Aerodynamic shape optimization via non-intrusive POD-based surrogate modelling
- 1 June 2013
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 1089778X,p. 1467-1474
Abstract
A surrogate-based optimization framework is proposed to exploit a reduced order model (ROM) as surrogate evaluator in aerodynamic design based on computational fluid dynamics (CFD) methods. The model is based on the Proper Orthogonal Decomposition (POD) of an ensemble of CFD solutions. Full POD and zonal POD models performances are analysed with respect to their suitability to find the global optimum in an evolutionary optimization frame. Indeed, reduced order models are used as fitness evaluator to improve the aerodynamic performances of a two-dimensional airfoil. Finally, the performances of various surrogate-based shape optimization (SBSO) methods are compared to the efficiency of data-fit assisted optimization and to the accuracy of a plain optimization, where, instead, each aerodynamic evaluation is performed with the high-fidelity model.Keywords
This publication has 12 references indexed in Scilit:
- Towards an adaptive POD/SVD surrogate model for aeronautic designComputers & Fluids, 2011
- Universal Parametric Geometry Representation MethodJournal of Aircraft, 2008
- Dynamic Domain Decomposition and Error Correction for Reduced Order Models2003
- Investigation of non-linear projection for POD based reduced order models for Aerodynamics2001
- Reduced order models in unsteady aerodynamics1999
- Efficient Global Optimization of Expensive Black-Box FunctionsJournal of Global Optimization, 1998
- A comparison of approximation modeling techniques - Polynomial versus interpolating models1998
- Turbulence, Coherent Structures, Dynamical Systems and Symmetry1996
- Karhunen–Loève procedure for gappy dataJournal of the Optical Society of America A, 1995
- Multivariate Adaptive Regression SplinesThe Annals of Statistics, 1991