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Reverse optimization algorithm of velocity uniformity in microchannels based on a simplified resistance network model
Chemical Engineering Science ( IF 4.1 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.ces.2020.115655
Chao Li , Pingnan Huang , Minqiang Pan

Abstract Velocity distribution plays an important role on the performances of microchannel reactors. In order to obtain an ideal velocity distribution among microchannels, a reverse optimization algorithm is proposed based on a simplified resistance network model, in which the relationship between the pressure drop and resistance is established, and the relationship between the flow rate and the channel velocity is also provided. The reverse optimization algorithm was developed based on the assumption of equal velocity values in all microchannels. Some structural parameters are set as unknown quantities and then optimized. In this work, microchannel width and manifold shapes are selected for optimization by using the reverse optimization algorithm. The results indicate that the non-equal microchannel width (NEMW) model can achieve more uniform velocity distribution than the corresponding equal microchannel width (EMW) model. The non-linear manifold structure (NLMS) can also present relatively uniform velocity distribution, but relatively poor velocity uniformity of microchannels compared to the NEMW model. Considering the requirement of practical application, a mass calculation algorithm is proposed to optimize the structural parameters in a certain range. However, the computing time of this algorithm is too large.

中文翻译:

基于简化阻力网络模型的微通道速度均匀性逆向优化算法

摘要 速度分布对微通道反应器的性能有重要影响。为了获得理想的微通道间速度分布,提出了一种基于简化阻力网络模型的逆向优化算法,其中建立压降与阻力的关系,流量与通道速度的关系为还提供。反向优化算法是基于所有微通道中速度值相等的假设而开发的。一些结构参数设置为未知量,然后进行优化。在这项工作中,通过使用逆向优化算法选择微通道宽度和流形形状进行优化。结果表明,非等微通道宽度 (NEMW) 模型可以实现比相应的等微通道宽度 (EMW) 模型更均匀的速度分布。非线性流形结构 (NLMS) 也可以呈现相对均匀的速度分布,但与 NEMW 模型相比,微通道的速度均匀性相对较差。考虑到实际应用的需要,提出了一种质量计算算法,在一定范围内优化结构参数。但是,该算法的计算时间过大。考虑到实际应用的需要,提出了一种质量计算算法,在一定范围内优化结构参数。但是,该算法的计算时间过大。考虑到实际应用的需要,提出了一种质量计算算法,在一定范围内优化结构参数。但是,该算法的计算时间过大。
更新日期:2020-08-01
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