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

被引:7
|
作者
Hamadneh, Nawaf N. [1 ]
Khan, Waqar A. [2 ]
Khan, Ilyas [3 ]
Alsagri, Ali S. [4 ]
机构
[1] Saudi Elect Univ, Coll Sci & Theoret Studies, Dept Basic Sci, Riyadh 11673, Saudi Arabia
[2] Prince Mohammad Bin Fahd Univ, Coll Engn, Dept Mech Engn, Al Khobar 31952, Saudi Arabia
[3] Ton Duc Thang Univ, Fac Math & Stat, Ho Chi Minh City 72915, Vietnam
[4] Qassim Univ, Mech Engn Dept, Buraydah 51431, Saudi Arabia
来源
SYMMETRY-BASEL | 2019年 / 11卷 / 04期
关键词
forced convection; microducts; Knudsen number; Nusselt number; artificial neural networks; particle swarm optimization; HEAT-TRANSFER CHARACTERISTICS; FORCED-CONVECTION; CONSTANT; MICROCHANNELS; ARBITRARY;
D O I
10.3390/sym11040488
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
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 epsilon 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.
引用
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页数:13
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