Enhancing the handling qualities analysis by collaborative aerodynamics surrogate modelling and aero-data fusion

In the modern aircraft design process numerical simulation is one of the key enablers. However, computational time increases exponentially with the level of fidelity of the simulation. In the EU Horizon2020 project AGILE different aircraft design analysis tools relative to different levels of fideli...

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Bibliographic Details
Published in:Progress in aerospace sciences Vol. 119; p. 100647
Main Authors: Zhang, Mengmeng, Bartoli, Nathalie, Jungo, Aidan, Lammen, Wim, Baalbergen, Erik, Voskuijl, Mark
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.11.2020
Elsevier
Subjects:
Aero-database
AGILE
Computational aerodynamics
CPACS
Engineering Sciences
Mathematics
MDO
Multi-fidelity analysis
Physics
Sampling approaches
Surrogate model repository
Surrogate-modeling
Computational aerodynamics
CPACS
Sampling approaches
Surrogate model repository
AGILE
Surrogate-modeling
MDO
Multi-fidelity analysis
Aero-database
multi-fidelity analysis
sampling approaches
Surrogate Model Repository
aero-database
computational aerodynamics
surrogate-modeling
Multidisciplinary design optimization
ISSN:0376-0421, 1873-1724
Online Access:Get full text
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Summary:In the modern aircraft design process numerical simulation is one of the key enablers. However, computational time increases exponentially with the level of fidelity of the simulation. In the EU Horizon2020 project AGILE different aircraft design analysis tools relative to different levels of fidelity are used. One of the challenges is to reduce the computational time - e.g. to facilitate an efficient optimization process - by processing the analysis data of various fidelity levels in a global surrogate model. This paper focuses on fusion of data sets via an automatic iterative process embedded in the collaborative multidisciplinary analysis (MDA) chains as applied in AGILE. Surrogate modeling techniques are applied, taking into account the optimal sampling and the corresponding fidelities of the samples. This paper will detail the different steps of the proposed collaborative approach. As a test case handling qualities analysis of the AGILE reference conventional aircraft is performed, by fusing the computed aerodynamic coefficients and derivatives. A full set of aerodynamic data computed either with different levels of fidelity or with only a low-fidelity tool has been derived and evaluated. The data set with multiple levels of fidelity significantly improved the accuracy of the flight performance analysis, especially for the transonic region in which the low fidelity aerodynamic method is not reliable. Moreover, the test case shows that by combining a collaborative surrogate modeling approach with fusion of the data sets, the fidelity of the analysis data can be significantly improved giving maximum relative prediction error less than 5% with minimal computing efforts.
ISSN:0376-0421
1873-1724
DOI:10.1016/j.paerosci.2020.100647