Three dimensional mathematical model of the iron ore sintering process based on multiphase theory

Castro, José Adilson de; Sazaki, Yasushi; Yagi, Jun‐ichiro

doi:10.1590/s1516-14392012005000107

Cited by 40 publications

(37 citation statements)

References 17 publications

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“…Some mathematical models have been developed in order to cope with the dynamic of the sintering process in an analytical way. A first attempt has been made in (Young, 1977) while a different perspective has been developed in (Augustin et al, 1995) and (de Castro et al, 2012). A different approach based on multiple-valued logic is the core of the present paper and concepts of fuzzy sets (Zadeh, 1965), fuzzy control (Lee, 1990) (Pedrycz, 1989) (Passino and Yurkovich, 1998) and expert systems (Jackson, 1998) (Durkin, 1998) are used to develop the strategies and to build the advisory system.…”

Section: Control Strategiesmentioning

confidence: 99%

Fuzzy Control of a Sintering Plant

Vannocci

Colla

Pulito³

et al. 2014

Proceedings of the International Conference on Fuzzy Computation Theory and Applications

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Within an integrated steelwork, the industrial priorities in the automation of the sinter plant comprise stable production rate at the highest productivity level and classical control scheme may fail due to the complexity of the sinter process. The paper describes an approach exploiting a fuzzy rule-based expert system to control the charging gates of a sinter plant. Two different control strategies are presented and discussed within an innovative advisory system that supports the plant operators in the choice of the most promising action to do on each gate. Through the proposed approach the operators are supported by the system in the control of the plant: through a suitable exploitation of real-time data, the system suggests the most promising action to do, by reproducing the knowledge of the most expert operators. Thus, this approach can also be used to train new technicians before involving them in the actual plant operations. The performance of the strategies and the goodness of the system have been evaluated for long time in the sinter plant of one of the biggest integrated steelworks in Europe, namely the ILVA Taranto Works in Italy.

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Section: Control Strategiesmentioning

confidence: 99%

Fuzzy Control of a Sintering Plant

Vannocci

Colla

Pulito³

et al. 2014

Proceedings of the International Conference on Fuzzy Computation Theory and Applications

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“…Although some research on the mechanism of NOx formation and reduction during sintering has been conducted, these processes are complicated, so further research is needed. However, many studies have focused on the combustion behavior and heat transfer in iron-ore sintering, particularly the influences of fuel ratio, gas supply, coke size, limestone particle size, and different exhaust-gas cycle schemes on sintering [17][18][19][20]. Some papers have reported mathematical models and key parameters for NOx behavior in conventional sintering (CS) [21,22].…”

Section: Introductionmentioning

confidence: 99%

The Effects of Coke Parameters and Circulating Flue Gas Characteristics on NOx Emission during Flue Gas Recirculation Sintering Process

et al. 2019

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The new process of flue gas recirculation, which reduces coke consumption and reducing NOx emissions, is now extensively used. Compared with traditional sintering, the characteristics of circulating flue gas and coke parameters significantly affect the combustion atmosphere and coke combustion efficiency. Based on the actual complex process of sintering machine, this study proposes a relatively comprehensive one-dimensional, unsteady mathematical model for flue gas recirculation research. The model encompasses NOx pollutant generation and reduction, as well as SO2 generation and adsorption. We focus on the effects of cyclic flue gas characteristics on the sintering-bed temperature and NOx emissions, which are rarely studied, and provide a theoretical basis for NOx emission reduction. Simulation results show that during sintering, the fuel NOx is reduced by 50% and 10% when passing through the surface of coke particles and CO, respectively. During flue gas recirculation sintering, the increase in circulating gas O2 content, temperature, and supply-gas volume cause increased combustion efficiency of coke, reducing atmosphere, and NOx content in the circulating area; the temperature of the material layer also increases significantly and the sintering endpoint advances. During cyclic sintering, the small coke size and increased coke content increase the char-N release rate while promoting sufficient contact of NOx with the coke surface. Consequently, the NOx reduction rate increases. Compared with the conventional sintering, the designed flue gas recirculation condition saves 3.75% of coke consumption, i.e., for 1.2 kg of solid fuel per ton of sinter, the amount of flue gas treatment is reduced by 21.64% and NOx emissions is reduced by 23.59%. Moreover, without changing the existing sintering equipment, sintering capacity increases by about 5.56%.

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“…Several attempts have been made to predict the quality of the sinter product based on process mechanisms. For example, models based on multiphase theory [6] and the finite difference method [7] have been developed, which aim to comprehensively simulate the sintering process and predict various properties [8,9]. Unfortunately, due to the complex mechanisms involved in the sintering process, it is extremely challenging to develop a mechanistic model based on first principles.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Model for Energy Consumption in the Sintering Process

Wang

Qiao

Zhao

et al. 2016

Journal of Manufacturing Science and Engineering

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As environmental performance becomes increasingly important, the sintering process is receiving more attention since it consumes large amounts of energy. This paper proposes a data-driven model for sintering energy consumption, which considers both model accuracy and time efficiency. The proposed model begins with removing data anomalies using a local outlier factor (LOF) algorithm and an attribute selection module using the RReliefF method. Then, to accurately predict sintering energy consumption, an integrated predictive model is employed that uses bagging-enhanced extreme learning machine (ELM) and support vector regression (SVR) machine, combined with an entropy weight method. A case study is used to demonstrate the effectiveness of the proposed model using actual production data for a year. Results show that the proposed model outperforms other models and is computationally efficient. Optimal parameters of the LOF (1.3) and number of attributes (30) were identified. It was found that coke powder has the most significant impact on the solid energy consumption (SEC), while cooling water flow rate provides the most significant impact on the gas energy consumption (GEC) within each recorded attribute variation. Parametric analysis further revealed the relationships between energy consumption and the significant attributes mentioned above. It is suggested that the proposed model could effectively reduce the energy consumption by attaining more efficient attribute settings.

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Three dimensional mathematical model of the iron ore sintering process based on multiphase theory

Cited by 40 publications

References 17 publications

Fuzzy Control of a Sintering Plant

Fuzzy Control of a Sintering Plant

The Effects of Coke Parameters and Circulating Flue Gas Characteristics on NOx Emission during Flue Gas Recirculation Sintering Process

A Data-Driven Model for Energy Consumption in the Sintering Process

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