Numerical simulation and optimisation of unconventional three‐section simulated countercurrent moving bed chromatographic reactor for oxidative coupling of methane reaction
Bibliographic record
Abstract
Abstract The simulated countercurrent moving‐bed chromatographic reactor (SCMCR) has been reported to significantly enhance methane conversion and C2 product yield for oxidative coupling of methane (OCM) reaction, which is otherwise a low per pass conversion reaction. A mathematical model of an unconventional three‐section SCMCR for OCM was first developed and solved using numerically tuned kinetic and adsorption parameters. The model predictions showed good agreement with available experimental results of SCMCR for OCM. Effects of several process parameters on the performance of SCMCR were investigated. A multi‐objective optimisation problem was solved at the operating stage using state‐of‐the‐art AI‐based non‐dominated sorting genetic algorithm with jumping genes adaptations (NSGA‐II‐JG), which resulted in Pareto Optimal solutions. It was found that the performance of the SCMCR could be significantly improved under optimal operating conditions. © 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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".