Finite Element Modeling of Fuel Emission for Thermoplastic Multilayer Fuel Tanks with Optimization of Barrier Properties
Bibliographic record
Abstract
A numerical simulation model for the prediction of fuel hydrocarbon permeation is presented in this work. The barrier layer thickness optimization for thermoplastic multilayer fuel tanks is also considered. The diffusion model is based on the continuum approach with steady-state permeation regime across the multilayer polymeric wall. The hydrocarbon flux through the multilayer wall is determined by assuming continuity in vapor pressure at the polymer-polymer interface. Since the pinch-off zone is known to be the major source of emission per unit area, a method has been developed to automatically detect this zone at the end of extrusion blow molding process. After then, an improvement to the diffusion model has been proposed in order to evaluate adequately the hydrocarbon permeation through this specific area. Finally, a gradient-based algorithm is applied to optimize the barrier layer thickness to satisfy the total hydrocarbon fuel emission constraint for a plastic fuel tank (PFT).
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".