Correlation of Gaseous Mass Leak Rates Through Micro- and Nanoporous Gaskets
Bibliographic record
Abstract
The present work deals with the theoretical and experimental studies of gaseous flow through tight gaskets. The paper presents an innovative approach to accurately predict and correlate leak rates of several gases through nanoporous gaskets. The new approach is based on the calculation of the gasket porosity parameters (D and N) using a model based on a first order slip flow regime. The model assumes the flow to be continuum but employs a slip boundary condition on the leak path wall. Experimental measured gas flow rates were performed on gaskets with a microscopic flow rate range and isothermal steady conditions. The flow rate is accurately measured using multigas mass spectrometers. The gasket porosity parameters used in the developed leakage rate formula were experimentally obtained for a reference gas (helium) for each stress level. In the presence of the statistical properties of a porous gasket, the leak rates for different gases can be predicted with reasonable accuracy. It was found that the approach that considers the slip flow with the first order combined to the molecular flow covers the prediction of flow rates at the microscopy level and down to 10−8 mg/s very well. Tightness hardening is the result of the saturation of the gasket combined porosity parameters or the equivalent thickness of the void layer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".