Aerodynamic optimization for hypersonic airfoil design based on local piston theory

Aerodynamic optimization by numerical methods has always been of engineering interest with the great advancement of computers. This paper presents a highly efficient aerodynamic optimization method for hypersonic airfoil based on local piston theory. In the optimization procedure, local piston theory has been employed for unsteady pressure perturbations caused by geometrical modification from the baseline. Because unsteady pressure perturbations at hypersonic conditions could be calculated by local piston theory based on initial flow field results in the optimum searching process, only one steady-state solution is required. Therefore, the optimization method described in this paper is an extremely efficient technique which combines the advantages of steady CFD and the local piston theory and thus with zero-computational cost in optimum search process. In order to investigate the applicability of local piston theory on aerodynamic prediction for blunt leading edge shape, single-objective and multi-objective optimizations for NACA0008 at various Mach numbers have been conducted with the objective to improve the lift-to-drag ratio and moment coefficient, and the optimization results have been validated by CFD and it is concluded that the optimization method based on local piston theory could be used in a wide Mach range while keeping a satisfactory efficiency and accuracy, therefore it can be employed for hypersonic airfoil optimization in the process of initial design in the engineering application.

[1]  D. Sarhaddi,et al.  From Piston Theory to a Unified Hypersonic-Supersonic Lifting Surface Method , 1997 .

[2]  Manas Khurana,et al.  Airfoil Optimisation by Swarm Algorithm with Mutation and Artificial Neural Networks , 2009 .

[3]  Holt Ashley,et al.  Piston Theory-A New Aerodynamic Tool for the Aeroelastician , 1956 .

[4]  Zheng-Yin Ye,et al.  Supersonic Flutter Analysis Based on a Local Piston Theory , 2009 .

[5]  Peretz P. Friedmann,et al.  Aeroelastic and Aerothermoelastic Analysis in Hypersonic Flow: Past, Present, and Future , 2011 .

[6]  A. Jahangirian,et al.  Airfoil shape parameterization for optimum Navier–Stokes design with genetic algorithm , 2007 .

[7]  Peretz P. Friedmann,et al.  Aeroelastic and Aerothermoelastic Analysis of Hypersonic Vehicles: Current Status and Future Trends , 2006 .

[8]  J. Périaux,et al.  Multicriterion Aerodynamic Shape Design Optimization and Inverse Problems Using Control Theory and Nash Games , 2007 .

[9]  Abolfazl Khalkhali,et al.  Applying evolutionary optimization on the airfoil design , 2012 .

[10]  A Samareh Jamshid,et al.  A Survey of Shape Parameterization Techniques , 1999 .

[11]  Marin D. Guenov,et al.  A Comparison of Airfoil Shape Parameterization Techniques for Early Design Optimization , 2010 .

[12]  Jack J. McNamara,et al.  Aeroelastic and Aerothermoelastic Analysis of Hypersonic Vehicles: Current Status and Future Trends , 2007 .

[13]  Raymond M. Hicks,et al.  Wing design by numerical optimization , 1977 .

[14]  Christopher Tarpley,et al.  Stability derivatives for a hypersonic caret-wing waverider , 1995 .

[15]  Andy J. Keane,et al.  A Study of Shape Parameterisation Methods for Airfoil Optimisation , 2004 .

[16]  David B. Doman,et al.  A Hypersonic Vehicle Model Developed With Piston Theory (Preprint) , 2006 .

[17]  David B. Doman,et al.  A Flexible Hypersonic Vehicle Model Developed With Piston Theory (Preprint) , 2006 .

[18]  John E. Mottershead,et al.  A review of robust optimal design and its application in dynamics , 2005 .

[19]  Xiaomin Chen,et al.  Shape optimization of airfoils in transonic flow using a multi-objective genetic algorithm , 2013 .

[20]  M. J. Lighthill,et al.  Oscillating Airfoils at High Mach Number , 1953 .

[21]  B. Kulfan Universal Parametric Geometry Representation Method , 2008 .

[22]  A. Jahangirian,et al.  Aerodynamic Optimization of Airfoils Using Adaptive Parameterization and Genetic Algorithm , 2014, J. Optim. Theory Appl..