Ladle Furnace Steel Research Articles

Investigation of the engineering and environmental properties of cement mortars incorporating ladle furnace steel slag

While the use of ladle steel slag in concrete offers several potential advantages, there are significant research gaps that need to be addressed to promote its safe and effective utilization in the construction industry, e.g. the variations in slag properties, such as chemical composition and physical characteristics, can influence concrete performance. Moreover, even there is some research on the mechanical properties of concrete containing ladle steel slag, more in-depth studies are needed to assess the long-term durability of such concrete and the research should focus more on evaluating the environmental impact of using ladle steel slag in concrete. The paper reports the fundamental findings of a research study focused on the treatment of ladle slag to be applied as a cement substitute in the manufacturing of cement products. The research aimed to determine the optimal proportion of admixture based on treated ladle slag and evaluate the environmental properties of the resulting cement composites. The treatment process involved mechanical activation, specifically grinding the ladle slag fraction of 0/8 mm using a vibrating mill (Coarse slag) and a ball mill (Fine slag). The treated ladle slag, as an admixture, was examined in conjunction with four types of cement (CEM I, CEM II, CEM III, and CEM V). The research findings revealed that the incorporation of coarse ladle slag enhanced the workability of fresh cement paste across all tested formulations. Moreover, the utilization of treated ladle slag as an admixture in cement paste (substituting cement) exhibited a retarding effect on the setting time. As the age of the test specimens progressed (90 to180 days), the strength properties of the samples with ladle slag admixture approached those of the cement composites prepared using natural aggregates. The climate change impact of cement mortars per strength unit spanned from 0.82 to 2.75 kg CO2eq/MPa for composites incorporating finely-ground slag, and from 0.9 to 3.1 kg CO2eq/MPa for composites utilizing coarse slag. The grinding of ladle slag, even up to 30 wt% cement replacement, did not significantly impact the overall global warming potential and climate change, considering the average mill energy consumption of 50 kWh per 1 t of material.

Life-cycle analysis of cement mortars with ladle furnace steel slag

The utilization of ladle slag holds potential for innovative advancements in concrete technology, contributing to the progression of environmentally sustainable and durable construction materials. This research explores the environmental impact of mortars incorporating treated ladle furnace steel slag at cement replacement ratios of 10%, 20%, and 30%. The ladle furnace steel slag was integrated into cement mortars of varying cement types. Life Cycle Assessment (LCA) was conducted using SimaPro software, version 9.3, employing ReCiPe and IPCC 2013 methodologies. The environmental impacts were assessed within the cradle-to-gate system boundaries, considering the grinding process of ladle furnace steel slag. The outcomes were expressed in terms of mid-point indicators. Across all cement types, a discernible reduction in the values of key environmental indicators was observed for the steel slag substitution samples compared to reference samples without cement substitution. Notably, the climate change indicator (GWP – global warming potential) exhibited a reduction of up to 54 g CO2eq per 1 kg of mortar. Grinding the slag to a higher fineness did not result in a significant escalation in the values of the monitored environmental indicators.

Swelling Potential and Performance Level of Hot Mix Asphalt Containing Not-Hydrated Ladle Furnace Steel Slags as Filler

Abstract Nowadays, the use of carbon-neutral materials is an urgent need because of energy consumption and CO2-emissions concerns. Thus, the use of ladle furnace steel slags (LFSs) is becoming common in asphalt pavement fields. One of the limitations on using LFSs is linked to swelling potential because of the changes in chemical structure due to the hydration of their components. In this study, two different asphalt binders, neat and 3.5 % styrene-butadiene-styrene modified, were mixed with limestone coarse aggregates and two fillers (limestone and LFSs) to analyze the swelling potential and the performance levels of hot mix asphalts containing not-hydrated LFSs as filler. The analysis was conducted performing the SuperPave indirect tensile test protocol at 10°C and by using a 3D-digital image correlation metadata model (3D-DICM) capable of computing the volumetric expansion of materials after four different periods of conditioning in water (24, 48, 168, and 336 h). The results showed no significant differences among the analyzed materials, highlighting that the volumetric expansion is mainly linked to the aggregates’ water absorption. On the other hand, conditioning time seems to affect the deformability of the mixtures, influencing performance level.

