Influence of Optimization Algorithm on Airfoil Shape Optimization of Aircraft Wings

Abstract

Computational fluid dynamics (CFD) is one of the computer-based solution methods which are more widely employed in aerospace engineering. The computational power and time required to carry out the analysis increases as the fidelity of the analysis increases. Aerodynamic shape optimization has become a vital part of aircraft design in the recent years. The Method of search algorithms or optimization algorithms is one of the most important parameters which will strongly influence the fidelity of the solution during an aerodynamic shape optimization problem. Nowadays various optimization methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) etc., are more widely employed to solve the aerodynamic shape optimization problems. In addition to the optimization method, the geometry parameterisation becomes an important factor to be considered during the aerodynamic shape optimization process. Generally if we want to optimize an airfoil we have to describe the airfoil and for that, we need to have at least hundred points of x and y co-ordinates. It is really difficult to optimize airfoils with this large number of co-ordinates. Nowadays many different schemes of parameter sets are used to describe general airfoil such as B-spline, Hicks- Henne Bump function, PARSEC etc. The main goal of these parameterization schemes is to reduce the number of needed parameters as few as possible while controlling the important aerodynamic features effectively. Here the work has been done on the PARSEC geometry representation method. The objective of this work is to introduce the knowledge of describing general airfoil using twelve parameters by representing its shape as a polynomial function. And also we have introduced the concept of Particle Swarm optimization Algorithm which is one kind of Non-Traditional Optimization technique to optimize the aerodynamic characteristics of a general airfoil for specific conditions. An aerodynamic shape optimization problem is formulated for NACA 2411 airfoil and solved using the method of Particle Swarm Optimization for 5.0 deg angle of attack. A MATLAB program has been developed to implement PARSEC, Panel Technique, and PSO Algorithm. This program has been tested for a standard NACA 2411 airfoil and optimized to improve its coefficient of lift. Pressure distribution and co-efficient of lift for airfoil geometries has been calculated using panel method. NACA 2411 airfoil has been generated using PARSEC and optimized for 5.0 deg angle of attack using PSO Algorithm. The results show that the particle swarm optimization scheme is more effective in finding the optimum solution among the various possible solutions.

Multi-network collaborative lift-drag ratio prediction and airfoil optimization based on residual network and generative adversarial network

“…The airfoil structure significantly influences the energy efficiency of wind power generation Sharma, Gupta, Pandey, Sharma, & Mishra (2021) . Due to the high cost of CFD calculation Koziel & Leifsson (2013) , - The aerodynamic performance optimization Bedon et al (2016) ; Chen and Li (2019) ; Kallath et al (2021) ; Mukesh et al (2012) ; Saleem and Kim (2020) ; Tang et al (2017) and robustness optimization Reis et al (2019) of Airfoil Based on CFD are limited. Therefore, optimizing the efficiency of airfoil structures has been a focus of research community.…”

“…Mukesh et al studied the performance of different optimization algorithms, such as GA and PSO based on CFD. The authors concluded that as compared with other methods, the PSO method has a greater ability to find the global optimal value Mukesh et al (2012) . Chen et al further fused the GA and PSO to optimize the NACA0018 wing sail and obtained a larger thrust than the original wing Chen and Li (2019) .…”

“…PARSEC parameterization has been applied in several studies ( Mukesh et al, 2012 ; Da et al, 2017 , MANAS S. K., 2008). The research by DA et al and MANAS is based on the PSO algorithm for airfoil optimization.…”

“…The research by DA et al and MANAS is based on the PSO algorithm for airfoil optimization. Based on the PARSEC parameterization method, Mukesh et al (Mukesh, R et al, 2012) compared the optimization results of the Panel Technique and the PSO algorithm. They concluded that the PSO algorithm could find the optimal solution more effectively.…”