Effect of dryer fabric structure on the performance of contact paper drying
Bibliographic record
Abstract
Existing measurement techniques have prevented extensive investigations of the effect of dryer fabric structure on contact drying of paper. Using a novel optical measurement method, the moisture content (MC) of paper can be accurately quantified at high spatial and temporal resolution while it is sandwiched between the heater surface and the dryer fabric. To study the paper drying process, an experimental setup is designed to simulate realistic conditions of a typical paper dryer while providing optical access for the measurement system. Ten commercially available fabrics manufactured by weaving synthetic filaments are used in the investigations. The 3D structure of the fabrics is characterized using optical coherence tomography (OCT). The fabrics are used in the experiments to investigate the effects of the filament structure and paper/fabric contact on the drying process. It is shown the fabric structure affects the drying rate and the drying time. Fabrics that have a relatively large drying rate at high paper MC may have a relatively small drying rate at low levels of MC. The contact area and 3D arrangement of the filaments have the greatest impact on the drying process. Adjacent filaments result in larger blocked regions of the paper surface, which reduces the drying rate. The spatial distribution of moisture as a function of time reveals that frequent rewetted spots appear during the drying. These rewetting spots are caused by reabsorption of water condensed on the fabric filaments.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".