11th International Symposium on High Temperature Metallurgical Processing: Ironmaking and Steelmaking
Sponsored by: TMS Extraction and Processing Division, TMS: Pyrometallurgy Committee
Program Organizers: Zhiwei Peng, Central South University; Jiann-Yang Hwang, Michigan Technological University; Jerome Downey, Montana Technological University; Dean Gregurek, RHI Magnesita; Baojun Zhao, Jiangxi University of Science and Technology; Onuralp Yucel, Istanbul Technical University; Ender Keskinkilic, Atilim University; Tao Jiang, Central South University; Jesse White, Kanthal AB; Morsi Mahmoud, King Fahd University Of Petroleum And Minerals
Thursday 2:00 PM
February 27, 2020
Room: 16A
Location: San Diego Convention Ctr
Session Chair: Onuralp Yücel, Istanbul Technical University; Zhongliang Tian, Central South University
2:00 PM Introductory Comments
2:15 PM
Optimization of Process Parameters for the Synthesis of Mo2C on an Activated Carbon Matrix: Grant Wallace1; Jerome Downey1; Jannette Chorney1; Katie Schumacher1; 1Montana Technological University
Commercial production of carbide materials is often associated with high energy costs due to the high temperatures and long milling times required to produce a powder carbide product. A process for synthesizing Mo2C was developed to reduce carburization temperatures and product particle size. Precursor material, produced by adsorbing molybdate anions onto activated carbon, was carburized under a reducing gas atmosphere to produce Mo2C at temperatures below 800°C. Molybdenum adsorption was measured using inductively coupled plasma spectroscopy, and carburization products were characterized using X-ray diffraction and scanning electron microscopy. Response surface analyses were used to mathematically model the adsorption and carburization processes and to determine optimal parameters for Mo-loading and Mo2C synthesis. The effects of temperature, time, pH, and initial Mo concentration were used to model adsorption behavior while the carburization process was modelled using the effects of temperature, reaction time, and reducing gas atmosphere on the synthesis of Mo2C.
2:35 PM
FactSage-based Design Calculations for the Production of High Carbon Ferromanganese on Pilot-scale: Joalet Steenkamp1; 1MINTEK
The EU-funded PreMa project investigates the potential for a preheatingstage to reduce the electrical energy requirement and CO2 emissions produced, during the production of high carbon ferromanganese in a submerged arc furnace. A pilot-scale campaign will be conducted at MINTEK in South Africa to demonstrate the potential effect of preheating on furnace operation. For the pilot-scale campaign, the design of the process flowsheet and sizing of the furnace and ancillary equipment, were based on predictive mass and energy balance calculations. FactSage thermodynamic software and Microsoft Excel were utilised. The paper reports on the method applied and results obtained.
2:55 PM Cancelled
Influences of Li2O on the Properties of Ultrahigh-basicity Mold Fluxes for Continuous Casting of Peritectic Steel: Min Li1; Yuan Bing Wu1; Sheng Ping He1; Qiang Qiang Wang1; Qian Wang1; 1Chong Qing University
The ultrahigh-basicity(R=1.75) mold flux has been proved to be effective in coordinating heat transfer and lubrication during continuous casting of peritectic steel in industry，while some mechanisms still need further in-depth studies. The effects of Li2O content on the properties of ultrahigh-basicity mold flux were systematically investigated. Main results indicated that as Li2O content raised from 0.8% to 2.4%, the viscosity at 1573 K first increased and then decreased, reaching the peak (0.148Pa•s) with 2.0% Li2O. Meanwhile, the break temperature dropped from 1484 K to 1435 K. The initial crystallization temperature, which was measured by an in-house apparatus, could decline by approximately 100 K with 2.4% Li2O addition while the crystallization rate represented an increasing trend except for the case with 2.0% Li2O. This study enhances the understanding of specified mold flux for peritectic steel.
3:15 PM Cancelled
Effect of Refining Slag Composition on the Cleanliness of 25Cr2Ni4MoV Rotor Steel: Chao Zhuo1; Yimin Zhang1; Yanhui Sun1; Ruimei Chen1; Sicheng Song1; 1University of Science and Technology Beijing
The effect of different refining slag components on the cleanliness of 25Cr2Ni4MoV turbine rotor steel was studied through four industrial experiments. It is found that less total oxygen, dissolved oxygen, inclusion quantity and smaller inclusion size could be obtained with a basicity of the refining slag between 3 and 4 and a C/A ratio between 7 and 10. FactSage7.0 was used to study the influence of slag composition on dissolved oxygen in molten steel and Al2O3 inclusion adsorption. The results reveal that high basicity is beneficial to reduce dissolved oxygen in molten steel, and less Al2O3 inclusions exist with high basicity and high C/A. Then, the evolution of typical inclusions in the refining process was discussed. Next, The physicochemical parameters of refining slag were analyzed, the viscosity and melting point of the four groups of refining slag showed that the addition of SiO2 and Al2O3 in the slag can reduce the amount of CaF2. Finally, the influence of the composition of refining slag on the lining erosion was investigated.
3:35 PM Break
3:50 PM Cancelled
Prediction Model of End-point Molten Steel Temperature in RH Refining Based on PCA-CBR: Maoqiang Gu1; Anjun Xu1; Dongfeng He1; Hongbing Wang1; Kai Feng1; 1University of Science and Technology Beijing
In this paper, the endpoint temperature prediction model of molten steel in RH refining, based on principal component analysis (PCA) and case-based reasoning (CBR), is established for the control precision of endpoint molten steel temperature in RH refining. Six principal components are extracted from eleven factors influencing molten steel temperature by PCA, which are taken as the PCA_CBR model input to construct the corresponding model. The precision of the model is verified by the actual production data of a steel plant, and compared with the prediction precision of conventional CBR models as well as the BP neural network model. The results show that the precision of the model based on PCA-CBR reaches 69.67%, 83.67% and 97% when its prediction error is in the range of [-5, 5], [-7, 7] and [-10, 10], respectively. Therefore, the model can predict the endpoint temperature of molten steel in RH refining more precisely.
4:10 PM Cancelled
Numerical Simulation and Optimization of Temperature Field in the Baking of RH Vessel: Fei Yuan1; Peiling Zhou2; Xiao Sun1; Shuai Deng1; 1University of Science and Technology Beijing; 2Tsinghua University
In order to optimize the baking of RH vessel, numerical simulation of gas flow, combustion and heat transfer in vacuum vessel during the baking process was conducted. The FLUENT code with finite volume and SIMPLEC methods was adopted to investigate the influence of top lance position on the temperature distribution of RH vessel. The numerical model was verified with the experimental data. Results show that the different height of RH top lance could cause significant changes of temperature distribution in vertical direction. There is an ideal and uniformity temperature distribution when the top lance height is 4.5m, which is benefited for removing the remaining solid steel in RH vessel. When the height of top lance is 5m, the bottom of the vacuum vessel and the immerge tube are in high baking temperature. The two baking schemes could be used in combination in the production process to improve the baking effect.