A numerical investigation has been performed to study the effect of eccentricity on unsteady state, laminar aiding mixed convection in a horizontal concentric and eccentric cylindrical annulus. The outer cylinder was kept at a constant temperature
while the inner cylinder was heated with constant heat flux. The study involved numerical solution of transient momentum (Navier-Stokes) and energy equation using finite difference method (FDM), where the body fitted coordinate system (BFC) was
used to generate the grid mesh for computational plane. The governing equations were transformed to the vorticity-stream function formula as for momentum equations and to the temperature and stream function for energy equation.
A computer program (Fortran 90) was built to calculate the bulk Nusselt number (Nub) after reaching steady state condition for fluid Prandtl number fixed at 0.7 (air) with radius ratio ( =2.6), Rayleigh number (Ra=200), Reynolds number (Re=50) for both concentric and eccentric cylindrical annulus with different eccentricity ratios (ε=0, 0.25, 0.50, 0.75) and angular positions (φo=0o
, 45o , 90o , 135o , 180o ).
The results show a reasonable representation to the relation between Nusselt number and (ε, φo). Generally, Nub decreased with the increase in (ε and φo). Also, results show that the best thermal performance for the inner cylinder was at the angular
position (φo=0o ) for eccentricity ratio (ε=0.25), while the maximum reduction in the rate of heat transfer for the inner cylinder was at the angular position (φo=180o) for eccentricity ratio (ε=0.75).
Comparison of the result with the previous work shows a good agreement.
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
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