PARAMETRIC OPTIMIZATION OF INCOMPRESSIBLE NAVIER–STOKES FLOW USING RESPONSE SURFACE METHODOLOGY

Abstract

Optimization in incompressible fluid flow is a vital activity towards maximizing the aerodynamic performance and energy efficiency in a rich field of engineering systems, such as aerodynamics, HVAC networks and pipeline transport. The current paper explores the parametric optimization of incompressible Navier Stokes flow by using Response Surface Methodology (RSM). The main aim was to analyze the effect of the important design parameters as well as to determine the optimum designs that reduce the drag coefficient, the intensity of turbulence and pressure loss in the flow domain. The benchmark flow behavior and performance measures were first determined by making a baseline configuration. Response-surface models were then developed to manifest the correlation between input variables, which are the angle of the wedge, the coefficient of suction, and the concentration of nanoparticles, and the responses of the system. The optimization process produced an adjusted design which significantly enhanced the system performance compared to the baseline: the drag coefficient was reduced by about 23%, the turbulence intensity was also reduced by almost 16%, and the pressure loss was also minimized by around 14. The results show an increase in the flow stability, less energy dissipation and increased fluid transport efficiency. The formulated response-surface models had a high level of predictive power and coefficient of determination was above 0.95 in all the assessed responses. The interaction effects of the design variables between the contour plots and response-surface visualizations through graphical analyses helped to confirm the correlation. The findings prove the fact that RSM is an effective analysis tool used to investigate the complicated fluid mechanics systems and to determine the best design parameters that can be used in order to enhance the aerodynamic performance.