Stiffening effects of LFS slags reused as filler in asphalt mixtures

Nowadays, the use of Ladle Furnace Steel (LFS) is spreading in the field of asphalt pavements. LFS are generally used as filler in Hot Mix Asphalt (HMA). The main purpose of this study is to analyse and understand the role of LFS characteristics on the possible stiffening effects of asphalt materials. Different characteristics of LFSs, such as particle size distribution, specific surface area (SSA), chemical and mineralogical properties were evaluated in addition to the performance of HMAs on different scales (mastic and HMA). One type of LFS, one standard limestone and their blends were mixed with two different asphalt binders, one pure and one 3.5% Styrene–Butadiene–Styrene (SBS) cross-linked modified. The results showed no significant correlations between the physical properties of the LFS and the performance levels of the HMAs, but it was pointed out that the LFS content in the filler blend should not exceed 30%.

Research on Sustainable Bituminous Mixture for Permeable Wearing Layers in Road Pavements

A surface layer of permeable bituminous mixture has been laid on an existing pavement section. This layer, in addition to providing the pavement with draining characteristics and acoustic comfort, incorporates a residue that is difficult to apply, the ladle furnace steel slag. The tests carried out show that the designed mixture meets the requirements in terms of mechanical properties, resistance to the action of water, and porosity. Furthermore, in-situ tests on the completed layer demonstrate its excellent permeability, as well as a surface texture suitable for use on roads and highways. The introduction of the ladle furnace slag makes it possible to design a high-performance, but also environmentally sustainable, mix.

Re-using Ladle Furnace Steel slags as filler in asphalt mixtures

In the last few years, the deployment of the natural sources has been leading to re-use and recycle several materials that have been considered as “waste” so far. The proposed study analyses the possible re-employment of the Ladle Furnace Steel (LFS) slags as filler in Hot Mix Asphalt (HMA). The main aim of the research is the evaluation of both the chemical composition of LFS and the performance level of HMAs. The analysis of chemical composition involved three different hydration methods. The HMA performance level was evaluated at different scales (mixture and mastic), performing mechanical tests. Three different conventional fillers and one type of LFS were investigated in combination with two different asphalt binders. The results showed that the presence of LFS leads to an increase in brittleness in terms of mechanical response, while not significantly modifying chemical and mineral composition.

Utilization of Industrial Byproducts for Enhancing the Properties of Cement Mortars at Elevated Temperatures

The research on industrial byproducts, such as slags and fly ash, was intense during the last decades in the building sector. Apart from the environmental benefits coming from their exploitation, their application may lead to the production of cost effective and durable building materials, such as mortars and concrete. The impact of industrial byproducts on the resistance of materials to fire and elevated temperatures was assessed by many scientists, however, it is still an open field of research. In this study, locally available byproducts were investigated, including High Calcium Fly Ash (HCFA), coming from lignite-fired power plants, as well as Ladle Furnace Steel (LFS) slag and Electric Arc Furnace (EAF) slag aggregates, originating from the steel making industry. Six mortar compositions were manufactured with substitution of Ordinary Portland Cement (OPC) with HCFA and LFS slag (20% w/w) and of natural aggregates with EAF slag (50% w/w). At the age of 7, 28, and 90 days, the physico-mechanical properties of the specimens were recorded, while they were further exposed at elevated temperatures, concerning 200 °C, 400 °C, 600 °C, 800 °C, and 1000 °C. After each exposure, their physico-mechanical and microstructure characteristics were identified. From the evaluation of the results, it was asserted that HCFA and EAF slag aggregates enhanced the overall performance of mortars, especially up to 600 °C. LFS was beneficial only in combination with EAF slag aggregates.

