CO2 capture using gas-lift pumps operating under two-phase flow conditions
Bibliographic record
Abstract
• Gas-lift pumps is evaluated for degasification (CO 2 stripping). • Simulated flue gas containing different volumetric CO2 concentrations is investigated. • Two-phase flow hydrodynamics is evaluated using high-speed imaging and capacitance sensor . • Churn flow is found to demonstrate superior mass transfer performance. • The CO 2 mass transfer performance exhibits a linear growth trajectory within the slug flow regime. CO 2 capture through dissolution in water offers environmental benefits and industry applications. However, current studies mostly focus on CO 2 extraction into solvents, overlooking its direct solubility in water. Alternatively, gas-lift pumps may hold significant potential for capturing and storing CO 2 in water; but this ability remains unexplored. Therefore, this study experimentally delves into the CO 2 capture capacity and hydraulic performance of a dual injection gas-lift pump with a 25.4 m m riser diameter. Operating at a constant submergence ratio of 70 %, the pump is fed with simulated flue gas with flow rates within 5–30 L P M at volumetric CO 2 concentrations of 10 %, 15 %, and 25 %, and temperatures of 22 °C (isothermal operation) and 110 °C (non-isothermal operation). Two-phase flow hydrodynamics is also evaluated using high-speed imaging in conjunction with time-series void fraction measurements. Within the riser pipe, three distinct two-phase flow patterns — slug, intermittent, and churn flows — are identified. The results reveal that under both isothermal and non-isothermal operations and across all volumetric CO 2 concentration levels, churn flow demonstrates superior mass transfer coefficient and lifted liquid flow rate, while slug flow achieves minimum energy consumption per ton of captured CO 2 , highest CO 2 capture degree, and maximum lifting efficiency. Also, the highest degrees of sensitivity to inlet gas flow rate for volumetric mass transfer coefficient, delivered liquid flow rate, and void fraction were observed in slug flow regime. Both gas temperature and volumetric CO 2 concentration positively impacted the mass transfer performance. However, the pump showed remarkably higher lifting efficiencies under isothermal operation conditions. Moreover, compared to four established CO 2 capture methods (absorption, adsorption, cryogenic distillation, and membrane diffusion), the gas-lift pump exhibits moderately lower energy consumption, at 38-266 k W h / t o n C O 2 , but with lower CO 2 capture degree of 2.3 % to 6.7 %.
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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 | 0.000 | 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) | 0.000 | 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".