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Modeling and Optimisation of Gas Stirred Ladle Systems

机译:气体搅拌钢包系统的建模与优化

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Experiments were carried out to measure mixing time and slag eye area in two different water model ladles with gas injection nozzle located at the mid bath radius position. Within the range of experimental conditions studied, the following correlations (in SI unit), for 95% mixing time and slag eye area, were found to work satisfactorily:In the above equations, Q is the gas flow rate (corrected to mean height and temperature of the liquid)(m~(3)/s), L is the liquid depth (m), R is the vessel radius (m), ΔL is the slag layer thickness (m), υ _(s) is the kinematic viscosity (m~(2)/s) of the upper phase, ρ _(L) is the bulk liquid density (kg/m~(3)), τ _(mix,95%) is the mixing time (s), A_(es) is the slag eye area (m~(2)), U_(P) is the average plume rise velocity (m/s), g is the gravitational acceleration (m/s~(2)) and Δρ is the metal-slag density differential (kg/m~(3)). Based on the above and a set of four different bounds on (i) specific energy input rate, (ii) ladle aspect ratio, (iii) amount of liquid in ladle and (iv) slag layer thickness, a multi-objective, constrained optimization problem was formulated to investigate inert gas injection in steelmaking ladles. To this end, a Genetic Algorithm based optimisation procedure embodied in MATLAB? was applied. Due to the conflicting nature of the objective functions, a Pareto optimal front, comprising many optimal solutions resulted from which the desirable range of operating parameters was identified. Present study has also indicated that desirable optimal operating conditions are likely to be a function of the location of the porous plug in a ladle. Finally, for the sake of validation, three arbitrarily chosen experimental conditions were evaluated against the relevant Pareto front and it is shown that the chosen conditions are, by and large, sub-optimal.
机译:进行了实验,以测量两个不同水模型钢包中的混合时间和渣眼面积,其中气体喷嘴位于中浴半径位置。在所研究的实验条件范围内,对于95%的混合时间和炉渣眼面积,以下相关性(以SI单位表示)令人满意地起作用:在上述等式中,Q为气体流速(校正为平均高度和液体温度)(m〜(3)/ s),L是液体深度(m),R是容器半径(m),ΔL是炉渣层厚度(m),υ_(s )是上相的运动粘度(m〜(2)/ s),ρ_(L)是堆积液体密度(kg / m〜(3)),τ_(mix, 95%)是混合时间(s),A_(es)是渣眼面积(m〜(2)),U_(P)是平均羽流上升速度(m / s),g是重力加速度( m / s〜(2)),Δρ是金属渣密度差(kg / m〜(3))。基于以上内容以及关于(i)比能量输入速率,(ii)钢包长宽比,(iii)钢包中的液体量和(iv)矿渣层厚度的四个不同范围的集合,多目标约束优化为了研究炼钢钢包中的惰性气体注入问题,提出了一个问题。为此,在MATLAB?中实现了一种基于遗传算法的优化程序。已应用。由于目标函数的冲突性质,产生了包含许多最优解的帕累托最优阵线,由此确定了所需的运行参数范围。本研究还表明,理想的最佳操作条件可能是钢包中多孔塞位置的函数。最后,出于验证的目的,针对相关的帕累托前沿评估了三个任意选择的实验条件,结果表明,选择的条件总体上是次优的。

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