Mathematical Modeling of CO2/CH4 Separation by Hollow Fiber Membrane Module Using Finite Difference Method
Bibliographic record
Abstract
Removal of CO2 in landfill gas recovery processes and fractured wells as well as its application in enhanced oil recovery and its environmental aspects are of interest. Also separation of CO2 from CH4 in Ethylene Oxide plant is an environmental policy of Marun Petrochemical Company. In the present work, a shell-fed hollow fiber module was modeled mathematically for CO2 separation from CH4. Finite difference method was used for solving the equations. Comparison between co-current and counter-current flow patterns showed that for all conditions, counter current pattern had better efficiency for CO2/CH4 separation. Influence of operating parameters such as feed pressure, permeate pressure, feed flow rate, fiber length and CO2 concentration of feed on separation efficiency of CO2/CH4 mixture was investigated. Also the effect of feed and permeate pressures on required membrane area showed that the membrane area increases by increasing permeate pressure and decreases by increasing feed pressure. The modeling offers valuable data about feasibility study and economical evaluation of a gas separation unit operation as a helpful unit in the industry.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".