Driving investments in ore beneficiation and scrap upgrading to meet an increased demand from the direct reduction-EAF route

Gyllenram, Rutger; Arzpeyma, Niloofar; Wei, Wenjing; Jönsson, Pär G.

doi:10.1007/s13563-021-00267-2

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…The MgO saturation varies with the temperature of the slag and composition as a function of the different compounds, such as FeO, CaO, SiO 2 , P 2 O 5 , Al 2 O 3 , TiO 2 and VO 2 . In this way, the process must be controlled through lime addition, so, as the gangue content increases, the lime percentage must be increased [17].…”

Section: Resultsmentioning

confidence: 99%

Integration of Open Slag Bath Furnace with Direct Reduction Reactors for New-Generation Steelmaking

Cavaliere

Perrone

Silvello

et al. 2022

Metals

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The present paper illustrates an innovative steel processing route developed by employing hydrogen direct reduced pellets and an open slag bath furnace. The paper illustrates the direct reduction reactor employing hydrogen as reductant on an industrial scale. The solution allows for the production of steel from blast furnace pellets transformed in the direct reduction reactor. The reduced pellets are then melted in open slag bath furnaces, allowing carburization for further refining. The proposed solution is clean for the decarbonization of the steel industry. The kinetic, chemical and thermodynamic issues are detailed with particular attention paid to the slag conditions. The proposed solution is also supported by the economic evaluation compared to traditional routes.

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Section: Resultsmentioning

confidence: 99%

Integration of Open Slag Bath Furnace with Direct Reduction Reactors for New-Generation Steelmaking

Cavaliere

Perrone

Silvello

et al. 2022

Metals

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“…RMM is a web-based, multi-purpose optimization tool using linear programming methods and process models for cost minimization and greenhouse gas emission estimations as the major objectives. It can be used for charge optimization, value in use calculations, and to assess the impact of changes in raw material properties and prices (Gyllenram and Westerberg 2016;Gyllenram et al 2021). The execution of the meltingrefining portion of the model was implemented in this software environment.…”

Section: Steelmaking Simulationsmentioning

confidence: 99%

Appraising the value of compositional information and its implications to scrap-based production of steel

et al. 2023

Self Cite

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The current nature of steel design and production is a response to meet increasingly demanding applications but without much consideration of end-of-life scenarios. The scrap handling infrastructure, particularly the characterization and sorting, is unable to match the complexity of scrapped products. This is manifested in problems of intermixing and contamination in the scrap flows, especially for obsolete scrap. Also, the segmentation of scrap classes in standards with respect to chemical compositions is based on tolerance ranges. Thus, variation in scrap composition exists even within the same scrap type. This study applies the concept of expected value of perfect information (EPVI) to the context of steel recycling. More specifically, it sets out to examine the difference between having partial and full information on scrap composition by using a raw material optimization software. Three different scenarios with different constraints were used to appraise this difference in terms of production and excess costs. With access to perfect information, production costs decreased by 8–10%, and excess costs became negligible. Overall, comparing the respective results gave meaningful insights on the value of reestablishing the compositional information of scrap at the end of its use phase. Furthermore, the results provided relevant findings and contribute to the ongoing discussions on the seemingly disparate prioritization of economic and environmental incentives with respect to the recycling of steel.

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“…[ 3 ] Such a major transition from the blast furnace–basic oxygen furnace (BF–BOF) route to the direct reduction–electric arc furnace route (DRI–EAF) would drastically increase the demand for high‐quality scrap ( Figure 1 ). [ 4 ]…”

Section: Introductionmentioning

confidence: 99%

“…[3] Such a major transition from the blast furnace-basic oxygen furnace (BF-BOF) route to the direct reduction-electric arc furnace route (DRI-EAF) would drastically increase the demand for high-quality scrap (Figure 1). [4] Even though scrap-based steelmaking processes will be of increasing importance, primary steel production (BF-BOF) will remain dominant. However, the expansion of the EAF route will be limited by the global availability of steel scrap since the integrated route consumes 35% of the totally available scrap.…”

mentioning

confidence: 99%

Toward the Decarbonization of the Steel Sector: Development of an Artificial Intelligence Model Based on Hyperspectral Imaging at Fully Automated Scrap Characterization for Material Upgrading Operations

Peña

Iriondo

Galletebeitia

et al. 2023

steel research int.

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Due to decarbonization commitment made by steelmaking companies, the steel industry is tackling a technological transition from blast furnace (BF)–basic oxygen furnace (BOF) route to direct reduction iron (DRI)–electric arc furnace (EAF) route. Under this scenario, ferrous scrap becomes a critical factor for reaching CO2 reduction challenge. However, ferrous scrap can be considered one of the most complex industrial raw materials. In addition, scrap presents a huge heterogeneity in both physical and chemical characteristics. However, for producing high‐quality steel products, certainty on scrap specifics is required. Herein, an artificial intelligent model based on spectral information for the segmentation of different materials contained in the ferrous scrap is proposed. Developed solution offers a processing pipeline through a 2D–3D convolutional neural network algorithm based on a dataset with more than 428 million of pixels through hyperspectral cameras in the 400–1700 nm range. By this model, the detection of ferric fraction, stainless steel, aluminum, zinc, copper, sterile, and rubber and plastic materials are assessed. This work aims at increasing the reliability of the steelmaking process by lowering the number of steel quality noncompliance rejection due to lack of knowledge and uncertainties of these raw material compositions.

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Driving investments in ore beneficiation and scrap upgrading to meet an increased demand from the direct reduction-EAF route

Cited by 8 publications

References 12 publications

Integration of Open Slag Bath Furnace with Direct Reduction Reactors for New-Generation Steelmaking

Integration of Open Slag Bath Furnace with Direct Reduction Reactors for New-Generation Steelmaking

Appraising the value of compositional information and its implications to scrap-based production of steel

Toward the Decarbonization of the Steel Sector: Development of an Artificial Intelligence Model Based on Hyperspectral Imaging at Fully Automated Scrap Characterization for Material Upgrading Operations

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