High-fidelity modelling of unburnt coal flow in an industry-scale blast furnace using a hybrid CFD-DEM method

被引:2
作者
Xie, Zhouzun [1 ]
Shen, Yansong [1 ]
机构
[1] Univ New South Wales, Sch Chem Engn, Sydney, NSW 2052, Australia
基金
澳大利亚研究理事会;
关键词
CFD-DEM method; Pulverised coal injection; Blast furnace; GAS-POWDER FLOW; NEURAL-NETWORK; SOLID FLOW; SIMULATION; ACCUMULATION; INJECTION; TUYERE; BED; COMBUSTION; IRONMAKING;
D O I
10.1016/j.ces.2024.120929
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Solid fuels, such as coal or biochar, can be injected into a blast furnace for low-carbon ironmaking. However, unburnt coal or biochar powders may accumulate in the coke bed, potentially reducing bed permeability and compromising furnace stability. Current CFD-DEM methods struggle to simulate systems with significant size differences between coke particles and coal or biochar powders, where the diameter ratio dck/dcl is 100-200 times. In this work, a novel multi-resolution hybrid CFD-DEM model is developed to simulate gas-unburnt powders-coke particles flow dynamics within and around the raceway with high fidelity. The model's accuracy is validated by comparing the simulated evolution of the raceway cavity shape with experimental results. Subsequently, the hybrid model is used to simulate unburnt powder flow through the raceway and the adjacent coke bed (dck/dcl = 100), comparing its performance with the conventional smoothed CFD-DEM model. The effects of gas inlet velocity and powder wettability are also analysed. Results show that the hybrid CFD-DEM model effectively simulates detailed pore fluid flow in the coke bed, which the smoothed model fails to capture, demonstrating the hybrid model's superiority. Increasing gas inlet velocity enlarges the raceway cavity, intensifies high-speed pore flows, and accelerates powder transport into the coke bed. Additionally, higher cohesion energy density (kCED) reduces powder penetration, aligns the peak holdup position and penetration angle, and decreases permeability at key probe positions. This work provides an effective and efficient numerical tool to help understand and optimise the injection operation in blast furnaces.
引用
收藏
页数:23
相关论文
共 60 条
[1]   Artificial neural network and response surface methodology for modeling reverse osmosis process in wastewater treatment [J].
Alardhi, Saja Mohsen ;
Salman, Ali Dawood ;
Breig, Sura Jasem Mohammed ;
Jaber, Alaa Abdulhady ;
Fiyadh, Seef Saadi ;
Aljaberi, Forat Yasir ;
Nguyen, D. Duc ;
Van, Bao ;
Le, Phuoc-Cuong .
JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY, 2024, 133 :599-613
[2]   A FLUID MECHANICAL DESCRIPTION OF FLUIDIZED BEDS [J].
ANDERSON, TB ;
JACKSON, R .
INDUSTRIAL & ENGINEERING CHEMISTRY FUNDAMENTALS, 1967, 6 (04) :527-&
[3]   Size-Dependent Penetration of Nanoparticles in Tumor Spheroids: A Multidimensional and Quantitative Study of Transcellular and Paracellular Pathways [J].
Chen, Wenjing ;
Wang, Wenqian ;
Xie, Zhouzun ;
Centurion, Franco ;
Sun, Bin ;
Paterson, David J. ;
Tsao, Simon Chang-Hao ;
Chu, Dewei ;
Shen, Yansong ;
Mao, Guangzhao ;
Gu, Zi .
SMALL, 2024, 20 (08)
[4]   DISCRETE NUMERICAL-MODEL FOR GRANULAR ASSEMBLIES [J].
CUNDALL, PA ;
STRACK, ODL .
GEOTECHNIQUE, 1979, 29 (01) :47-65
[5]   THE VOIDAGE FUNCTION FOR FLUID PARTICLE INTERACTION SYSTEMS [J].
DIFELICE, R .
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW, 1994, 20 (01) :153-159
[6]   Gas-powder flow and powder accumulation in a packed bed II: Numerical study [J].
Dong, XF ;
Zhang, SJ ;
Pinson, D ;
Yu, AB ;
Zulli, P .
POWDER TECHNOLOGY, 2004, 149 (01) :10-22
[7]   Gas-powder flow and powder accumulation in a packed bed I. Experimental study [J].
Dong, XF ;
Pinson, D ;
Zhang, SJ ;
Yu, AB ;
Zuilli, P .
POWDER TECHNOLOGY, 2004, 149 (01) :1-9
[8]   Performances of pulverized coal injection in blowpipe and tuyere at various operational conditions [J].
Du, Shan-Wen ;
Chen, Wei-Hsin ;
Lucas, John .
ENERGY CONVERSION AND MANAGEMENT, 2007, 48 (07) :2069-2076
[9]   A fictitious domain approach for the simulation of dense suspensions [J].
Gallier, Stany ;
Lemaire, Elisabeth ;
Lobry, Laurent ;
Peters, Francois .
JOURNAL OF COMPUTATIONAL PHYSICS, 2014, 256 :367-387
[10]  
Gu M, 2008, STEEL RES INT, V79, P17, DOI [10.2374/SRI07SP050, 10.1002/srin.200806311]