Novel CO2 Separation Using Supersonic Separator for Carbon Capture and Storage (CCS)
Bibliographic record
Abstract
Summary The separation of the carbon dioxide (CO2) is one of the key issues of Carbon Capture and Storage (CCS). The conventional CO2 separation technology have some disadvantages including the relatively large facilities, a considerable investment, complex mechanical work, and the possibility of having a negative impact on the environment. The supersonic separation process, a revolutionary technique for CO2 removal, provides an environmentally friendly-facility by eliminating the need for chemicals. In present study, we propose a novel CO2 separation using the supersonic separator. The separation characteristics of carbon dioxide in supersonic flows are investigated using the real gas equation of state and Reynolds stress model. The results show that the gas mixture is accelerated to supersonic speed and results in a low pressure and temperature, which is good for the nucleation and condensation of the carbon dioxide. The helical vanes generate the swirling flow, which is further strengthened in the Laval nozzle. The centrifugal acceleration can reach approximately 8.08×10λ6 m/sA2 that will separate the CO2 droplets from the gas-liquid mixtures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".