Stall Buffet Modeling using Swept Wing Flight Test Data

S. Marschalk, P.C. Luteijn, D. van Os, D.M. Pool, C.C. de Visser

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

As of April 2019, upset prevention and recovery training in flight simulation training devices is a mandatory practice for commercial and civil aircraft pilots. Aircraft stalls are a well-known upset type, therefore simulation of aircraft stall behavior is required. A key characteristic of stalls is the stall buffet, which in current stall models is still insufficiently modeled. In this research, a new methodology to more accurately model stall buffet behavior derived from swept wing flight test data is presented. Buffet effects occur after exceeding the critical angle of attack, with an aircraft type-specific buffet onset duration to fully develop the maximum buffet intensity. The buffet transient behavior is modeled with a frequency response fit and a multivariate second-order polynomial to capture aircraft eigenmode-shape frequencies and state dependent buffet intensity, respectively. Aircraft recovery and thus receding buffet effects occur as the angle of attack starts increasing again after the initial recovery dip, which is used as buffet offset scheduling parameter. Generalization of the results was shown with the validation of data set of a straight-wing aircraft, which indicates a step towards a more generic stall buffet model methodology.
Original languageEnglish
Title of host publicationAIAA Scitech 2021 Forum
Subtitle of host publication11–15 & 19–21 January 2021, Virtual Event
PublisherAmerican Institute of Aeronautics and Astronautics Inc. (AIAA)
Pages1-18
Number of pages18
ISBN (Electronic)978-1-62410-609-5
DOIs
Publication statusPublished - 2021
EventAIAA Scitech 2021 Forum - Virtual/online event due to COVID-19
Duration: 11 Jan 202121 Jan 2021

Publication series

NameAIAA Scitech 2021 Forum

Conference

ConferenceAIAA Scitech 2021 Forum
Period11/01/2121/01/21

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