Emission of Fine Particles and Ageing Behavior of PTFE Finished Filter Media during Industrial Pollution Control
Bibliographic record
Abstract
Present study embodies the effect of two different filter media viz. polyester filter fabric treated with PTFE finish and polyester fabric filter without finish, and two different dust concentration (50 and 150 g/m3) on industrial pulse-jet filtration process performance. The fabrics were tested based on ISO - 11057 Standard, while conducting 200 pulsing cycles at measuring phase. Emission in terms of mass concentration (PM2.5, PM10) and number particle concentration are substantially lower while using PTFE finished filter media in comparison to media without finish. Outgoing particle number largely reduced while using PTFE treated fabrics particularly at higher dust concentration. The particle size distribution in the downstream side reflects that use of PTFE finish filter is particularly more beneficial for capturing very fine particle. PTFE finish fabric also exhibit lower residual pressure drop as compared to unfinished fabric during measuring phase of filtration operation. Further it was also evident that the trend of residual pressure drop with time is quite stable for PTFE finished fabrics. The said fabric get stable (age) earlier than without finish, hence expected to provide more consistent filtration behaviour for longer time.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".