Modeling and Optimization of Gaseous Thermal Slip Flow in Rectangular Microducts Using a Particle Swarm Optimization Algorithm

Symmetry

NawafN. Hamadneh¹  WaqarA. Khan²  Ilyas Khan³  AliS. Alsagri⁴ 

[1] Department of Basic Sciences, College of Science and Theoretical Studies, Saudi Electronic University, Riyadh 11673, Saudi Arabia;Department of Mechanical Engineering, College of Engineering, Prince Mohammad Bin Fahd University, Al Khobar 31952, Saudi Arabia;Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City 72915, Vietnam;Mechanical Engineering Department, Qassim University, Buraydah 51431, Saudi Arabia;

关键词: forced convection;    microducts;    Knudsen number;    Nusselt number;    artificial neural networks;    particle swarm optimization;   

DOI  :  10.3390/sym11040488

来源: DOAJ

【 摘 要 】

In this study, pressure-driven flow in the slip regime is investigated in rectangular microducts. In this regime, the Knudsen number lies between 0.001 and 0.1. The duct aspect ratio is taken as $0\le \epsilon \le 1$ . Rarefaction effects are introduced through the boundary conditions. The dimensionless governing equations are solved numerically using MAPLE and MATLAB is used for artificial neural network modeling. Using a MAPLE numerical solution, the shear stress and heat transfer rate are obtained. The numerical solution can be validated for the special cases when there is no slip (continuum flow), $\epsilon =0$ (parallel plates) and $\epsilon =1$ (square microducts). An artificial neural network is used to develop separate models for the shear stress and heat transfer rate. Both physical quantities are optimized using a particle swarm optimization algorithm. Using these results, the optimum values of both physical quantities are obtained in the slip regime. It is shown that the optimal values ensue for the square microducts at the beginning of the slip regime.

【 授权许可】

Unknown