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首页> 美国卫生研究院文献>Nanomaterials >Configuration and Optimization of a Minichannel Using Water–Alumina Nanofluid by Non-Dominated Sorting Genetic Algorithm and Response Surface Method
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Configuration and Optimization of a Minichannel Using Water–Alumina Nanofluid by Non-Dominated Sorting Genetic Algorithm and Response Surface Method

机译：非支配排序遗传算法和响应面法的水-氧化铝纳米流体微通道构型与优化

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Nanofluids in minichannels with various configurations are applied as cooling and heating fluids. Therefore, it is essential to have an optimal design of minichannels. For this purpose, a square channel with a cylinder in the center connected to wavy fins at various concentrations of an Al O nanofluid is simulated using the finite volume method (FVM). Moreover, central composite design (CCD) is used as a method of design of experiment (DOE) to study the effects of three input variables, namely the cylinder diameter, channel width, and fin radius on the convective heat transfer and pumping power. The impacts of the linear term, together with those of the square and interactive on the response variables are determined using Pareto and main effects plots by an ANOVA. The non-dominated sorting genetic algorithm-II (NSGA-II), along with the response surface methodology (RSM) is applied to achieve the optimal configuration and nanofluid concentration. The results indicate that the effect of the channel width and cylinder diameter enhances about 21% and 18% by increasing the concentration from 0% to 5%. On the other hand, the pumping power response is not sensitive to the nanofluid concentration. Besides, the channel width has the highest and lowest effect on the heat transfer coefficient (HTC) and pumping power, respectively. The optimization for a concentration of 3% indicates that in = 500 when the geometry is optimized, the HTC enhances by almost 9%, while the pumping power increases by about 18%. In contrast, by increasing the concentration from 1% to 3%, merely an 8% enhancement in HTC is obtained, while the pumping power intensifies around 60%.
机译：具有各种配置的微通道中的纳米流体被用作冷却和加热流体。因此，有必要对微通道进行优化设计。为此，使用有限体积法（FVM）模拟了一个方形通道，该通道的中央有一个圆柱体，以各种浓度的Al O纳米流体连接到波浪状的鳍片上。此外，采用中央复合设计（CCD）作为实验设计（DOE）的方法，以研究三个输入变量，即圆柱直径，通道宽度和翅片半径对对流换热和抽气功率的影响。线性项的影响，以及平方和交互影响对响应变量的影响，使用方差分析（Pareto）和主效应图通过ANOVA确定。使用非主导的排序遗传算法-II（NSGA-II）以及响应面方法（RSM）来实现最佳配置和纳米流体浓度。结果表明，通过将浓度从0％增加到5％，通道宽度和圆柱直径的影响分别提高了约21％和18％。另一方面，泵浦功率响应对纳米流体浓度不敏感。此外，通道宽度分别对传热系数（HTC）和泵浦功率有最高和最低的影响。浓度为3％的优化表明，当优化几何形状时，在= 500中，HTC几乎提高了9％，而泵浦功率则提高了约18％。相反，通过将浓度从1％增加到3％，仅获得了8％的HTC增强，而泵浦功率却提高了60％左右。

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