A multi-fidelity simulation approach for the generation of aerodynamic data sets by computational fluid dynamics methods is discussed. Using Kriging-based surrogate modelling methods, data obtained a priori from a computationally less expensive low-fidelity model are combined with a fewer number of high-fidelity simulation data. An adaptive sampling method is used to iteratively select the high-fidelity data points in the parameter space and update the surrogate model. A description of the multi-fidelity simulation scheme is given and initial evaluations of the method for generating aerodynamic data on an aircraft configuration test case are discussed.
Implementation of an Automatic Multi-fidelity Scheme for Industrial Applications in the Cassidian SimServer Environment
Notes Numerical Fluid Mech.
2013-01-01
15 pages
Article/Chapter (Book)
Electronic Resource
English
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