Sinter Plant Research Articles

Adaptability analysis of H2-rich gas injection and sintered ore performance with different raw material ratios

As a source substitution technology that reduces pollutants emission and optimizes sinter properties, H2-rich gas injection-assisted iron ore sintering holds significant practical value. This study analyzed the adaptability of this technology to different ore blend ratios and basicity levels by comparing sintering indexes, pore structure, mineral phase composition, and metallurgical performance before and after H2-rich gas injection. The carbon emission reduction following H2-rich gas injection was calculated. The results indicate that increasing the proportion of high-silica, low-alumina ore (Ore-A) and basicity, along with H2-rich gas injection, can effectively enhance sinter yield and quality, but shrink the pore structure of sinter. Under H2-rich gas injection conditions, decreasing Ore-A ratios and increasing basicity can augment SFCA phase formation and mineral phase uniformity, thereby improving the anti-pulverization ability and reductivity of the sinter. H2-rich gas injection presents better adaptability to sintered ore with lower Ore-A ratio and basicity, which can achieve greater improvements in the sintering indexes, RDI, and RI. For a 265 m2 sinter plant producing sinter with 18 wt% Ore-A and 2.0 basicity, annual CO2 emissions can be reduced by approximately 40,000 t.

DETERMINATION OF OPTIMAL PARAMETERS OF SINTERING OF ROLLING SCALE

This article presents the results of studies conducted to determine the optimal parameters of sintering of rolled scale in a mixture with iron-containing steelmaking waste. The conducted studies of sintering of rolled scale have shown that the gas permeability of the charge depends on a number of physical properties, the size and shape of the grains, the amount of return, the height of the charge layer, and the moisture content of the charge. The initial gas permeability strongly depends on the degree of humidification of the agglomeration charge, especially when sintering small classes of materials under study. The maximum gas permeability of the charge is ensured with an optimal granulometric composition of the charge, which is characterized by an average equivalent diameter: the higher this indicator, the higher the gas permeability of the charge. The value of the surface tension reaches its maximum at a certain moisture content of the charge, which is the optimal moisture for this charge. By increasing the amount of return during agglomeration, the vertical sintering rate increases and the quality of the agglomerate improves. These factors lead to an increase in the productivity of sintering plants. According to the results of the study, the optimal parameters of the sintering sintering process of rolled scale in a mixture with iron-containing steelmaking waste were worked out. It is established that the optimal amount of return is the use of 20 % of the mass of the sintering charge at the optimal height of the sintered layer of 300 mm. As a result of the conducted research, the following optimal indicators were achieved: mechanical strength – 70.2 %, sintering rate – 28.7 mm/min, specific productivity – 1.75 t/m2·hour. Keywords: Rolling scale, agglomeration, optimal parameters, sintering, return, layer height.

Mercury Concentrations in Dust from Dry Gas Cleaning of Sinter Plant and Technical Removal Options

Mercury (Hg) is a naturally occurring element and has been released through human activities over an extended period. The major source is the steel industry, especially sinter plants. During a sintering process, high amounts of dust and gaseous emission are produced. These gases contain high loads of SOx and NOX as well as toxic pollutants, such as heavy metals like Hg. These toxic pollutants are removed by adsorbing to solids, collected as by-products and deposited as hazardous waste. The by-products contain a high amount of salt, resulting in a high water solubility. In this study, to ultimately reduce the waste amount in landfills, leachates of the by-products have been produced. The dissolved Hg concentration and its distribution across different charges were determined. Hg concentrations between 3793 and 12,566 µg L−1 were measured in the leachates. The objective was to lower the Hg concentration in leachates by chemical precipitation with sodium sulfide (Na2S) or an organic sulfide followed by filtration. Both reagents precipitate Hg with removal rates of up to 99.6% for the organic sulfide and 99.9% for Na2S, respectively. The dose of the precipitator as well as the initial Hg concentration affected the removal rate. In addition to Hg, other relevant heavy metals have to be included in the calculation of the amount of precipitator as well. Between relevant heavy metals including Hg and sulfide, the ratio should be more than 1.5. The novelty of this study is the measurement and treatment of Hg in wastewater with a high ionic strength. The high salt concentrations did not influence the efficiency of the removal methods. An adjustment of the precipitator dose for each sample is necessary, because an overdose potentially leads to the re-dissolving of Hg. It could be shown that the emission limit of 0.005 mg L−1 could be reached especially by precipitation with Na2S.

