Evaluation of Interfacial and Permeation Leaks in Gaskets and Compression Packing
Bibliographic record
Abstract
The quantities of leak rate through sealing systems are subjected to strict regulations because of the global concern on radiative materials. The maximum tolerated leak is becoming a design criterion in pressure vessel design codes, and the leak rate for an application under specific conditions is required to be estimated with reasonable accuracy. In this respect, experimental and theoretical studies are conducted to characterize gasket and packing materials to predict leakage. The amount of the total leak is the summation of the permeation leak through the sealing material and the interfacial leak generated between the sealing element and its mating surfaces. Unfortunately, existing models used to predict leakage do not separate these two types of leaks. This paper deals with a study based on experimental testing that quantifies the amount of these two types of leaks in bolted gasketed joints and packed stuffing boxes. It shows the contribution of interfacial leak for low and high contact surface stresses and the influence of the surface finish of 0.8 and 6.3 μm (32 and 250 μin) resulting from phonographic grooves in the case of a bolted flange joint. The results indicate that most leakage is interfacial, reaching 99% at the low stress while interfacial leak is of the same order of magnitude of permeation leak at high stresses reaching 10−6 and 10−8 mg/s in both packing and gaskets, respectively. Finally, particular focus is put on the technique of precompression to improve material sealing tightness.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".