Optimization of Helical Microreactors by a Genetic Algorithm Technique,Chemical Engineering & Technology

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Optimization of Helical Microreactors by a Genetic Algorithm Technique
Chemical Engineering & Technology ( IF 1.8 ) Pub Date : 2020-09-29 , DOI: 10.1002/ceat.202000301
Reza Beigzadeh ₁ , Mahtab Izadi ₂ , Masoud Rahimi ₂

Affiliation

Micromixing in coiled microreactors is attained by a higher pressure drop and more pumping power. The optimum geometries of helically coiled microreactors were determined by multiobjective optimization based on a genetic algorithm (GA). The segregation index (X_s) values of the Villermaux/Dushman reaction were measured in twelve coiled microchannels. The effects of the geometries including curvature diameter and coil pitch on the mixing performance and pressure drop were investigated. The mixing performance of the microreactors and the pressure drop were considered as the GA objectives. The optimum geometries of the studied coiled microchannels with a trade‐off between X_s and friction factors were obtained using GA‐based multiobjective optimization.

中文翻译：

遗传算法优化螺旋微反应器

通过更高的压降和更大的泵送功率，可以在螺旋式微反应器中实现微混合。通过基于遗传算法（GA）的多目标优化来确定螺旋螺旋微反应器的最佳几何形状。在12个卷曲的微通道中测量了Villermaux / Dushman反应的偏析指数（X _s）。研究了曲率直径和线圈节距等几何形状对混合性能和压降的影响。将微型反应器的混合性能和压降视为GA目标。使用基于GA的多目标优化方法，可以在X _s和摩擦系数之间进行折衷，从而获得所研究的螺旋微通道的最佳几何形状。

更新日期：2020-11-19

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