Evaluation and impact of the degree of impregnation of uncured out-of-autoclave prepreg
Bibliographic record
Abstract
Out-of-autoclave prepreg contains partially impregnated fibre tows which act as paths for gas evacuation. The degree of impregnation of resin into the dry fibre bed is a quantitative measure of the size of these dry fibre pathways and can affect part quality and rejection rates. There is no well-defined and accurate standard method to measure this quantity. The current state-of-the-art is to manufacture discriminator panels, which are panels containing complex features such as tight radius corners, internal ply drop-offs, sandwich regions, etc. to determine the producability of specific components by specific material. That is, it is an empirical method used to determine if the initial properties of the prepreg fall within certain boundaries. This technique is time consuming and does not necessarily account for variations within specific rolls of material. The aim of this thesis is twofold: examine different techniques to measure the degree of impregnation of out-of-autoclave prepreg and perform an experimental investigation into the impact of degree of impregnation on the breathability of the material.Firstly, different methods to quantitatively measure the degree of impregnation of out-of-autoclave prepreg are examined. Three methods are compared: X-ray computed tomography, the water uptake test, and active infrared thermography. The first method serves as a baseline for accuracy but is expensive both in terms of cost and time. The second method is characterized by its simplicity but is destructive and only gives local information over a small sample area. The latter method shows promise as a quick, non-destructive evaluation technique. A further investigation into active infrared thermography highlights some limitations of the technique with regards to its implementations in an industrial setting.Secondly, the impact of degree of impregnation on the gas transport phenomena in composite materials is evaluated by manufacturing single skin sandwich panels in an instrumented fixture with a simple design of experiments. Under room temperature conditions, as the degree of impregnation increases, the material's ability to transport gas is reduced, resulting in higher core pressure. However, at elevated temperatures, this impact is lessened and final laminate quality in all panels manufactured is similar.Both material and process variability is inherent in composite materials. Currently, it is important to use robust material systems and process cycles; however, through the use of non-destructive material inspection it would be possible to measure this variability and mitigate any problems caused by it through process modification or material rejection.
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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 | 0.002 |
| 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".