期刊
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
卷 118, 期 -, 页码 113-124出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijmecsci.2016.09.011
关键词
Elastic wall; Magnetic field; Nanofluids; Fluid-structure interaction; Finite element method
In this study, MHD mixed convection in a CuO-nanofluid filled lid-driven cavity having an elastic side wall and volumetric heat generation is numerically investigated. The left vertical wall is moving with constant velocity in the +y direction. The left vertical wall of the cavity is maintained at constant cold temperature while the right vertical wall is at hot temperature and the other walls of the cavity are insulated. The governing equations are solved with finite element method. The Arbitrary Lagrangian-Eulerian method is used to describe the fluid motion with the elastic wall in the fluid structure interaction model. The influence of Richardson number (between 0.01 and 100), internal Rayleigh number (between 10(3) and 10(6)), Hartmann number (between 0 and 50), inclination angle of the magnetic field (between 0 and 90), Young's modulus of flexible wall (between 5 x 10(2) N/m(2) and 10(6) N/m(2)), and nanoparticle volume fraction (between 0 and 0.05) on the fluid flow and heat transfer were numerically investigated. The effect of Brownian motion on the effective thermal conductivity was taken into account. The averaged heat transfer decreases with decreasing values of Richardson number and increasing values of Hartmann number and internal Rayleigh number. Absolute value of the averaged heat transfer enhances by 14.34% and 8.83% at Richardson number of 1 and 100 and deteriorates by 6.51% at Richardson number of 0.01 for Young's modulus of the elastic wall 500 when compared to configuration for Young's modulus of 10(6). The local and averaged heat transfer enhance as the value of solid volume fraction of the nanoparticle increases and this is more effective for higher values of Richardson number where heat transfer process is effective.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据