基于熔池搅拌动力学的电弧炉炼钢成分预报基础研究

终点预报与控制是电弧炉冶炼高品质特殊钢与实现智能化的关键技术。由于电弧炉炉内各区域化学反应不均衡，钢液流动对熔池内反应作用机理尚不清晰，一直未能彻底解决电弧炉炼钢成分准确预报的技术难题。随着合理供电、强化供氧与底吹等技术的采用，冶炼节奏加快，实现成分的预报更为迫切。针对国内外研究状况和本人在熔池搅拌与终点预报的前期研究工作，申请人提出了“基于熔池搅拌动力学的电弧炉炼钢成分预报”新方法，将熔池划分为“剧烈反应区”与“流动区”，采用理论计算、数值模拟、水模拟、热试实验等方法，研究氧气射流作用的剧烈反应区的选择性氧化热力学机理，探明电弧炉炼钢熔池钢液流动特征规律与传质的循环准数，分析集成化学反应的剧烈反应区熔池特征规律，确定整个熔池内各元素成分变化规律，建立基于熔池搅拌动力学的电弧炉炼钢成分预报模型。本研究将提高电弧炉炼钢钢液成分预报准确性，为电弧炉炼钢实现智能化提供理论基础与应用方法。

End point prediction and control is the key technology to smelt high quality special steel and to realize intelligent in EAF steelmaking process. Due to uneven regional chemical reactions in bath of electric arc furnace, and the mechanism of steel flow to the reaction in molten bath is not clear, the technical problems of composition accurate prediction in EAF steelmaking have not been able to solve thoroughly. With technology of reasonable power supply, strengthening the oxygen supply and bottom blowing to be adopted, rhythm of smelting has accelerated, so end point composition prediction has become more urgent. In view of the research status at home and abroad, and prophase research work for bath stirring and end point prediction, the applicant put forward the new method “Composition prediction based on bath stirring dynamics in EAF steelmaking”. The molten pool is divided into “violent reaction area” and “flow area”. By using theoretical calculation, numerical simulation, water simulation, and hot state experiment, this topic study selective oxidation thermodynamics mechanism in the violent reaction area by oxygen jet, proven the characteristics of steel flow and the mass transfer cycle number in bath of EAF steelmaking, and study the characteristics in violent reaction area with chemical reaction, to determine the composition of the each element in the molten bath for the establishment of composition prediction model based on bath stirring dynamics in EAF steelmaking. This topic will improve accuracy of molten steel composition prediction in EAF steelmaking, providing theoretical basis and application method for intelligence of EAF steelmaking.