Analysis of the sintering process of the sintering charge in a high layer. Report 1. Fuel combustion and dissociation of limestone

Communication 1 provides a brief overview of theoretical works on the creation of mathematical models of the sintering process, ranging from simplified balance models to the three-dimensional dynamic model. A modern three-dimensional mathematical model is adapted from industrial data on the agglomeration of a sinter mix in a bed 700 mm high with a bed of sinter at the sinter plant No. 5 of PJSC “MMK”. Changes in the device circuit diagram of sinter plan, the actual temperature of the mix, segregation of fuel along the height of the bed, the mode of intensive ignition of the mix in the ignition hearth with diffusion burners, the unevenness of the sintering process across the width of the pallets, additional heating of the bed after the hearth with air from a linear cooler, the actual degree of throttling of the vacuum chambers of the sinter machine, heat exchange in pallets are taken into account. The process of a combustion zone of solid fuel formation under the ignition hearth has been analyzed, and an increase in its height during the sintering process in a high bed has been established, that due to the segregation of mix and fuel along the height of the bed and the consumption of oxygen for the oxidation of FeO above this zone. The processes of limestone dissociation and melting of the mix zones formation and their development during the sintering process are considered

Analysis of the sintering process of the sintering charge in a high layer. Report 2. Reduction and oxidation processes, moisture behavior and gas dynamics of the sintering process

Piece of information 1 of this article briefly examines the history of the development of modeling the sintering process. To study it, a modern three-dimensional mathematical model was used. Its adaptation was made for the operating conditions of sinter plant No. 5 of PJSC “MMK”, on whose sinter machines the mix is sintered in a bed 700 mm high. Studies have been carried out on the formation and development of fuel combustion and limestone dissociation zones. In the information under consideration, the reduction and oxidation processes of moving the temperature fields of the material with the melt, the combustion zone, processes of gas formation along the height of the bed are presented together. It has been established that a small-height Fe2O3 reduction zone is formed under the fuel combustion zone, and that the conditions for the formation of an oxidation zone under the fuel combustion zone, discussed in the literature, are extremely unfavorable. An analysis of the processes of drying and waterlogging of the mix in a high bed was carried out. A lesser negative impact of moisture condensation in a high bed has been established compared to a low or medium height bed. The gas-dynamic operation of the bed under the ignition hearth with throttling conditions of the first vacuum chambers of the sinter machine is considered. A decrease in the rate of gas filtration at the outlet of the bed was established in comparison with the input rate after the drying and fuel combustion zones exited the bed.

Batch Sintering of FeO·OH and Fe2O3 Blends: Chemical and Metallurgical Characterization

A sample of goethite iron ore sinter feed (G_SF) was employed as a raw material in a sintering bed. This sample partially replaced hematite sinter feed (H_SF), which is currently used as raw material in a sintering plant in the state of Minas Gerais, Brazil. This substitution did not adversely affect the chemical and metallurgical proprieties of the sinter mix product, provided that the utilization of G_SF was kept below 30% in weight. Despite the higher proportion of fines in G_SF, the presence of argillaceous minerals in the sample led to an improvement in the granulation index (GI) of the sinter mix product. The GI value increased from 68.4 to 82.7% for the experiments conducted without the presence of goethite ore and with 40% of goethite ore in the sintering mix, respectively. Consequently, the qualities of both the process and the produced sinter product were not compromised. The raw materials and the various sinters produced were characterized through X-ray fluorescence (XRF) and X-ray diffraction (XRD), as well as thermal gravimetric analysis (TGA). The XRD results were used to perform a quantitative assessment of the mineral phase using the Rietveld method (RM). This technique allowed for the determination of goethite content in the studied sample, which was 35.5%. Finally, the incorporation of G_SF in the sintering bed led to a 20% reduction in the cost of raw materials.

Intelligent Sinter Machine Speed Control System Using Optimized Fuzzy Logic Controller: An Experimental Study in Iron and Steel Plant

Intelligent control systems developed for production facilities significantly contribute to production efficiency and quality. Using intelligent control systems has now become a necessity in iron and steel sintering plants that produce millions of tonnes annually. Automatic control of the sinter machine speed, which directly affects production efficiency and quality, is one of the first issues to be addressed. The complexity of the sintering process, being affected by many variables, and the nonlinearity of these variables make it difficult to control the machine speed. This study demonstrates that we have overcome this challenge using a fuzzy logic controller (FLC), which is optimized with an adaptive neuro-fuzzy inference system (ANFIS). The FLC we have designed operates with the characteristic point of the thermal state, the mixture level, the vacuum average, and the current speed parameters. We achieved an average success rate of 95%. The developed system automatically controls the speed of the sinter machine with high accuracy, independent of the operator. The system we have developed is used continuously at the Iskenderun Iron & Steel Co. sinter plant. The results obtained from the production facility show that the developed system captures the thermal change in the sinter pallet and manages the machine accordingly, increases the sintering efficiency by at least 10%, and ensures process safety. These results revealed that the developed system can be used effectively in the iron and steel industry and the use of the system will increase efficiency.

