Two-Fluid Modeling of Dilute and Dense Liquid-Particle Flows
Bibliographic record
Abstract
This thesis explores the use of computational fluid dynamics (CFD) to model multiphase flows. Specifically, a multiphase Eulerian-Eulerian model, referred to as the two-fluid model (TFM), is explored with applications to turbulent liquid-solid vertical pipe and horizontal channel flows. The TFM provides a computationally efficient method to solve multiphase flows, but requires several closures and constitutive relations. The TFM used in this research is implemented in a one-dimensional (1-D) in-house code that uses a low-Reynolds number (LRN) 𝑘 − 𝜀 turbulence model with a volume fraction solver based on the particle-phase radial/transverse momentum balance. The goals of this research were to benchmark the use of the in-house TFM to solve relatively dilute turbulent liquid-solid vertical pipe flows, explore the effects of different turbulence modulation terms, extend the use of the TFM to dense vertical pipe flows and explore the performance of the TFM for horizontal liquid-solid open-channel flows. Within the context of these goals, new particle-phase boundary conditions developed by Schneiderbauer et al. (2012b) were implemented and a particle-phase frictional stress model based on Schneiderbauer et al. (2012a) was introduced. The benchmarking of the vertical dilute liquid-solid pipe flow showed that the model adequately predicted the fluid-phase mean and fluctuating velocities but underpredicted the particle-phase mean and fluctuating velocities. Of the turbulence modulation models explored, the so-called New model was the only one capable of predicting both turbulence attenuation and turbulence enhancement, depending on the particle diameter. The application of the TFM to dense vertical pipe flows showed that the code can predict 10% bulk volume fractions flows but struggles to predict denser 30% bulk volume fraction flows. The new boundary conditions were successfully implemented, which represents an improvement over the previous heuristic boundary conditions used in the code. The use of the TFM in liquid-solid open-channel flow showed that the model could predict the mixture velocity profiles for neutrally buoyant, small particles, but failed to predict the experimental volume fraction profiles from Wang and Qian (1989). The particle-phase frictional model was implemented for these horizontal flows, but its contribution was limited and confined to the near-wall region.
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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 | 0.001 |
| 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".