ReviewHeliyon2024
A review of simulation and numerical modeling of electric arc furnace (EAF) and its processes.
Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Numerical Simulation of Short-Arc-Plasma Characteristics in DC Electrofusion Magnesium Furnaces.Materials (Basel, Switzerland) · 2026Article
- Impact of high-energy photon irradiation on early-stage dissolution of EAF slag and brownmillerite.Scientific reports · 2025Article
- Improvement of the Foaming Agent Feeding Process to an Electric Arc Furnace by Analyzing the Sound Generated by an Electric Arc and the Coefficient of Variation of Active Power Consumption.Materials (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electric Arc Furnaces (EAFs) play a pivotal part in the steel industry, offering a versatile of producing high-quality steel. This paper conducts an in-depth examination of the EAF, along with exploring mathematical modeling and optimization techniques pertinent to this furnace. Additionally, it delves into the global steel production capacity employing this technology, introduces different processes associated with EAF, scrutinizes the energy balance of EAFs, and provides an overview of numerical and simulation modeling in this context. The core focus of this extensive review is the diverse landscape of EAF simulation methods. It places particular emphasis on understanding the key components and stages of the EAF process, including charging, melting, refining, tapping, and slag removal. The review delves into the wide array of approaches and methodologies employed in EAF modeling, spanning from innovative computational fluid dynamics (CFD) and finite element analysis to the intricacies of mathematical and thermodynamic models. Furthermore, the paper underscores the importance of simulation in predicting and enhancing crucial aspects such as heat transfer, chemical reactions, and fluid dynamics within the EAF. By doing so, it contributes to the optimization of energy efficacy and the ultimate quality of steel produced in these furnaces. In conclusion, this review identifies gaps in existing knowledge and offers valuable recommendations for improving mathematical process models, underscoring the continuous efforts to enhance the efficiency, sustainability, and environmental impact of steel production processes. In conclusion, several techniques aimed at enhancing both production rates and the quality of the melting process in EAF have been put forward.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.