Neural network-based aeroelastic system identification for predicting flutter of high flexibility wi...
Neural network-based aeroelastic system identification for predicting flutter of high flexibility wings
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Author / Creator
Guo, Qing , Li, Xiaoqiang , Zhou, Zhijie , Ma, Dexiao and Wang, Yuzhuo
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publisher
London: Nature Publishing Group UK
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Contents
Flutter is an extremely significant academic topic in both aerodynamics and aircraft design. Since flutter can cause multiple types of phenomena including bifurcation, period doubling, and chaos, it becomes one of the most unpredictable instability phenomena. The complexity of modeling aeroelasticity of high flexibility wings will be substantially...
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Full title
Neural network-based aeroelastic system identification for predicting flutter of high flexibility wings
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TN_cdi_doaj_primary_oai_doaj_org_article_1b381f759ad041428a1c5a90fa9d7c9a
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1b381f759ad041428a1c5a90fa9d7c9a
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-024-82573-7