Dissolution of olivines from steel and copper slags in basic solution

This study explores the effect of aqueous chemical environment on the dissolution rate of the minerals γ-C2S and fayalite, identified as primary phases of ladle furnace steel slag and copper slag. γ-C2S and fayalite were exposed to solutions of NaOH and Ca(OH)2, chosen to mimic the pore solutions of alkali-activated and Portland-cement based binders. While both from the olivine mineral group, γ-C2S and fayalite displayed opposing dissolution trends with respect to pH. The rates of γ-C2S dissolution were observed to decrease with higher pH, while fayalite dissolution rates increased with pH, and both relationships were described via empirical functions of the form R = k ∙ aH+n. The contrasting dependence of dissolution rate on pH for both minerals was attributed to the formation of chemically distinct surface layers on both minerals during dissolution. These results have significance for blending of slags with high olivine contents in binders with a range of aqueous chemical environments.

Performance-Based Characterization of Bituminous Mortars Prepared With Ladle Furnace Steel Slag

A circular approach to managing resources that will promote their reuse and recycling is nowadays of crucial importance for a sustainable society. In this regard, the substitution of natural aggregates by steel slag in construction materials represents a promising option. In this paper, the use of Ladle Furnace Slag (LFS) as sustainable filler and fine aggregate for asphalt mixtures is studied. In particular, the evaluation of the LFS contribution in mastic and mortar mixes at mid-range and high-service temperatures is investigated, employing a dynamic shear rheometer to assess the main viscoelastic properties as well as the fatigue and the permanent deformation resistance of the blends. The experimental findings showed that the addition of LFS led to a clear stiffening effect, altering the chemo-physical interaction with the bitumen and producing an appreciable difference in complex stiffness moduli and phase angles. Regardless of the aging condition, the use of LFS lowered the linear viscoelastic limits and increased the elasticity of blends in the case of both mastics and mortars. It caused also a slightly higher thermal dependence of the linear viscoelastic properties even if the enhanced stiffness and elasticity produced appreciable improvements in the permanent deformation resistance. In contrast, a slight reduction of fatigue resistance was observed under the test conditions and was reasonably ascribed to the higher stiffness of LFS blends. Further research is needed to strengthen these promising results and to address the issues at a multiscale level, in particular to evaluate possible lower workability and reduced ductility due to the encountered higher stiffness of slag-based materials.

Development of digital twins and optimization of resource-efficient steelmaking technologies

In this study, mathematical models, algorithms and software for dynamic simulating of processing technologies in a ladle furnace and vacuum degassers were developed, and a new method for optimizing ladle processing technologies for various steel grades was created. Physicochemical models were developed based on the laws of conservation of mass and energy, as well as the principles of non-equilibrium thermodynamics. The developed software allows us to calculate the basic characteristics of steel refining processes, such as temperature and chemical composition of slag and steel melts, kinetics of refining processes, economic indicators, energy and resource efficiency of technologies. To validate the software, the results of industrial hits and the results of the control of metal and slag were used. Nonmetallic inclusion analysis procedures have been developed using the fractional gas analysis method to control of steel cleanness and to detect and adjust the sources of inclusions formation at all stages of ladle furnace steel processing. For various steel grades, it was shown that it is possible to successfully optimize technologies using a combination of developed modeling software and fractional gas analysis. A mathematical model for the interaction of a high chromium iron base melt with a low temperature plasma was developed. Comparison of the experimental results in DC arc furnace with calculating data is in a good agreement.

