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Processes
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Development, Optimization and Simulation of Metallurgical Extraction Processes
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Development, Optimization and Simulation of Metallurgical Extraction Processes

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Chemical Processes and Systems".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1399

Editor

Dr. Kalenda Mutombo

E-Mail Website
Guest Editor
Advanced Materials Engineering, Manufacturing Cluster, Council for Scientific and Industrial Research (CSIR), Pretoria 0184, South Africa
Interests: metallurgical process design; process evaluation; manufacturing; characterisation of materials for mining and manufacturing sectors

Special Issue Information

Dear Colleagues,

The metallurgical industry is currently facing a "triple-pressure" scenario defined by the depletion of high-grade ores, the urgent need for decarbonisation, and the volatility of global supply chains. To survive this transition, the sector must move away from trial-and-error methodologies and toward predictive metallurgy.

This Special Issue seeks to highlight research that utilises multi-physics modelling, Computational Fluid Dynamics, and Machine Learning to optimise extraction efficiency. We invite papers that demonstrate how simulation can reduce smelting energy intensity, how optimisation algorithms can improve the recovery of critical minerals from complex tailings, and how digital twins can predict furnace behaviour in real-time. We aim to provide a comprehensive toolkit for the "Smart Smelter" of the future, for whom process development is guided by rigorous data and validated simulations.

Dr. Kalenda Mutombo
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • process modelling: computational fluid dynamics, discrete element method, and multiphase flow
  • thermodynamics: phase equilibria, slag chemistry, pyrometallurgical simulations, and hydrometallurgical kinetics
  • sustainability: low-carbon extraction, hydrogen reduction, energy recovery, and waste valorisation
  • advanced optimization: digital twins, genetic algorithms, and artificial intelligence (AI) in metallurgy
  • resource management: critical mineral recovery, tailing reprocessing, and urban mining
  • simulation and scale-up: reactor performance prediction and chemical yield optimisation
  • process intensification: reducing residence time, lowering reagent consumption, and integrating renewable energy into metallurgical units
  • fundamental development: new extractive pathways and complex mineral charactrisation

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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13 pages, 17976 KB  
Article
Prior-Informed Separation of Long-Scale Shape and Short-Scale Texture on Blast Furnace Burden Surfaces
by Jiuzhou Tian, Akira Tanaka and Di Gao
Processes 2026, 14(15), 2510; https://doi.org/10.3390/pr14152510 - 5 Aug 2026
Viewed by 308
Abstract
Particle-scale analysis of blast furnace burden surfaces lacks an operational criterion for separating long-scale shape from short-scale texture on complex digital elevation models. This study proposes a prior-informed framework in which the application cutoff ω*=argminJ minimizes the mismatch [...] Read more.
Particle-scale analysis of blast furnace burden surfaces lacks an operational criterion for separating long-scale shape from short-scale texture on complex digital elevation models. This study proposes a prior-informed framework in which the application cutoff ω*=argminJ minimizes the mismatch between high-pass texture RMS height and the tiled-surface prior of the same particle batch. On cold-state large-coke belts with identical particles but different long-scale morphology, numerical validation via RMS–frequency transition analysis shows coincident transition structures. At a transition-informed validation cutoff of ω=4.2, absolute texture errors of 1.56–3.22 mm are comparable in magnitude to the approximately 2 mm instrument depth resolution. Grid-search application yields ω*=5.8 and 4.4 with absolute errors of 0.03 and 0.35 mm and operationally distinct shape and texture components. The separated fields can supply bed-surface boundaries and local roughness inputs for gas–solid simulation and charging optimization. Full article
(This article belongs to the Special Issue Development, Optimization and Simulation of Metallurgical Extraction Processes)
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12 pages, 1343 KB  
Article
Quantitative Thermodynamic Criterion for TiC Precipitation in Molten Iron Under Industrial Blast Furnace Conditions
by Shanchao Gao, Xu Geng, Xiaobo Zhang, Yanhui Zhang, Zhe Jiang and Zhenghong Zhao
Processes 2026, 14(11), 1754; https://doi.org/10.3390/pr14111754 - 28 May 2026
Viewed by 299
Abstract
In this study, the thermodynamic conditions governing TiC formation were systematically investigated based on Gibbs free energy and interaction parameter theory. The effects of temperature and furnace atmosphere on interaction parameters were explicitly incorporated, enabling an improved thermodynamic description of TiC formation under [...] Read more.
In this study, the thermodynamic conditions governing TiC formation were systematically investigated based on Gibbs free energy and interaction parameter theory. The effects of temperature and furnace atmosphere on interaction parameters were explicitly incorporated, enabling an improved thermodynamic description of TiC formation under realistic blast furnace conditions. Furthermore, compared with conventional two-dimensional equilibrium analyses, a three-dimensional Ti-C-temperature thermodynamic precipitation surface was established to quantitatively evaluate the effects of temperature, titanium content, and carbon content on TiC precipitation behavior. The results indicate that titanium is the dominant controlling factor for TiC formation, while carbon plays a secondary synergistic role. Compared with dissolved carbon, solid carbon provides more favorable thermodynamic conditions, suggesting that TiC preferentially forms via interactions with high-activity carbon sources such as coke or refractory materials. Based on the modified thermodynamic framework and boundary conditions, a quantitative precipitation criterion was established as 100 × w[Ti]% + w[C]% ≥ 10, which ensures TiC precipitation prior to molten iron solidification under representative blast furnace hearth conditions. The proposed criterion provides a practical guideline for titanium addition and carbon regulation in blast furnace ironmaking and improves the thermodynamic prediction capability for titanium-bearing protective phase formation in complex high-temperature metallurgical environments. Full article
(This article belongs to the Special Issue Development, Optimization and Simulation of Metallurgical Extraction Processes)
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Review