A comprehensive examination of temporal-seasonal variations of PM1.0 and PM2.5 in taiwan before and during the COVID-19 lockdown

COVID-19 has been a significant global concern due to its contagious nature. In May 2021, Taiwan experienced a severe outbreak, leading the government to enforce strict Pandemic Alert Level 3 restrictions in order to curtail its spread. Although previous studies in Taiwan have examined the effects of these measures on air quality, further research is required to compare different time periods and assess the health implications of reducing particulate matter during the Level 3 lockdown. Herein, we analyzed the mass concentrations, chemical compositions, seasonal variations, sources, and potential health risks of PM1.0 and PM2.5 in Central Taiwan before and during the Level 3 lockdown. As a result, coal-fired boilers (47%) and traffic emissions (53%) were identified as the predominant sources of polycyclic aromatic hydrocarbons (PAHs) in PM1.0, while in PM2.5, the dominant sources of PAHs were coal-fired boilers (28%), traffic emissions (50%), and iron and steel sinter plants (22.1%). Before the pandemic, a greater value of 20.9 ± 6.92 μg/m3 was observed for PM2.5, which decreased to 15.3 ± 2.51 μg/m3 during the pandemic due to a reduction in industrial and anthropogenic emissions. Additionally, prior to the pandemic, PM1.0 had a contribution rate of 79% to PM2.5, which changed to 89% during the pandemic. Similarly, BaPeq values in PM2.5 exhibited a comparable trend, with PM1.0 contributing 86% and 65% respectively. In both periods, the OC/EC ratios for PM1.0 and PM2.5 were above 2, due to secondary organic compounds. The incremental lifetime cancer risk (ILCR) of PAHs in PM2.5 decreased by 4.03 × 10-5 during the pandemic, with PM1.0 contributing 73% due to reduced anthropogenic activities.

Rheological Studies on Optimizing the Sinter Mix Granulation Mechanism to Sustain Productivity

Granulation of the sinter mix is an important step in the iron ore sintering process. This article presents the results of various studies conducted to understand the rheological aspects and methods implemented in industrial‐scale sinter plants to sustain productivity over the last decade. The intergranular bonding material in the mixing and nodulizing drum is characterized to understand its influence on the granulation. Calcined lime, when increased from 20 to 40 kg t−1 of sinter, increases the granulation index and helps in achieving higher productivity. Up to 20 kg t−1, calcined dolo increases productivity, beyond which a decline is noticed. Lignosulfonate and polymer binders in the range of 0.2%–0.7% in the sinter mix, respectively, increase the granulation of the microfines (0.25 and 0.5 mm size). When a magnetic field is applied to water, the granulation improves. Higher electrical conductivity and lower contact angle of the recycled water are found to improve the bonding of the particles. Zeta potentials of fly ash and bentonite solution in water are positive and negative in the cases of calcined lime and calcined dolo. It is suggested to use fly ash as a binder of microfines.

Health assessment of emerging persistent organic pollutants (POPs) in PM2.5 in northern and central Taiwan

