Research Progress on Numerical Simulation Methods for Metallurgical Fluidization

Numerical simulation has become a powerful and versatile toolkit for investigating gas–solid flow behavior in metallurgical fluidization processes. This review summarizes recent advances in the application of computational fluid dynamics (CFD)-based approaches, particularly the Eulerian–Eulerian and Eulerian–Lagrangian methods, within the field of metallurgical fluidization. It covers model development, particle and bubble dynamics, reactor flow field analysis, and structural optimization. The study demonstrates that numerical simulation plays a crucial role in elucidating fluidization mechanisms, optimizing process parameters, and guiding reactor design. For example, numerical simulation provides key quantitative insights, such as the enhancement of iron ore reduction rates by up to 40% with increased gas velocity and the optimization of reactor cone angles to 5–10° for improved stability, in the design of hydrogen-based iron oxide reduction reactors. However, this review identifies that current research is predominantly focused on iron ore reduction, while numerical studies on fluidized-bed smelting of non-ferrous metals, such as zinc, copper, and aluminum, remain relatively limited. Future efforts should aim to broaden the application of numerical simulation in non-ferrous metallurgy, develop efficient multi-scale coupled computational methods, and integrate artificial intelligence technologies to advance metallurgical fluidization toward greater efficiency, energy savings, and intelligent operation.

Authors

Institutions

Publication Details

Journal
Processes
Published
2026-02-05
DOI
https://doi.org/10.3390/pr14030555
Primary Topic
Granular flow and fluidized beds
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research Progress on Numerical Simulation Methods for Metallurgical Fluidization

Zhenglin Zhang, Hongliang Zhao, Fan Li, Fengqin Liu et al.
Processes
Granular flow and fluidized beds
article

Research Progress on Numerical Simulation Methods for Metallurgical Fluidization

Zhenglin Zhang, Hongliang Zhao, Fan Li, Fengqin Liu, Mingzhuang Xie, Rongbin Li
article en

Abstract

Numerical simulation has become a powerful and versatile toolkit for investigating gas–solid flow behavior in metallurgical fluidization processes. This review summarizes recent advances in the application of computational fluid dynamics (CFD)-based approaches, particularly the Eulerian–Eulerian and Eulerian–Lagrangian methods, within the field of metallurgical fluidization. It covers model development, particle and bubble dynamics, reactor flow field analysis, and structural optimization. The study demonstrates that numerical simulation plays a crucial role in elucidating fluidization mechanisms, optimizing process parameters, and guiding reactor design. For example, numerical simulation provides key quantitative insights, such as the enhancement of iron ore reduction rates by up to 40% with increased gas velocity and the optimization of reactor cone angles to 5–10° for improved stability, in the design of hydrogen-based iron oxide reduction reactors. However, this review identifies that current research is predominantly focused on iron ore reduction, while numerical studies on fluidized-bed smelting of non-ferrous metals, such as zinc, copper, and aluminum, remain relatively limited. Future efforts should aim to broaden the application of numerical simulation in non-ferrous metallurgy, develop efficient multi-scale coupled computational methods, and integrate artificial intelligence technologies to advance metallurgical fluidization toward greater efficiency, energy savings, and intelligent operation.

ProcessesVol. 14(3)
Aluminum Corporation of China (China) (CN), China Nonferrous Metal Mining (China) (CN), University of Science and Technology Beijing (CN)
Affordable and clean energy
Openalex Percentile: Top 62%
Granular flow and fluidized beds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research Progress on Numerical Simulation Methods for Metallurgical Fluidization — Zhenglin Zhang, Hongliang Zhao, et al. · Processes (2026) | TGRS Research Map | TGRS