Optimizing airlift pumps for efficient solid-liquid transport: Effect of particle properties, submergence ratio, and injector design
Bibliographic record
Abstract
Airlift pumps have been widely utilized for liquid transport and have recently shown significant potential for efficiently handling slurry flows in many applications such as mining, wastewater treatment , dredging , and oil and gas, where the need for effective solid-liquid transport is critical for operations like removing sediments, transferring drilling mud, or managing slurries in pipelines. The present study experimentally investigates the performance of airlift pumps under three-phase solid-gas-liquid flow conditions, emphasizing the influence of particle properties (diameter and density), pump submergence ratio (SR), and injector design. The experimental setup involved two types of solid particles (glass and ceramic) with different densities (2835 kg/m³ and 2668 kg/m³) and sizes (1, 4, and 5 mm), three SRs (50 %, 70 %, and 90 %), and two injector designs (annular and swirl). High-speed imaging and flow measurements were used to assess the dynamics within the riser pipe and evaluate pump performance. It was found that the presence of solid particles significantly reduces the liquid phase deliverability , reducing the superficial velocity of the lifted liquid phase and therefore the pump's effectiveness, notably at smaller particle sizes due to momentum transfer to the solid phase and clogging effects. Pump performance was evaluated based on three key operational phases : start-up, transitional, and steady state. The results show that smaller, less dense particles and higher SRs significantly improve the solid production rate and effectiveness and accelerate the transition phase where the pump begins lifting solid particles. The swirl injector design that promotes angular momentum transfer to the liquid as the carrying medium for solids was found to increase solid particle discharge rates and consequently improve pumping effectiveness. The present results are correlated with the Stokes number to describe the inertia of the solid particles relative to viscous drag forces, determining how well the particles follow the liquid's motion. Consequently, the study introduces new performance curves that demonstrate the interaction between solid particle concentration, terminal velocity , and known airlift pump parameters such as lifting efficiency and effectiveness. These findings provide valuable insights for optimizing airlift pump system designs for a wide range of industrial applications, where efficient solid-liquid transportation is crucial.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".