Over the last two decades, Taiwan has effectively diminished atmospheric concentrations of polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) through the adept utilization of advanced technologies and the implementation of air pollution control devices. Despite this success, there exists a dearth of data regarding the levels of other PM2.5-bound organic pollutants and their associated health risks. To address this gap, our study comprehensively investigates the spatial and seasonal variations, potential sources, and health risks of PCDD/Fs, Polychlorinated biphenyls (PCBs), and Polychlorinated naphthalene (PCNs) in Northern and Central Taiwan. Sampling collections were conducted at three specific locations, including six municipal waste incinerators in Northern Taiwan, as well as a traffic and an industrial site in Central Taiwan. As a result, the highest mean values of PM2.5 (20.3–39.6 μg/m3) were observed at traffic sites, followed by industrial sites (14.4–39.3 μg/m3), and the vicinity of the municipal waste incinerator (12.4–29.4 μg/m3). Additionally, PCDD/Fs and PCBs exhibited discernible seasonal fluctuations, displaying higher concentrations in winter (7.53–11.9 and 0.09–0.12 fg I-TEQWHO/m3) and spring (7.02–13.7 and 0.11-0.16 fg I-TEQWHO/m3) compared to summer and autumn. Conversely, PCNs displayed no significant seasonal variations, with peak values observed in winter (0.05–0.10 fg I-TEQWHO/m3) and spring (0.03–0.08 fg I-TEQWHO/m3). Utilizing a Positive Matrix Factorization (PMF) model, sintering plants emerged as the predominant contributors to PCDD/Fs, constituting 77.9% of emissions. Woodchip boilers (68.3%) and municipal waste incinerators (21.0%) were identified as primary contributors to PCBs, while municipal waste incinerators (64.6%) along with a secondary copper and a copper sludge smelter (22.1%) were the principal sources of PCNs. Moreover, the study specified that individuals aged 19–70 in Northern Taiwan and those under the age of 12 years in Central Taiwan were found to have a significantly higher cancer risk, with values ranging from 9.26 x 10−9-1.12 x 10−7 and from 2.50 x 10−8-2.08 x 10−7respectively.

Local machine learning model-based multi-objective optimization for managing system interdependencies in production: A case study from the ironmaking industry

Modeling interdependencies in a production process is a vital aspect of process engineering. Being built on the fundamental understanding of the process and capturing underlying physical and chemical mechanisms, this task is traditionally carried out through first-principle modeling. However, due to various assumptions and parameter approximation, such approach sometimes struggles to accurately model process dynamics. This is partially due to the requirements for process stability in mission-critical scenarios, where it is not viable to conduct extensive experiments that would enable the development of comprehensive models, and hence, the process control is still partially dependent on the experience of the process operator. In this paper, a data-driven approach based on production data is introduced to address the challenge of discovering, understanding, and modeling interdependencies in a production process by constructing a constrained multi-objective optimization problem. The applicability of the proposed approach is demonstrated through a case study in the ironmaking industry, whereby a set of Machine Learning and causality-based methods is provided while highlighting the significance of transparency and use of domain knowledge in the development of data-driven models. Based on the real data from a Sintering plant, interdependencies are quantified between five key process parameters, which, when supplemented with other control parameters, result in a higher overall process output leading to reductions in operational costs and environmental impact. Such approach shows potential for applications in a broader context across other fields of science and engineering, where it can be used to improve the discovery of interdependencies in complex real-world industrial settings.

Influence of Aging Time on Filtration Performance of P84 Filter Media with Seam.

Although the area with the seam is approximately 4% of the total area of an industrial filter bag, a more extensive investigation of the influence of this region on surface filtration is necessary since the small seam holes can be a conduit for the passage of fine particles even after a certain time of use of the filter bag. Therefore, this work aimed to assess the influence of aging time on the filtration performance of P84 filter bags (samples without and with seam) used in an industrial bag filter, regarding tensile mechanical properties, air permeability, fractional separation efficiency, and filtration cycles. The particulate matter applied (sinter dust) to evaluate the efficiency and to perform the cycles was collected in the hoppers of an industrial bag filter installed in the primary dedusting system of a sinter plant in the steel industry. The results showed that the filter bag aged for 10 months presented a fractional separation efficiency of almost 100%, even for the samples with a seam, suggesting that the seam holes were sealed by the powder in the industrial installation. As for the tensile mechanical properties, the tests showed that the aging of the filter bag caused a reduction in the tensile strength of the filter medium. With respect to air permeability and filtration cycles, the longer the aging time of the filter bag, the more similar was the filtration performance of the samples without and with seam.

Quantifying particulate matter optical properties and flow rate in industrial stack plumes from the PRISMA hyperspectral imager

