Sensitivity Analysis of Air Gap Membrane Distillation
Bibliographic record
Abstract
In this study, parametric sensitivity analysis using dimesionless sensitivity analysis and temperature polarization was used to investigate the sensitivity of the mass flux to the different parameters associated with the air gap membrane distillation (AGMD) process for pure water production. The model of AGMD used in this study is the approximate model proposed by Jonsson et al., which neglects the temperature polarization effect. The effect of temperature polarization is studied using another model developed by Banat and Simandl. The results obtained show that the mass flux of pure water production is highly sensitive to the feed bulk temperature, membrane porisity at low porosity values, and air gap width. Results also show that increasing the membrane thickness decreases the mass flux of pure water and decreases the temperature polarization effect. In addition, results show that the temperature polarization effect becomes significant as feed bulk temperature increases. Increasing the film heat‐transfer coefficients, increasing the diffusion path, or decreasing the membrane porosity can reduce the temperature polarization effect significantly.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".