Quantification of Swelling in Sealing Materials
Bibliographic record
Abstract
The objective of this study was to quantify swelling in gasket materials to better predict the gaskets life span in heat exchangers. Alfa Laval produces plate heat exchangers, which are a common unit within the process industry. There are different types of plate heat exchangers, and one type is sealed with gaskets. Two common types of rubber used as gasket materials are EPDM and NBR which are studied in this report. A problem that can occur in gasketed plate heat exchangers is that the gasket swell, due to a lack of resistance from the selected gasket material toward the medium. The swelling increase can cause the gaskets to be nonreusable after opening and cleaning the heat exchanger, as it no longer fits. It can also result in failures with leakages. Both types of rubber were swelled in 1-octanol and 1-decanol. Additionally, EPDM was also swelled in pentadecane and oleic acid, NBR was also swelled in triethyl citrate. The swelling was examined in two different tests, free swelling, and rubber strands. In the free swelling test, small pieces of rubber were completely immersed in a solvent. The rubber strands had only one end of the strand immersed in a solvent. This allowed solvent to diffuse up through the strand. From the free swelling test, it was shown that most combinations displayed Fickian diffusion, with some deviations. A linear relationship was found between the diffusivity, temperature, and solvents. Similarly, a linear relationship was also found for the equilibrium swelling level, temperature, and solvent. The diffusion up through rubber strands proved to be slow. Therefore, it was examined whether it was possible to find a relationship between the diffusion distance in the rubber strands and the diffusion constant calculated from free swelling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".