Efficient Modelling of a Nonlinear Gust Loads Process for Uncertainty Quantification of Highly Flexible Aircraft

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

An efficient gust loads process is presented which can predict worst case loads on a highly flexible aircraft, for use in uncertainty quantification. This process generates a neural network surrogate model of an aeroelastic system using linearised system equations to rapidly determine worst gust cases, including the capability to model atypical gust excitations. The surrogate model is used to produce a reduced set of identified gust cases which cause the largest loads; these cases are then run in the nonlinear code. Uncertainty quantification of this gust process is carried out using polynomial chaos expansion (PCE) techniques, considering uncertain structural properties. Convergence studies of the gust
loads using PCE indicate significantly fewer samples are required than would be for a Monte Carlo simulation. It is demonstrated how oblique gusts exceed the loads envelope from a traditional gust process, justifying the need to consider alternative gust excitations, but interestingly for the particular test case in this work, uncertain structural properties can be seen to have little effect on the uncertainty of the static g and gust loads.
Original languageEnglish
Title of host publication59th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc. (AIAA)
ChapterAIAA 2018-1681
Number of pages15
ISBN (Electronic)9781624105326
DOIs
Publication statusPublished - 8 Jan 2018
EventAIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, AIAA SciTech Forum - Gaylord Palms , Kissimmee, United States
Duration: 8 Jan 201812 Jan 2018

Conference

ConferenceAIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, AIAA SciTech Forum
Abbreviated titleSciTech 2018
CountryUnited States
CityKissimmee
Period8/01/1812/01/18

Keywords

  • aerogust

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  • Projects

    AEROGUST

    Gaitonde, A. L., Cooper, J. E., Jones, D. P., Cook, R. G. & Wales, C. J. A.

    1/05/1530/09/18

    Project: Research, Parent

    Cite this

    Cook, R., Wales, C., Gaitonde, A., Jones, D., & Cooper, J. (2018). Efficient Modelling of a Nonlinear Gust Loads Process for Uncertainty Quantification of Highly Flexible Aircraft. In 59th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference American Institute of Aeronautics and Astronautics Inc. (AIAA). https://doi.org/10.2514/6.2018-1681