Simulation of binary gas separation with asymmetric hollow fibre membranes and case studies of air separation
Bibliographic record
Abstract
Abstract A mathematical model for high‐flux asymmetric hollow fibre membrane was developed considering the effect of permeate pressure build‐up inside the fibre bore. A new solution technique was developed to solve the model equations, which constitute a boundary value problem. The ordinary differential equations were solved as an initial value problem in two successive steps using the Gear's BDF method. The technique is advantageous since it requires minimum computational time and effort with improved solution stability, and the computational complexity does not multiply as the number of components increases. The model predictions and the robustness of the numerical technique were validated with experimental data for several membrane systems with different flow configurations. The model and the solution technique were applied to evaluate the separation characteristics of air using representative membranes with different configurations, including single‐stage, single‐stage with permeate recycle, single‐stage with retentate recycle, air blending, and two stages in series. The study demonstrates that the new solution technique can conveniently handle the high‐flux hollow fibre membrane problems with different module configurations. © 2011 Canadian Society for Chemical Engineering
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".