CFD application in slurry transport through Annular Jet Pump -A Mixture Model Approach
Why this work is in the frame
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Bibliographic record
Abstract
The transport of slurry plays a critical role in determining the efficiency, cost, and sustainability of largescale mining operations.Annular Jet Pumps (AJPs), owing to their simple geometry, absence of moving parts, and low maintenance demands, represent a promising alternative to conventional pumping systems.This study presents a detailed numerical investigation of sand-water slurry flow in an AJP using the mixture model within a CFD framework.The Realizable k- turbulence model is incorporated to capture the multiphase turbulence characteristics, enabling accurate prediction of particle-fluid interactions and energy dissipation mechanisms.A comprehensive parametric analysis is conducted to assess the influence of dispersedphase particle size, solid volume fraction, and geometric parameters, including nozzle radius and convergence angle, on suction performance, pressure recovery, and specific energy consumption (SEC).The results indicate that careful optimization of operating and geometric parameters can substantially enhance suction capacity while minimizing SEC, thereby improving the overall energy efficiency of the system.Model predictions are validated against established experimental and numerical benchmarks from the literature, showing strong agreement and confirming the reliability of the adopted methodology.The outcomes of this work underscore the potential of modular AJPs as sustainable, energy-efficient solutions for slurry transport in mining, with broader implications for reducing environmental footprint and operational costs.
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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 it