Contribution to modeling of fuel permeation and barrier layer optimization in multilayer automotive plastic fuel tanks using BlowView software
Bibliographic record
Abstract
The use of plastic fuel tanks (PFT) continues to grow in the automotive industry. One of the few drawbacks of PFTs, compared to steel or aluminum fuel tanks, is that a fuel fraction may permeate through the polymer material and cause hydrocarbon emissions. For environmental reasons the emissions have to be kept to a minimum to avoid smog and green house effects. Because of this, the government has regulated acceptable levels of evaporative fuel emissions for automotive PFT through the sealed housing evaporative determination (SHED) test. One of the methods used by the automotive industry to conform to SHED requirements is by adding thin layers of a low permeability material such as Ethylene-vinyl alcohol (EVOH). These co-extruded multilayer blow molded fuel tanks are now commonly used. In general, the inner and outer layers of PFTs are made of virgin high-density polyethylene (HDPE), whereas the core of the sheet is made of HDPE regrind. To ensure good hydrocarbon barrier properties, the EVOH layer must be positioned in the core of the structure and cross-linked to the inner HDPE and regrind layer with adhesive tie layers of linear low-density polyethylene (LLDPE), to ensure the required adhesion between EVOH and HDPE. With this material layer configuration, the low permeability criterion is achieved over most of the fuel tank surface. However, it is still common practice in the thermoplastic forming industry to rely on trial and error to find the right configuration/thickness of the barrier layer required to meet the SHED test. A tool that offers more efficient alternatives based on reliable predictive/virtual analysis of the fuel diffusion throughout multilayer blow molded parts could significantly shorten the design/development cycle by allowing the product prototypes to be analyzed and tested virtually. In this regard, NRC’s BlowView numerical model for predicting the fuel hydrocarbon permeation, as well as the optimized barrier layer thickness for multilayer PFT will be presented and discussed. The diffusion model is based on Fick’s laws of diffusion through a multilayer polymeric wall. The hydrocarbon flux determination through the multilayer film is solved using homogenization techniques that ensure continuity of partial pressure at the polymer-polymer inter-diffusion interface. The problem for automotive PFTs is the pinch-off zone where EVOH layers (or other barrier materials) are highly compressed and can ultimately vanish. Therefore, adequate prediction of fuel permeation in this specific area is of utmost importance. The pinch off zone is automatically detected at the end of the extrusion blow molding process and a modified diffusion model is applied that evaluates adequately the fuel permeation through this specific area. Finally a gradient-based algorithm has been implemented to get the minimum weight and the optimal barrier layer thickness which satisfies the total hydrocarbon fuel emission constraint. The numerical validation in terms of hydrocarbon flux calculation under steady and non-steady state is performed on academic case studies by comparing numerical predictions to the analytical ones. The illustration of the methodology and the gain in terms of weight and fuel permeation, during optimization iterations, will be presented for a PFT case study.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".