Stochastic Investigation on the Robustness of Laminar-Flow Wings for Flight Tests

Natural laminar-flow (NLF) wings and hybrid laminar-flow control (HLFC) wings are efficient drag reduction technologies. It is vital to develop robust laminar-flow wings to research the stochastic characteristics of both NLF and HLFC wings and reveal the generation mechanism for differences in their...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:AIAA journal 2022-04, Vol.60 (4), p.2266-2286
Hauptverfasser: Yang, Tihao, Chen, Yifu, Shi, Yayun, Hua, Jun, Qin, Feifei, Bai, Junqiang
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Natural laminar-flow (NLF) wings and hybrid laminar-flow control (HLFC) wings are efficient drag reduction technologies. It is vital to develop robust laminar-flow wings to research the stochastic characteristics of both NLF and HLFC wings and reveal the generation mechanism for differences in their statistical responses. Wing-glove flight experiments and deterministic numerical simulations using the eN method with a suction-velocity model are performed, which are in good agreement. Uncertainty and correlation analyses based on nonintrusive polynomial chaos expansion are then performed to evaluate the influence of operational and geometric uncertainties. The simulations indicate that operational condition uncertainties have a greater impact on their statistical responses. Pressure coefficients near the leading edge and end region of the favorable pressure gradient are the most sensitive to disturbances in the angle of attack (AOA) and Mach number, respectively. Whereas HLFC wings significantly delay the laminar–turbulent transition, NLF wings may have better robustness against disturbances if the development of Tollmien–Schlichting (TS) waves is not completely suppressed in the suction region. This is because disturbances affect statistical responses of HLFC wings by changing both the local pressure gradients and suction coefficient distributions. Positive correlations between the AOA, local pressure gradients, and suction coefficients amplify the influence of AOA disturbances. Meanwhile, Mach-number disturbances have negative and positive correlations with local pressure gradients and suction coefficients, respectively. The opposite correlation weakens the influence of Mach-number disturbances.
ISSN:0001-1452
1533-385X
DOI:10.2514/1.J060842