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Open AccessArticle

Optimization of the Iron Ore Direct Reduction Process through Multiscale Process Modeling

1
Institut Jean Lamour, CNRS, Université de Lorraine, 54011 Nancy, France
2
Laboratory of Excellence on Design of Alloy Metals for Low-Mass Structures (DAMAS), Université de Lorraine, 57073 Metz, France
*
Author to whom correspondence should be addressed.
Materials 2018, 11(7), 1094; https://doi.org/10.3390/ma11071094
Received: 29 May 2018 / Revised: 19 June 2018 / Accepted: 20 June 2018 / Published: 27 June 2018
(This article belongs to the Special Issue Design of Alloy Metals for Low-Mass Structures)
Iron ore direct reduction is an attractive alternative steelmaking process in the context of greenhouse gas mitigation. To simulate the process and explore possible optimization, we developed a systemic, multiscale process model. The reduction of the iron ore pellets is described using a specific grain model, reflecting the transformations from hematite to iron. The shaft furnace is modeled as a set of interconnected one-dimensional zones into which the principal chemical reactions (3-step reduction, methane reforming, Boudouard and water gas shift) are accounted for with their kinetics. The previous models are finally integrated in a global, plant-scale, model using the Aspen Plus software. The reformer, scrubber, and heat exchanger are included. Results at the shaft furnace scale enlighten the role of the different zones according to the physico-chemical phenomena occurring. At the plant scale, we demonstrate the capabilities of the model to investigate new operating conditions leading to lower CO2 emissions. View Full-Text
Keywords: ironmaking; direct reduction; iron ore; DRI; shaft furnace; mathematical model; simulation; CO2 emissions ironmaking; direct reduction; iron ore; DRI; shaft furnace; mathematical model; simulation; CO2 emissions
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MDPI and ACS Style

Béchara, R.; Hamadeh, H.; Mirgaux, O.; Patisson, F. Optimization of the Iron Ore Direct Reduction Process through Multiscale Process Modeling. Materials 2018, 11, 1094.

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