Study on optimization of reduction temperature of hydrogen-based Shaft Furnace—Numerical simulation and multi-criteria evaluation

Liu, Zhengjian; Lu, Shaofeng; Wang, Yaozu; Zhang, Jianliang; Cheng, Qiang; Ma, YunFei

doi:10.1016/j.ijhydene.2023.01.057

Cited by 17 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A higher inlet temperature of the reducing gas improved the reduction performance. In the simulations of Liu et al, where H 2 /CO = 4.5, the metallization rate increased with the reducing gas temperature rising from 1123 to 1223 K. The ratio of iron reduced by hydrogen also increased, implying an enhanced utilization rate of H 2 . On one hand, the increase in the temperature of the reducing gases resulted in the injection of more sensible heat, increasing the internal temperature at the same height, as shown in Figure a.…”

Section: Model Applicationsmentioning

confidence: 92%

“…For heat transfer, the reaction heats from iron ore reduction and water–gas shift reactions are usually added to the solid phase in the plug flow and REDUCTOR models (eqs 10 and 18). − , In the Eulerian two-phase model, the reaction heat is referred to the gas and solid phases − Hamadeh et al , and Costa et al considered an additional heat source (the last term in eq 17) corresponding to the gas phase, characterizing the heat brought by the gas evolving from pellets.…”

Section: Physical Modelingmentioning

confidence: 99%

“…Zhang et al elucidated more details about the critical temperature. Several studies have simplified the multi-interface USCM to the three-interface USCM in the entire temperature range. − The USCM is suitable for the cases with weak gas diffusion in iron ore pellets. For example, Φ 2 > 10 3 –10 4 in eq , where the Thiele’s modulus (Φ) is related to the ratio between the kinetic and diffusive resistances.…”

Section: Physical Modelingmentioning

confidence: 99%

“…For example, Φ 2 > 10 3 –10 4 in eq , where the Thiele’s modulus (Φ) is related to the ratio between the kinetic and diffusive resistances. Nonetheless, the multi- and three-interface USCMs have been commonly used to describe the gas–solid chemical reactions in SFs. ,,− ,− normalΦ 2 = k · r normalp D eff …”

Section: Physical Modelingmentioning

confidence: 99%

“…The energy consumption mainly varies with the molar flow rate of the reducing gas ( q ) and the temperature ( T g,in ) and pressure ( p g,in ) of the reducing gas at the gas inlet. The known model parameters are as follows: the efficiency factors of the gas compressor and gas heater λ c = λ h = 0.7, the process gas temperature from the mixer T m = 343 K, and the process gas pressure from mixer p m = 1 atm. , The molar flow rate of reducing gas is composed of the fresh ( q fresh ) and recycled ( q recycle ) parts, and q recycle is required while considering top-gas recycling. , MR = w Fe 112 160 w Fe 2 normalO 3 + 168 232 w Fe 3 normalO 4 + 56 72 w FeO + w Fe η normalH 2 = y normalH 2 in − y normalH 2 out y normalH 2 in , goodbreak0em1em⁣ η CO = y CO in − y …”

Section: Model Applicationsmentioning

confidence: 99%

See 4 more Smart Citations

A Review on the Modeling and Simulation of Shaft Furnace Hydrogen Metallurgy: A Chemical Engineering Perspective

Fei,

Guan,

Kuang

et al. 2023

ACS Eng. Au

View full text Add to dashboard Cite

Hydrogen-based shaft furnace technology holds promise for low-carbon hydrogen metallurgy. Since hydrogen-assisted iron ore reduction is highly endothermic, inadequate heat supply relevant to the contact of gas and densely packed ores may reduce the rate and efficiency of reductions. The key to addressing this issue lies in understanding the competition among heat supply, heat transfer, and heat loss driven by the gas flow around ores and reactions within them. Modeling and simulation are crucial for revealing the underlying mechanisms and promoting process scale-up and intensification. This review summarizes previous efforts in physical modeling and model applications for improving the reduction performance. The discrete element method (DEM) and computational fluid dynamics (CFD)− DEM models have been used for particle-scale simulation to investigate inhomogeneous particle descent and relevant particle−particle interactions. For macroscale simulations, steady-state simplified models such as plug flow and REDUCTOR, as well as the Eulerian two-phase model, have been developed by considering heat and mass transfer. Based on these model applications, strategies including the optimization of operating conditions and gasfeeding methods have been proposed to improve the furnace performance. Further numerical efforts are needed to analyze the infurnace heat evolution and reduction and reveal the competitiveness of flow, transport, and reaction by incorporating multiscale physics in shaft furnaces. Additionally, attention could be paid to the effects of particle sticking and degradation on reduction, which may be more serious when the proportion of lump ores increases. When evaluating relative optimization strategies, comprehensive comparisons are expected in terms of iron ore reduction degree, gas utilization rate, energy consumption, and economic feasibility under various reducing and cooling gas operating conditions and furnace profiles to offer practical guidelines for industrial design and intensification.

show abstract

Section: Model Applicationsmentioning

confidence: 92%

Section: Physical Modelingmentioning

confidence: 99%

Section: Physical Modelingmentioning

confidence: 99%

Section: Physical Modelingmentioning

confidence: 99%

Section: Model Applicationsmentioning

confidence: 99%

See 3 more Smart Citations

A Review on the Modeling and Simulation of Shaft Furnace Hydrogen Metallurgy: A Chemical Engineering Perspective

Fei,

Guan,

Kuang

et al. 2023

ACS Eng. Au

View full text Add to dashboard Cite

show abstract

Investigation of Pellet Shape on the Hydrogen Reduction of Iron Oxide Using Mathematical Modeling and Image Processing

Hosseinzadeh,

Kasiri,

Rezaei

et al. 2023

steel research int.

View full text Add to dashboard Cite

Due to environmental concerns and climate change, the use of hydrogen gas in the reduction of iron oxide has gained more attention recently. Many factors can affect the reduction of iron oxide pellets, and among them, a few studies have considered the shape of iron oxide pellets as a parameter. To evaluate how much the pellets might diverge from their ideal state, the circularity of the pellets was evaluated in this study using an image processing technique. Although this fell to as low as 0.75 in some cases, the computed average circularity of the pellets was 0.96. Afterward, considering that the reaction is non‐catalytic, mathematical modeling was used to develop an unreacted shrinking core model (USCM) with three interfaces. The examination of the pellet’s shape was conducted using this model, resulting in relative errors of 11.13% and 25.02% for the total conversion time at shape factor values of 0.9 and 0.8, respectively. Finally, the impact of the shape factor was demonstrated by varying each of the process parameters, including temperature, pressure, reduction gas composition, and pellet size.This article is protected by copyright. All rights reserved.

show abstract

Effects of Metallization Degree of DRI on the Yield and CO2 Emission in Reduction Shaft Furnace Process

Zhou,

Jiang,

Wang

et al. 2024

J. Sustain. Metall.

View full text Add to dashboard Cite

Study on optimization of reduction temperature of hydrogen-based Shaft Furnace—Numerical simulation and multi-criteria evaluation

Cited by 17 publications

References 22 publications

A Review on the Modeling and Simulation of Shaft Furnace Hydrogen Metallurgy: A Chemical Engineering Perspective

A Review on the Modeling and Simulation of Shaft Furnace Hydrogen Metallurgy: A Chemical Engineering Perspective

Investigation of Pellet Shape on the Hydrogen Reduction of Iron Oxide Using Mathematical Modeling and Image Processing

Effects of Metallization Degree of DRI on the Yield and CO2 Emission in Reduction Shaft Furnace Process

Contact Info

Product

Resources

About