Abstract. Industrial activities such as metallurgy, coal and oil combustion, cement production, and petrochemistry release aerosol particles into the atmosphere. We propose analyzing the aerosol composition of plumes emitted by different industrial stacks using PRISMA (PRecursore IperSpettrale della Missione Applicativa) satellite hyperspectral observations. Three industrial sites have been observed: a coal-fired power plant in Matla, South Africa (imaged on 25 September 2021); a steel plant in Wuhan, China (24 March 2021); and gas flaring at an oil extraction site in Hassi Messaoud, Algeria (9 July 2021). Below-plume surface reflectances are constrained using a combination of PRISMA and Sentinel-2/MSI images. Radiative transfer simulations are performed for each scene including the surface, background atmosphere, and plume optical properties. The plume aerosol optical thickness (AOT), particle radius, volume of coarse-mode aerosol, and soot are then retrieved within the plumes following an optimal estimation framework. The mean plume retrieved AOT at 500 nm ranges between 0.27 and 1.27 and the median radius between 0.10 and 0.12 µm. We found a volume fraction of soot of 3.6 % and 10.4 % in the sinter plant and coal-fired plant plumes, respectively. The mass flow rate of particulate matter at a point source estimated by an integrated mass enhancement method varies from 840 ± 155 g s−1 for the flaring emission to 1348 ± 570 g s−1 at the coal-fired plant.

A novel approach to the extraction and analysis of dioxins and furans sampled onto Amberlite XAD-2 sorbent.

Despite the efficacy of strong emission control plans that have been implemented the last few decades, polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) may still be released from anthropogenic sources such as sinter plants, and municipal and hazardous waste incinerators. Monitoring for PCDDs and PCDFs in gaseous emissions from such facilities is important due to the acute toxicity of these compounds even at trace levels. Currently, most of these samples from the African continent are being analysed abroad at high cost, with the direct consequence that the number of measurements are kept to a minimum. In this context, we developed a more affordable analytical approach for the measurement of PCDD/Fs sampled onto Amberlite XAD-2 sorbent, which relies on a novel extraction, clean-up, and analysis method with the aim of reducing both the cost and the complexity of standard methods while maintaining high quality results. A simple, sequential, 3 hour end-over-end tumbling extraction procedure was developed employing acetone : n-hexane (1 : 9) as extraction solvent. This was combined with a dimethyl sulfoxide (DMSO) clean-up to remove aliphatic interferences, prior to direct analysis by gas chromatography triple quadrupole mass spectrometry. The Unites States Environmental Protection Agency Method 23, in contrast, requires a 16 hour Soxhlet extraction with toluene and multiple column chromatography steps. The end-over-end tumbling extraction yielded an average recovery of 79% for PCDD/Fs usually monitored in gaseous samples, whilst an average recovery of 89% was achieved for the DMSO clean-up procedure. In addition, an overall average recovery of 78% and a Z-score of -1.1 was obtained using the developed method for the proficiency testing of a solid reference material, proving the method is fit for purpose. It was then successfully applied to the analysis of air emissions from a medical waste incinerator, which further showed that the alternative approach may deliver quality, fast, and cost-effective analysis of gaseous PCDD/Fs sampled onto Amberlite XAD-2 sorbent in a developing country context.

Improving the efficiency of the preparation of agglomeration charge

Improving the efficiency of averaging of agglomeration charges containing finely dispersed materials and reducing fluctuations in the chemical composition of the agglomerate is an actual topic since sintering plants do not have enough equipment for the complete preparation of the agglomeration charge, namely averaging. In addition, the supply of finely dispersed components of iron ore concentrate and iron-containing sludge to the warehouse for averaging and the processes of stack formation and disassembly are accompanied by disorganized structure formation. Solving this issue will improve agglomerate quality and increase agglomeration machines' productivity. A method of preparing agglomeration charge is proposed. This method involves averaging the mixture after equalizing its granulometric composition, which minimizes material segregation during stack formation and disassembly. The leveling of the granulometric composition of the mixture is carried out by processing it in mixers at natural humidity, which leads to the destruction of locally over-moistened micro volumes of sludge and concentrate and finishing the mixture at optimal humidity, which contributes to the preferential formation of granules of class 1.6...10.0 mm. A component for crushing is added to the mixture in the amount of 10 ...40 % of the weight of the mixture to intensify the process of crushing in the mixer. Granulation of the charge before averaging and storage in the warehouse contributes to eliminating the phenomenon of caking, the unorganized formation of macrostructures in the process of loading the material. This ultimately improves the quality of the agglomerate in terms of strength indicators. The method will reduce fluctuations in the agglomerate's chemical composition in terms of iron content and basicity while increasing the productivity of sinter machines and strengthening the heat. Taken together, this allows us to conclude about its feasibility and the possibility of its introduction into industry.

