Direct reduction of iron-ore with hydrogen in fluidized beds: A coarse-grained CFD-DEM-IBM study
Bin Lan, Ji Xu, Shuai Lu, Yige Liu, Fan Xu, Bidan Zhao, and Zheng Zou, Ming Zhai, Junwu Wang

TL;DR
This paper introduces a novel CFD-DEM-IBM simulation approach using hybrid CPU-GPU computing to model hydrogen-based direct reduction of iron ore in fluidized beds, aiding reactor design and optimization.
Contribution
It develops a coarse-grained CFD-DEM-IBM solver with GPU acceleration and an unreacted shrinking core model for simulating hydrogen reduction in fluidized beds, enabling efficient and accurate analysis.
Findings
Simulation results agree with experimental data.
Reaction kinetics and temperature significantly affect reduction degree.
The method facilitates digital design and scale-up of ironmaking reactors.
Abstract
Hydrogen metallurgy technology uses hydrogen as the reducing agent instead of carbon reduction, which is one of the important ways to reduce carbon dioxide emissions and ensure the green and sustainable development of iron and steel industry. Due to the advantages of high gas-solid contact efficiency and outstanding mass and heat transfer, direct reduction of iron ore in fluidized beds has attracted much attention. In this study, a coarse-grained CFD-DEM-IBM solver based on hybrid CPU-GPU computing is developed to simulate the direct reduction process of two kinds of iron ore with hydrogen in fluidized beds, where an unreacted shrinking core model based on multiple reaction paths is used to model the reduction reactions, a coarse-grained model and multiple GPUs enable the significant acceleration of particle computation, and the immersed boundary method (IBM) enables the use of simple…
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Taxonomy
TopicsGranular flow and fluidized beds · Iron and Steelmaking Processes · Lattice Boltzmann Simulation Studies
