Flexible injection : a novel LCM technology for low cost manufacturing of high performance composites. Part II : Numerical model
Why this work is in the frame
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Bibliographic record
Abstract
SUMMARY: A novel technology based on Liquid Composite Molding was developed for low cost manufacturing of high-performance composites. The description of this new approach called flexible injection has shown that two main flows occur during the fabrication process: Stokes flow in the compaction chamber or upper cavity and Darcy’s flow such as in resin infusion through the fibrous reinforcement contained in the lower cavity [1]. The algorithm to model this new process is based on the solution of these two flows that are coupled through the deformation of the membrane separating the upper and lower chambers [2]. Unlike in classical Resin Transfer Molding (RTM), which is basically governed only by the injection pressure or flow rate, flexible injection allows setting optimum values to several process parameters: the injection pressure such as in RTM, the vacuum pressure such as in Vacuum Assisted Resin Infusion (VARI), the compaction pressure, the thickness of the two chambers and the viscosity of the compaction fluid. This large number of control parameters gives a wider processing window, but it makes also more complex the understanding and control of the fabrication process. Numerical simulation is expected here to assist in finding the best ranges of process parameters so as to decrease fill times and improve part quality.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it