Analysis of hydrodynamic forces on solid particles in mixing tanks using coupled CFD–DEM method: Influence of impeller pumping direction and speed on mixing dynamics
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Bibliographic record
Abstract
This study presents a comprehensive analysis of hydrodynamic forces acting on particles in a three-phase (gas–liquid–solid) mixing tank using a coupled Computational Fluid Dynamics–Discrete Element Method (CFD–DEM) approach. A baffled cylindrical tank equipped with a Pitched Blade Turbine (PBT45) impeller is simulated under both upward and downward pumping directions over a range of speeds (300–800 rpm). Key particle–fluid forces — including drag, lift, pressure gradient, virtual mass, and flow-induced torque — are modeled to assess their individual and collective impacts on particle suspension and mixing dynamics. The simulations capture temporal evolution, spatial distributions, and time-averaged behavior of forces, providing insight into flow regime transitions and solid dispersion characteristics. Experimental validation is performed using both torque measurements and Electrical Resistance Tomography (ERT), showing good agreement between CFD–DEM predictions and experimental observations. Results indicate that pressure gradient and drag forces dominate particle–fluid momentum exchange, while virtual mass forces play secondary but directionally significant roles. Lift force and fluid-generated torque exhibit minor contributions across most operating conditions. Furthermore, comparison of impeller pumping directions reveals that upward pumping facilitates early suspension but shows diminishing force effectiveness at higher speeds, whereas downward pumping supports sustained force growth and more efficient suspension at high rotational speeds. These findings establish a quantitative and qualitative framework for comparing all major hydrodynamic forces in stirred tanks, offering both fundamental insight and practical recommendations for optimizing multiphase mixing simulations. • Utilization of the CFD–DEM framework to investigate the hydrodynamics of mixing systems. • Quantitative evaluation of key fluid–particle interaction forces. • Examination of the role of fluid-generated torque on particle behavior. • Recommendations for reducing computational cost in CFD–DEM simulations. • Practical insights for selecting impeller configurations in multiphase mixing processes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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