Sajjadi H, Mansouri N, Nabavi S N, Delouei A Amiri, Atashafrooz M
Department of Mechanical Engineering, University of Bojnord, Bojnord, Iran.
Department of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran.
Sci Rep. 2024 Apr 29;14(1):9847. doi: 10.1038/s41598-024-60330-0.
In the present study, natural convection heat transfer is investigated in a porous cavity filled with Cu/water nanofluid and equipped with horizontal fins. Optimization and sensitivity analysis of the fin's geometry, porous medium and nanofluid properties to maximize heat transfer rate is the aim of this work. To achieve this purpose, a design space is created by input parameters which include length, number of fins, distance between fins, porosity, Darcy number and volumetric fraction of the nanoparticles. Several tools have been used to implement optimization methods including the Taguchi method (TM) for design points generation, sensitivity analysis of design variables by using signal-to-noise ratio (SNR) and analysis of variance (ANOVA), response surface method (RSM) for interpolation and regression by using nonparametric regression, and genetic algorithm (GA) for finding optimum design point. The double multi-relaxation time lattice Boltzmann method (MRT-LBM) is used to analyze and simulate the flow field and heat transfer in each design point. The results show that the optimal configuration leads to an average Nusselt number of 5.56. This optimal configuration is at the length of fins L/2, the number of fins 2, the distance between fins L/12, porosity 0.8, Darcy number 0.1, and the volumetric fraction of the nanoparticles 0.02. By using the SNR results, the Darcy number and the number of fins have the most and the least effect in maximizing the average Nusselt number, respectively. The ANOVA results and global sensitivity analysis (GSA) findings further validated this conclusion.
在本研究中，对充满铜/水纳米流体并装有水平翅片的多孔腔内的自然对流换热进行了研究。本工作的目的是对翅片几何形状、多孔介质和纳米流体特性进行优化和敏感性分析，以最大化传热速率。为实现这一目的，通过输入参数创建了一个设计空间，这些参数包括长度、翅片数量、翅片间距、孔隙率、达西数和纳米颗粒的体积分数。已使用多种工具来实施优化方法，包括用于生成设计点的田口方法（TM）、通过使用信噪比（SNR）和方差分析（ANOVA）对设计变量进行敏感性分析、通过使用非参数回归进行插值和回归的响应面方法（RSM）以及用于找到最佳设计点的遗传算法（GA）。采用双多松弛时间格子玻尔兹曼方法（MRT-LBM）对每个设计点的流场和传热进行分析和模拟。结果表明，最优配置导致平均努塞尔数为5.56。该最优配置为翅片长度L/2、翅片数量2、翅片间距L/12、孔隙率0.8、达西数0.1以及纳米颗粒的体积分数0.02。通过使用SNR结果，达西数和翅片数量分别对最大化平均努塞尔数具有最大和最小的影响。ANOVA结果和全局敏感性分析（GSA）结果进一步验证了这一结论。
