Airlift Pumps with Annulus Risers: An Experimental Investigation
Bibliographic record
Abstract
Airlift pumps are used in many industries.In these pumps, the performance is strongly affected by the geometrical design conditions.In this study, the performance of an airlift pump is experimentally evaluated for both circular and annulus pump risers.An airlift pump operating under air-water two-phase flow conditions was tested using a dual pump injector and for a constant submergence ratio.Capacitance sensors are used to measure the instantaneous void fraction through the pump riser, while high-speed images are analyzed to identify the interfacial structures of the air-water two-phase flow patterns through the pump risers.The results show that the water flow rate and efficiency of the pump for both risers are strongly dependent on the flow-pattern.In the annulus riser, higher liquid flow rates and pump efficiency are achieved at low gas flow rates, where slug pattern exists, while for the circular riser, the pump performs better at higher gas flow rates.Also, void fraction was found to be higher in the annulus riser for the entire range of gas flow rate due to the smaller cross-sectional area and the faster gas phase velocity through this area.Moreover, in the annulus riser, the Taylor bubble exhibited rotational motion around the pipe axis while moving upward.The length of Taylor bubbles in the pump riser was found to be longer and move with higher velocity and frequency in the case of the annulus riser, which is contributing to the better pump performance at low air flow rates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".