Three‐dimensional simulations of non‐isothermal flow for gas penetration in complex cavity during gas assisted injection moulding process
Bibliographic record
Abstract
Abstract In this paper an R‐function is employed to construct the shape level set (LS) function for representing the complex mould cavity in a gas‐assisted injection moulding (GAIM) process. With the shape LS function, the continuity, momentum, and energy equations can be extended for solving the gas‐liquid two‐phase flows using the finite volume and immersed boundary methods. Firstly, an improved simple coupled level set and volume of fluid (S‐CLSVOF) method is proposed to track the moving interfaces of gas‐liquid interface and polymer melt front. Then the benchmark problems of the two‐ and three‐dimensional deformation tests are carried out to verify the ability of the improved S‐CLSVOF method. At last, the gas penetration processes are simulated in two different complex mould cavities. The numerical results show that the improved S‐CLSVOF method has higher accuracy than the S‐CLSVOF method, and the coupled numerical framework can successfully depict the asymmetry phenomenon of gas flow, racetracking, and fountain phenomena, which has great significance in determining processing conditions and designing mould cavities.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".