Multisource Information Fusion for Autoformer: Soft Sensor Modeling of FeO Content in Iron Ore Sintering Process

As a key thermal-state indicator of the iron ore sintering process, the content of ferrous oxide (FeO) in the finished sinter is directly related to product quality. Based on the massive data of sintering process, the data-driven soft sensor model provides a good choice for real-time FeO content detection. However, the complex characteristics of the data, including dynamics, nonlinearity, and multi-source heterogeneity, are still the main obstacles to improving the modeling accuracy. To solve this problem, a multi-source information fusion Autoformer (MIF-Autoformer) model is introduced in this paper. Firstly, feature-level information fusion and data-level information fusion are implemented based on the MIF strategy. Then, the comprehensive information of the sintering process is fed to the downstream Autoformer model in a serial manner, which not only improves the information capacity, but also provides additional prior information about the FeO content grade. This is helpful for Autoformer to capture the complex temporal distributions in the sintering process. Finally, the proposed model is applied to a real sintering plant. Experimental results show that the hybrid image features provided by the MIF strategy have a general optimization effect on different competitive models, and MIF-Autoformer exhibits the lowest prediction error on the test set.

Long-term simulation of an industrial coke breeze grinding circuit

One important application of rod milling is in size reduction of coke breeze, which is used as solid combustible in iron ore sintering plants. The work applies modeling and simulation of an industrial circuit comprised of a flip-flow screen and a rod mill to predict the circuit response in long-term operation, following the strategy used in the plant of replacing the rod charge only when it reaches the end of its life. Initially, the model for rod wear has been calibrated and the mill fillings estimated. Then the mill model has been validated with data from several industrial surveys, showing good agreement between the two. A long-term (approximately three-month) pseudo-dynamic simulation was then carried out to mimic the strategy normally used in plant operation. Additional simulations were then carried out to compare different scenarios of operation, demonstrating the benefit of increasing the rod charge and diameter, in particular when associated with operation of the mill at lower speed in the beginning of the charge life and progressive increase thereafter, besides partially replacing worn rods in their midlife. For instance, simulations showed that an increase in initial mill filling from 15 to 20 %, progressive increase in fraction of critical speed from 0.40 to 0.65 in contrast to operation at constant speed and gradual reduction of throughput from 60.0 to 40.2 t/h resulted in 56 % increase in charge lifetime, 35 % reduction in variability in product quality and 12 % reduction in cost of operation per ton of coke breeze produced.

Deep Learning Based Feature Selection and Ensemble Learning for Sintering State Recognition.

Sintering is a commonly used agglomeration process to prepare iron ore fines for blast furnace. The quality of sinter significantly impacts the blast furnace ironmaking process. In the vast majority of sintering plants, the judgment of sintering quality still relies on the intuitive observation of the cross section at sintering machine tail by operators, which is susceptible to the external environment and the experience of operators. In this paper, we propose a new sintering state recognition method using deep learning based feature selection and ensemble learning. First, features from the infrared thermal images of sinter cross section at the tail of the sinterer are extracted based on ResNeXt. Then, to eliminate the irrelevant, redundant and noisy features, an efficient feature selection method based on binary state transition algorithm (BSTA) is proposed to find the truly useful features. Subsequently, an ensemble learning (EL) method based on group decision making (GDM) is proposed to recognize the sintering states. Novel combination strategies considering the varying performance of the base learners are designed to further improve recognition accuracy. Industrial experiments conducted at a steel plant verify the effectiveness and superiority of the proposed method.

A new disposal method for white mud: Replacing limestone in iron ore sintering

The pulp production process generates a CaCO3-rich solid waste known as white mud (WM), and its improper disposal is a cause for global concern. The present study investigates the composition, microstructure, and thermal decomposition characteristics of WM and proposes a strategy for replacing limestone with WM for iron ore sintering. Granulation and sinter pot tests were performed to evaluate the influence of added WM on the granulation and sintering processes. We assess the feasibility of using WM as a flux and discuss the mechanism through which WM affects the mineral phase and strength of the sinter based on metallographic and micropore observations. The results indicate that the sintering rate remains stable after replacing 50% of the limestone with WM via moisture control, and the quality and production indicators of the sinter do not change. Moreover, the mineral phase and microporosity remain similar to the basic case without WM, and the comprehensive index decreased by only 5.5%. Overall, this study demonstrates that it is feasible to replace 50% of limestone with WM in industrial sintering plants, which could significantly increase our WM disposal capacity and bring additional economic benefits.

Reduction of Nitrogen Oxides by Calcium Ferrites in an Iron Ore Sintering Plant

Reduction of Nitrogen Oxides by Calcium Ferrites in an Iron Ore Sintering Plant