A contact-based technique for measurement of membrane tension
Bibliographic record
Abstract
Abstract Membranes are used widely in engineering applications, including the porous membranes in fuel cells and ventilation systems. In order to understand the mechanical behavior of the membrane, one should know the loads acting on it, including the tension applied to it during the manufacturing process. This study describes a novel contact-based method to measure the pre-tension for applications, such as membrane energy exchangers, where optical access to the membrane is limited. The method involves direct measurement of the membrane location under various pressures, using a novel probe, and inferring the pre-tension by comparing the results with theoretical models. The technique is validated by measuring the tension of membranes pre-tensioned to known values. The RMS deviation between the measured tension and the set pre-tension is 0.55 N m −1 , which is approximately 3% of the pre-tension used in a typical membrane energy exchanger.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".