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9 pages, 453 KB  
Review
A Review on Numerical Simulation and Modeling Techniques in Blast Furnace Ironmaking
by Shanchao Gao, Xu Geng, Xiaobo Zhang, Zhe Jiang, Zhenghong Zhao and Yanhui Zhang
Processes 2026, 14(12), 2014; https://doi.org/10.3390/pr14122014 - 20 Jun 2026
Cited by 1 | Viewed by 422
Abstract
Blast furnace (BF) ironmaking is a complex multiphase process involving gas–solid flow, heat transfer, chemical reactions, burden movement, and phase transformation under high-temperature conditions. Since many internal states of the blast furnace cannot be directly observed during operation, numerical simulation and mathematical modeling [...] Read more.
Blast furnace (BF) ironmaking is a complex multiphase process involving gas–solid flow, heat transfer, chemical reactions, burden movement, and phase transformation under high-temperature conditions. Since many internal states of the blast furnace cannot be directly observed during operation, numerical simulation and mathematical modeling have become important tools for understanding furnace behavior and optimizing operational parameters. This paper reviews recent advances in blast furnace numerical simulation and internal state reconstruction methods. Existing approaches, including packed-bed flow models, cohesive zone reconstruction methods, burden distribution models, and temperature field prediction methods, are summarized and discussed. In addition, the evolution of blast furnace mathematical models from early one-dimensional steady-state formulations to modern three-dimensional multifluid and hybrid simulation approaches is reviewed. Recent developments in computational fluid dynamics (CFD), the discrete element method (DEM), digital twin, and data-driven modeling are also discussed. Compared with traditional simplified models, modern multidimensional and hybrid approaches show improved capability in describing asymmetric furnace inner states, multiphase transport behavior, and operational parameter effects under industrial conditions. However, challenges still remain in achieving computational efficiency, parameter calibration, multiphase coupling, and real-time industrial application. Future studies are expected to focus on the integration of mechanism-based simulation and intelligent data-driven methods to improve prediction accuracy, operational adaptability, and intelligent control capability in blast furnace ironmaking. Full article
(This article belongs to the Special Issue Development, Optimization and Simulation of Metallurgical Extraction Processes)
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