Optimization of Dual-Impeller Configurations in a Gas-Liquid Stirred Tank Based on Computational Fluid Dynamics and Multiobjective Evolutionary Algorithm
Optimization of Dual-Impeller Configurations in a Gas-Liquid Stirred Tank Based on Computational Fluid Dynamics and Multiobjective Evolutionary Algorithm
复制标题
基于计算流体动力学和多目标进化算法的气液搅拌槽双叶轮配置优化
DOI：
10.1021/acs.iecr.6b01660
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发表时间：
2016-08-24
影响因子：
4.2
通讯作者：
Feng, Lianfang
中科院分区：
文献类型：
--
作者：
Chen, Miaona;Wang, Jiajun;Feng, Lianfang
以总有效气含率最大、功率消耗最小为目标，提出了一种基于计算流体力学（CFD）和多目标进化算法（MOEA）的曝气池双桨优化设计策略。应用非支配排序遗传算法-II（NSGA-II）从大量的设计点构造Pareto前沿，大大减少了计算量。利用双电导探针和扭矩传感器测量局部气含率和功率消耗，对CFD模型进行了验证，并对优化设计进行了评价。采用斜凹叶盘涡轮机作为下叶轮、斜下泵式斜叶涡轮机作为上叶轮的优化设计具有最佳的气体分散性能和有效的节能效果。这种方法有可能大大提高工业搅拌反应器的效率。
An optimization strategy combining computational fluid dynamics (CFD) with multiobjective evolutionary algorithm (MOEA) for dual-impeller design in an aerated tank was proposed to maximize the overall effective gas holdup and minimize the power consumption with six geometrical variables. The nondominated sorting genetic algorithm-II (NSGA-II) was applied to construct a Pareto front from numerous design points with greatly reduced computation. The measurement of local gas holdup and power consumption by dual electric conductivity probe and torque sensor was utilized to verify the CFD model and evaluate the optimal design. The optimal design with a pitched concave blade disk turbine as the lower impeller and a down-pumping pitched blade turbine as the upper impeller exhibited the best gas dispersion performance with efficient energy savings. This approach has the potential to greatly enhance the efficiency of industrial stirred reactors.