CFD simulation of two- and three-phase flow in FCC reactors
Bibliographic record
Abstract
Liquid distribution and evaporation in Fluid Catalytic Cracking (FCC) reactors are investigated numerically. The well-documented inaccuracy of conventional two-fluid modeling of hydrodynamics in fluidized beds of Geldart Group A particles is revisited. A new force-balance (FB) sub-grid-scale model, introduced and applied to the conventional Wen-Yu drag correlation, analyzes the balance of van der Waals, drag, gravity and buoyancy forces. It predicts formation of agglomerates inside the bed, updating the drag calculations by applying a correction factor to the conventional drag models. Good predictions are obtained of fluidization regimes and bed expansion, and there is promising agreement with experimental time-average radial voidage profiles reported by Dubrawski et al. (2013). Good quantitative agreement between discrete element models (DEM) and two-fluid predictions of minimum bubbling velocity is also observed when the model is used to predict minimum bubbling velocity, in contrast to the predictions from a non-cohesive, Wen-Yu model. Liquid injection experiments on a lab-scale fluidized bed were conducted, at the Institute of Chemical and Fuels from Alternative Sources (ICFAR) in London, Ontario to study the distribution, as well as the penetration, of liquid into catalyst pores. The results shed light on complexities involved in the injection zone to understand the effect of superficial gas velocity on evaporation and imbibition of liquid into particle pores. A methodology is developed to couple and incorporate existing liquid imbibition (into particle pores) models with evaporation models in the CFD code. The results are compared to another set of lab-scale experiments conducted at the British Columbia Research Institute (BCRI) facilities in Burnaby, BC. Simulation results demonstrate that CFD models can capture correct qualitative behavior of liquid injection and evaporation inside the bed. However, quantitative deviations revealed the likely effect of hydrodynamic properties on drying from both the liquid film around the particles and inside the pores. The deviations also imply that the assumption of convection- or diffusion-dominant drying might be unsuitable, and the two should be combined. Based on experimental results, a methodology is proposed to include the effect of hydrodynamic properties such as superficial gas velocity and particle impact velocity on drying.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".