depending on the way the heating technology is implemented.This led to several tool design recommendations to optimize the energy savings of future tools, specifically by avoiding excessive use of high thermal mass substructures, and making every effort to thermally isolate the tool surface from the rest of the mould.The processing flexibility experiments demonstrated that heated tools are not limited to flat, monolithic parts.First, resin film infusion (RFI) was investigated as a possible low-cost, short cycle time application.Heated tools were shown to produce good quality laminates in all configurations but one.This led to the recommendation that heated tool RFI trials make use of a tool-side resin strategy where possible, and a short room temperature vacuum hold prior to infusion when using both rapid heating and an interspaced strategy.Next, both tapered laminates and sandwich structures featuring lightweight materials were investigated.The TCX™ prototypes were found to be able to handle both configurations by implementing multiple heating zones, and a hybrid heating blanket system.throughout my time at McGill.His advice and mentorship were not only instrumental to my Master's project, but to also to my growth as an engineer.My time in the Structures and Composite Materials Laboratory has been amazing, and I believe that is mainly due to the spirit of learning and friendship instilled in the group by Professor Hubert as well as Professor Larry Lessard.I would also like to acknowledge Professor Lessard for giving me my start in the composites lab as an undergraduate all those years ago.Within the Structures and Composite Materials Laboratory, I'd like to thank everyone who has called MD53A home for the last two years.I've truly appreciated the wonderful environment, and it made my graduate studies a period of my life that I'll never forget.Every member had an impact on my work, be it through lending a hand in the lab or helping to brainstorm ideas, and for that I'll always be grateful.Special thanks go to Adam Smith (for continued support on this project), Olivia Houston (helping with ramp rate trials), and to both Benoit Landry and Mathieu Préau (abstract translation).This research was made possible thanks to a number of partners.I would like to acknowledge the financial support of the FQRNT
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".