Ensemble regularized local finite impulse response models and soft sensor application in nonlinear dynamic industrial processes

This paper proposes a novel adaptive soft sensor modeling method based on ensemble of regularized local finite impulse response (FIR) models, which are estimated by using the stable kernel-based regularized least squares (SKRLS), for quality prediction of nonlinear dynamic industrial processes, referred to as the ELFIR-SKRLS. Meanwhile, the proposed ELFIR-SKRLS approach provides an effective way to extend the FIR-SKRLS for nonlinear dynamic system under the ensemble learning framework, and the tricky question of model order selection can be avoided. To deal with the process nonlinearity, an improved adaptive local domain partition method is employed to adaptively partition the historical data set into multiple local domains, where the optimal benchmark window selection mechanism is proposed to ensure the samples within the benchmark window belong to the same process state. In addition, a novel prediction performance-based adaptive ensemble method is proposed to combine the outputs of local FIR models, which is based on the weighted Euclidean distance-based similarity criterion and a strategy of reducing the online computation burden. The effectiveness of the proposed ELFIR-SKRLS adaptive soft sensor is demonstrated through a sulfur recover unit process application and a ladle furnace steel refining process application.

A Novel Process Modeling Method for Steel Sulphur Content Soft Sensing during Ladle Furnace Steel Refining

A Novel Process Modeling Method for Steel Sulphur Content Soft Sensing during Ladle Furnace Steel Refining

Steel-Making dust as a potential adsorbent for the removal of lead (II) from an aqueous solution

The presence of high concentrations of toxic heavy metals such as lead Pb(II) in water is a major hazard to human health and may have a detrimental effect on the aquatic life and the environment. Implementing an efficient and economical treatment method for the reduction of Pb(II) is a major challenge that is being addressed through employing such processes as adsorption, utilizing low cost adsorbents. In this study, Steel-Making dust obtained from a local Steel Factory was utilized for the adsorption of lead Pb(II) from an aqueous solution. The determination of optimum pH condition, adsorption isotherms and kinetics studies were carried out. The experimental data were fitted to five different isotherms, including Langmuir, Freundlich, Sips, Dubinin-Radushkevich and exponential models; while the kinetic data were fitted to Pseudo-first order, Pseudo-second order, Elovich’s and intraparticle diffusion models. The fitting of the isotherm experimental data to the five isotherm models was compared through the Akaike Information Criterion (AIC). The Dubinin-Radushkevich model was found to best describe the experimental data for the adsorption of lead ions onto Ladle furnace and cyclone steel dust with high Akaike weight (wi) of 0.91 and 0.83, respectively. The optimum pH range was found to be around 4–5; working within this range prevents lead precipitation during the adsorption process. The maximum adsorption capacity for lead on Steel Dust as obtained from the Langmuir isotherm was 208.9 mg/g for the Ladle Furnace steel dust, and 39.8 mg/g for the Cyclone steel dust. Overall, the Steel-Making dust gave a high efficiency for the reduction of lead concentration in the aqueous solutions and thus could be utilized in industrial adsorption processes.

Stabilized ladle furnace steel slag for glycerol carbonate synthesis via glycerol transesterification reaction with dimethyl carbonate

Abundant waste from ladle furnace (LF) steel slag industry was utilized to catalyze the glycerol transesterification reaction with dimethyl carbonate (DMC) to synthesize valuable glycerol carbonate (GC). LF slag was modified using various sodium hydroxide (NaOH) loadings (1–15wt.%), and the catalyst samples were characterized using XRD, FTIR, TPD-CO2, and EDS techniques. Modifying the LF using different NaOH loadings enhanced the stability, basicity, and basic strength of LF. Favorable reaction conditions at the best glycerol conversion and GC yield were investigated via reaction influencing parameter screening. Thus, the 10wt.% NaOH incorporated in LF under the reaction conditions of 75°C, DMC-to-glycerol molar ratio of 2, and 3wt.% catalyst dosage achieved 99% glycerol conversion and 97% GC yield. The catalyst exhibited sufficient heterogeneity and was utilized in five successive cycles of the experiment without serious deactivation.

