Transport phenomena in vacuum bag only prepreg processing of honeycomb sandwich panels
Bibliographic record
Abstract
Honeycomb sandwich panels offer an extremely lightweight solution for aerospace structures. As efficiency demands increase, low-cost non-autoclave manufacturing solutions are sought for honeycomb and other composite structures. Vacuum-bag-only (VBO) manufacturing is one possible solution that relies on vacuum to remove all entrapped volatiles prior to cure, and then the differential pressure between the inside and outside of the vacuum bag consolidates the layers during cure. This technique can be very effective for monolithic laminates made with out-of-autoclave (OOA) prepregs, but honeycomb structures introduce two additional manufacturing nuisances. First, the core entraps up to 98 % of its volume during lay-up, and second, non-metallic cores readily absorb ambient moisture. Entrapped air and moisture can increase the honeycomb core pressure during processing, reducing part quality. Given that the honeycomb core pressure is crucial to achieving success in VBO manufacturing of honeycomb panels, a threefold approach was used in this thesis to study the transport phenomena that influence this behaviour. First, the transport phenomena of the constituent materials were characterized. Applying an impermeable boundary condition to the tool-side skin allowed for simple air permeability characterization of honeycomb skins by considering only the bag-side skin. An instrumented test fixture was used to measure the honeycomb core pressure during the pre-processing vacuum hold. The results revealed that a transverse interconnected pore space was required in OOA prepreg skins for gas evacuation to proceed in honeycomb panels. The same test fixture was used to characterize the honeycomb skin air permeability and honeycomb core moisture diffusivity during elevated temperature processing. The evolving skin air permeability and core diffusivity were observed to cause the honeycomb core pressure to increase during the temperature ramp and decrease during the temperature hold. Second, a process model was developed to predict honeycomb core pressure throughout the manufacturing process. The process model identified that the honeycomb core pressure can exceed the vacuum bag consolidation pressure due to the high core moisture adsorption and elevated temperature diffusivity. Choosing, or creating, a honeycomb skin with high air permeability was identified as a key process parameter to avoid exceeding the consolidation pressure. Finally, the material characterization and process modelling were successfully scaled to reproduce the honeycomb core pressure behaviour in holistic honeycomb panels. The in-situ honeycomb core pressure was measured throughout the manufacturing process in dual-skin honeycomb panels using embedded pressure sensors. The embedded pressure sensor response validated the material characterization assumptions and model simplifications used to predict the honeycomb core pressure during the VBO manufacturing process. Manufacturing honeycomb panels is a complex activity with many material and processing variables. A suitable skin material and bagging configuration was selected for VBO manufacturing of honeycomb panels by coupling transport phenomena modelling and tailored material characterization. This approach could be used to reduce manufacturing trial and error before scaling these materials to larger applications.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".