Implementation of an Automatic Multi-fidelity Scheme for Industrial Applications in the Cassidian SimServer Environment

摘要

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.