Determination of defects on a processed disc from S355J2 steel

Purpose – A failed disc that was forged from S355J2 round bar was investigated in order to determine the failure route cause. The purpose of this paper is to determine the defects and route cause analysis regarding their origin. Design/methodology/approach – Macroscopic evaluation, microstructure observation using light optical metallography and scanning electron microscopy with EDX analysis were the techniques used to analyse and characterize the defected areas. Findings – Macro-inclusions (up to 850 µm) that correspond to high melting aluminium rich calcium-aluminate particles were detected. Their formation, possibly due to improper calcium treatment during ladle furnace steel refining process might be associated with clogging problems at casting. SEM-EDX analysis revealed whitish spots containing Zr that could be related to submerged entry nozzle (SEN) erosion/breakage. Characteristic is the large size and unusual shape of the traced particles, as well as the presence of low Si, Na, K. The findings indicated that nozzle clogging and/or breakage at casting was most possibly the root cause of the product’s quality degradation. Originality/value – After extended root cause analysis, specific countermeasures are proposed to avoid clogging phenomena. The suggestions are based on the findings taking into account restrains of the steel-making process. Emphasis was laid in detecting the weaknesses that lead to product quality degradation and consequently in optimizing the steel-making process. Such incidents are often found during steelmaking a useful suggestion to steelmakers is to mark and remove cast parts after SEN problems are encountered. In this way quality issues in intermediate and/or final products will be avoided.

Hybrid modelling for real-time prediction of the sulphur content during ladle furnace steel refining with embedding prior knowledge

Real-time prediction of the sulphur content of steel is of great importance for operation guidance during ladle furnace (LF) steel refining. For seeking an accurate prediction, this paper proposes to establish sulphur content prediction model in a hybrid way, where a simplified first principle model is introduced and fine tuned by data-driven modelling methods. The derived hybrid model employs optimization approach to optimize its data representation part, while prior knowledge is embedded in the form of linear constraints. An innovation of the proposed methodology is the full exploitation of prior knowledge about the process for determining reasonable process parameters. Moreover, a novel optimization approach is developed for ensuring accuracy and improving solution efficiency by the integration of genetic algorithm and successive approximation method. The proposed hybrid model possesses flexible interpretable structure and adaptive learning ability. As a result, it ensures the extrapolation property for real-time prediction and is able to provide an in-depth understanding of practical desulphurization process, making it very suitable for process monitoring and operations optimization during LF steel refining. Finally, this hybrid model is validated on recorded data from an industrial LF plant.

Ladle Furnace Steel Temperature Prediction Model Based on Partial Linear Regularization Networks with Sparse Representation

AbstractPartial linear regularization networks (PLRN) combined with sparse representation technique is developed to establish the steel temperature prediction model for LF. Parametric linear part is introduced into the classical regularization networks in order to fit the partial linear structured temperature model, which is obtained by analyzing the mechanism of LF thermal system in detail. Improvement in prediction accuracy is achieved due to the well learning performance of regularization networks and the modification according to the special structure. Furthermore, sparse representation technique is adopted on original PLRN for the sake of reducing computational cost and further improving the generalization performance. Learning scheme of recursive version is designed to train the sparsely represented PLRN, in which support vectors is selected one‐by‐one and recursive algorithm is adopted for computational efficiency. The proposed method is examined by practical data. The experiment results demonstrate that the proposed method can both improve the prediction accuracy and lead to sparse solution, so that it reduce the storage need and the prediction time for practical application.

A Hybrid Model of Steel Refining in The Ladle Furnace

AbstractThe paper presents the concept of a new mathematical model, which has been used for the simulation of the ladle furnace steel refining process. The structure of the model contains a mathematical description of the steel stirring processes caused by the injection of argon and a thermodynamic description of the reactions occurring at the metal‐slag interface. Both models have been combined into a single hybrid model, using the SimuSage package. The hybrid model has served as the basis for the creation of a proprietary simulation tool, which has been used to assess the effectiveness of the metal bath desulfurization process in the ladle furnace. The applied mathematical description of the processes occurring in the ladle furnace enables the process simulation to be carried out in real time. The constructed model has been verified in industrial conditions for a ladle furnace of 140 t capacity.