Effect of Drag Models on the Numerical Simulations of Bubbling and Turbulent Fluidized Beds

2021 ◽  
Vol 44 (5) ◽  
pp. 865-874
Author(s):  
Mona Mary Varghese ◽  
Teja Reddy Vakamalla ◽  
Bhargav Mantravadi ◽  
Narasimha Mangadoddy
Keyword(s):  
Numerical Simulations ◽  
Fluidized Beds ◽  
Drag Models

scholarly journals Analysis and development of novel data-driven drag models based on direct numerical simulations of fluidized beds

2021 ◽  
Vol 231 ◽  
pp. 116245
Author(s):  
Kun Luo ◽  
Dong Wang ◽  
Tai Jin ◽  
Shuai Wang ◽  
Zhuo Wang ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Fluidized Beds ◽  
Direct Numerical Simulations ◽  
Data Driven ◽  
Drag Models

A CFD Study of Existing Drag Models for Geldart A Particles in Bubbling Fluidized Beds

2014 ◽  
Author(s):  
Bahareh Estejab ◽  
Francine Battaglia
Keyword(s):  
Experimental Data ◽  
Fluidized Beds ◽  
Fine Particles ◽  
The Other ◽  
Particle Interactions ◽  
Model Group ◽  
Drag Model ◽  
Numerical Studies ◽  
Solid Phases ◽  
Drag Models

In this study, seven drag models are examined to determine how they affect fluidization behavior of Geldart A particles of biomass and coal. Notwithstanding the notable number of numerical studies to find the best drag model for larger particles, there is a dearth of information related to drag models for finer Geldart A particles. Additionally, to our knowledge, these drag models have not been tested with a binary mixture of Geldart A particles. Computational fluid dynamics was used to model the gas and solid phases in an Eulerian-Eulerain approach to simulate the particle-particle interactions of coal-biomass mixtures and compare the predictions with experimental data. In spite of the previous findings that bode badly for using predominately Geldart B drag models for fine particles, the results of our study reveal that if static regions of mass in the fluidized beds are considered, these drag models work well with Geldart A particles. It was found that the seven drag models could be divided into two categories based on their performance. One category included the Gidaspow family of drag models (Gidaspow, Gidaspow-Blend, and Wen-Yu) and the Syamlal-O’Brien drag model; these models closely predicted the experiments for single solids phase fluidization. For binary mixtures, however, the other drag model group (BVK, HYS, Koch and Hill) yielded better predictions.

Assessment of Drag Models for Geldart A Particles in Bubbling Fluidized Beds

2015 ◽  
Vol 138 (3) ◽  
Author(s):  
Bahareh Estejab ◽  
Francine Battaglia
Keyword(s):  
Binary Mixtures ◽  
Fluidized Beds ◽  
Fine Particles ◽  
Poplar Wood ◽  
Hydrodynamic Behavior ◽  
Empirical Relationships ◽  
Drag Model ◽  
Model Predictions ◽  
Solid Phases ◽  
Drag Models

In order to accurately predict the hydrodynamic behavior of gas and solid phases using an Eulerian–Eulerian approach, it is crucial to use appropriate drag models to capture the correct physics. In this study, the performance of seven drag models for fluidization of Geldart A particles of coal, poplar wood, and their mixtures was assessed. In spite of the previous findings that bode badly for using predominately Geldart B drag models for fine particles, the results of our study revealed that if static regions of mass in the fluidized beds are considered, these drag models work well with Geldart A particles. It was found that drag models derived from empirical relationships adopt better with Geldart A particles compared to drag models that were numerically developed. Overall, the Huilin–Gidaspow drag model showed the best performance for both single solid phases and binary mixtures, however, for binary mixtures, Wen–Yu model predictions were also accurate.

scholarly journals Numerical simulations of lateral solid mixing in gas-fluidized beds

2014 ◽  
Vol 120 ◽  
pp. 117-129 ◽  
Author(s):  
Oyebanjo Oke ◽  
Paola Lettieri ◽  
Piero Salatino ◽  
Roberto Solimene ◽  
Luca Mazzei
Keyword(s):  
Numerical Simulations ◽  
Fluidized Beds ◽  
Gas Fluidized Beds

scholarly journals APPLICATION OF THE LINEAR SPRING-DASHPOT MODEL IN THE CFD-DEM SIMULATION OF ALUMINA FLUIDIZATION

2015 ◽  
Vol 14 (2) ◽  
pp. 95
Author(s):  
A. M. C. Branco Jr ◽  
A. L. A. Mesquita ◽  
J. R. P. Vaz
Keyword(s):  
Experimental Data ◽  
Fluidized Beds ◽  
Limiting Factors ◽  
Uniform Size ◽  
Ansys Fluent ◽  
Dem Simulation ◽  
Linear Spring ◽  
Computational Fluid Dynamics Cfd ◽  
Drag Models ◽  
Particle Approach

The coupling of the Computational Fluid Dynamics (CFD) to the Discrete Element Method (DEM) to simulate fluidization is computationally demanding. Although the Linear Spring-Dahspot (LSD) model can help to reduce the CFD-DEM simulation runtime due to its simplicity, its applicability is not reasonable for all sorts of problems. The objective of the present work is to show the application of the LSD model to the CFD-DEM simulation of alumina fluidization. The simulations were carried out with the software ANSYS FLUENT 14.5 and divided into two parts: (1) the reproduction with ANSYS FLUENT of simulations from the literature in which the LSD model and a representative particle approach were used. (2) the simulation of alumina fluidization and validation with experimental data. The results of three main sets of parameters were analysed to include different DEM and CFD time steps, drag models, the representation of particles with both uniform size and particle size distribution, etc. The main conclusion of this work is that the LSD model and the CFD-DEM approach can be used to model the actual behaviour of alumina fluidized beds, but the high simulation runtime and the correct setting of the strategies used to control it are still limiting factors which deserve special attention.

scholarly journals A Model to Improve Granular Temperature in CFD-DEM Simulations

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4730 ◽  
Author(s):  
Yaxiong Yu ◽  
Li Zhao ◽  
Yu Li ◽  
Qiang Zhou
Keyword(s):  
Drag Force ◽  
Fluidized Beds ◽  
Present Model ◽  
Fluid Dynamic ◽  
Direct Numerical Simulations ◽  
Granular Temperature ◽  
Force Fluctuations ◽  
Dem Simulations ◽  
Inhomogeneous Systems ◽  
Drag Models

CFD-DEM (computational fluid dynamic-discrete element method) is a promising approach for simulating fluid–solid flows in fluidized beds. This approach generally under-predicts the granular temperature due to the use of drag models for the average drag force. This work develops a simple model to improve the granular temperature through increasing the drag force fluctuations on the particles. The increased drag force fluctuations are designed to match those obtained from PR-DNSs (particle-resolved direct numerical simulations). The impacts of the present model on the granular temperatures are demonstrated by posteriori tests. The posteriori tests of tri-periodic gas–solid flows show that simulations with the present model can obtain transient as well as steady-state granular temperature correctly. Moreover, the posteriori tests of fluidized beds indicated that the present model could significantly improve the granular temperature for the homogenous or slightly inhomogeneous systems, while it showed negligible improvement on the granular temperature for the significantly inhomogeneous systems.

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