Numerical modelling of rotating packed beds used for <scp> CO <sub>2</sub> </scp> capture processes: A review
Bibliographic record
Abstract
Abstract Over the last decades, renewable and clean energy sources are being rigorously adopted along with carbon capture technologies to tackle the increasing carbon dioxide (CO 2 ) concentration level in the environment. CO 2 capture is a quintessential option for tackling global warming issues. In this context, the present paper has reviewed the process intensification equipment called a rotating packed bed (RPB), which is highly industry applicable due to high gravity (HiGee) force. This facilitates strong mass transfer characteristics, a compact design, and low energy consumption. In this review, the current research scenario of RPBs using numerical, computational fluid dynamics (CFD), and mathematical modelling, along with different machine learning approaches in the CO 2 capture process, has been reviewed. The different geometry designs, hydrodynamic characteristics, performance parameters, research methods, and their effects on CO 2 removal efficiency have been discussed. Furthermore, the latest experimental studies are also summarized, especially in the absorption and adsorption domain. Finally, recommendations have been given to support the RPBs in different industrial and commercial applications of CO 2 removal.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".