Modelling of multicomponent gas separation with asymmetric hollow fibre membranes—methane enrichment from biogas
Bibliographic record
Abstract
Abstract A mathematical model for the dynamic performance of gas separation with high flux, asymmetric hollow fibre membranes was developed considering the permeate pressure build‐up inside the fibre bore and cross flow pattern with respect to the membrane skin. The solution technique provides reliable examination of pressure and concentration profiles along the permeator length (both residue/permeate streams) with minimal effort. The proposed simulation model and scheme were validated with experimental data of gas separation from literature. The model and solution technique were applied to investigate dynamic performance of several membrane module configurations for methane recovery from biogas (landfill gas or digester gas), considering biogas as a mixture of CO2, N2 and CH4. Recycle ratio plays a crucial role, and optimum recycle ratio vital for the retentate recycle to permeate and permeate recycle to feed operation was found. From the concept of two recycle operations, complexities involved in the design and operation of continuous membrane column were simplified. Membrane permselectivity required for a targeted separation to produce pipeline quality natural gas by methane‐selective or nitrogen‐selective membranes was calculated. © 2012 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".