Computational Analysis of the G-III Laminar Flow Glove

Malik, Mujeeb R.; Liao, Wei; Lee-Rausch, Elizabeth M.; Li, Fēi; Choudhari, Meelan M.; Chang, Chau‐Lyan

doi:10.2514/6.2011-3525

Cited by 17 publications

(11 citation statements)

References 37 publications

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“…It has been known for some considerable time that curvature included PSE models predict (as is verified by experiment) a significant stabilising effect of curvature on stationary crossflow waves, particularly around the curved leading edge of a swept wing. In the recent work of Malik et al, 5 on the NASA Environmentally Responsible Aviation Project, computational assessment of the Gulfstream-III (G-III) aircraft wing-glove design revealed strong curvature dependent effects on instability amplitudes. Inclusion of curvature and non-parallel modelling within the receptivity modelling arena is contentious.…”

Section: Introductionmentioning

confidence: 98%

Uncertainty Quantification Based Receptivity Modelling of Crossflow Instabilities Induced by Distributed Surface Roughness in Swept Wing Boundary Layers

Mughal

Ashworth

2013

43rd Fluid Dynamics Conference

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A high fidelity methodology based on the rapid solution of a linearised Navier-Stokes equation set is used to model the role of distributed surface roughness in generating stationary crossflow disturbances on swept wing flows. The technique is based on a stochastic description of surface roughness linked to high precision measurement data for both anodised aluminium and painted surfaces. A Monte Carlo analysis of laminar-turbulent transition is demonstrated for data from the AERAST wind tunnel test which was designed to show control of stationary cross-flow disturbances through the forced excitation of a sub-dominant disturbance mode generated by the artificial placement of periodically distributed roughness elements. The method provides both the roughness induced naturally occurring and forced control mode disturbance amplitudes for initialisation of a simulation based on solution of the non-linear parabolised stability equations. Monte-Carlo based uncertainty quantification analysis enables propagation of uncertainties from the roughness field through the receptivity phase, to ultimately providing bounds on the predicted transition location.

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Section: Introductionmentioning

confidence: 98%

Uncertainty Quantification Based Receptivity Modelling of Crossflow Instabilities Induced by Distributed Surface Roughness in Swept Wing Boundary Layers

Mughal

Ashworth

2013

43rd Fluid Dynamics Conference

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“…This work was continued under NASA's Environmentally Responsible Aviation (ERA) project. [9][10][11][12][13][14] Other related activities under the SFW project focused on in-flight characterization of crossflow receptivity to surface roughness, 15 design tools 16 and high Reynolds number testing for natural laminar flow (NLF) wings. 17 These activities were subsequently transitioned to the ERA project.…”

Section: Introductionmentioning

confidence: 99%

Towards Bridging the Gaps in Holistic Transition Prediction via Numerical Simulations

Choudhari

Chang

et al. 2013

21st AIAA Computational Fluid Dynamics Conference

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The economic and environmental benefits of laminar flow technology via reduced fuel burn of subsonic and supersonic aircraft cannot be realized without minimizing the uncertainty in drag prediction in general and transition prediction in particular. Transition research under NASA's Aeronautical Sciences Project seeks to develop a validated set of variable fidelity prediction tools with known strengths and limitations, so as to enable "sufficiently" accurate transition prediction and practical transition control for future vehicle concepts. This paper provides a summary of research activities targeting selected gaps in high-fidelity transition prediction, specifically those related to the receptivity and laminar breakdown phases of crossflow induced transition in a subsonic swept-wing boundary layer. The results of direct numerical simulations are used to obtain an enhanced understanding of the laminar breakdown region as well as to validate reduced order prediction methods. Nomenclature A= amplitude of crossflow instability mode or secondary instability mode, measured in terms of peak chordwise velocity perturbation and normalized with respect to freestream velocity c = wing chord length normal to the leading edge C = coupling coefficient for receptivity D = diameter of cylindrical roughness element f = frequency of instability oscillations (Hz) F = forcing function representing external disturbance environment F = geometry factor from receptivity theory G = gain factor associated with instability amplification i = (-1) 1/2 k = grid index along wall-normal direction M = freestream Mach number N = N-factor (i.e., logarithmic amplification ratio) of linear crossflow instability or secondary instability q = arbitrary flow variable R = transfer function associated with receptivity Re c = Reynolds number based on wing chord t = time (u,v,w) = Cartesian velocity components aligned with (x,y,z) axes x = chordwise coordinate in direction perpendicular to leading edge y = Cartesian coordinate normal to x-y plane z = spanwise coordinate, i.e., the coordinate parallel to airfoil leading edge α = chordwise wavenumber 1 2 β = spanwise wavenumber Γ = wing sweep angle λ = spanwise wavelength of crossflow instability λ w = chordwise wavelength of wall waviness Λ = efficiency function for localized receptivity ξ = dummy integration variable in chordwise direction π = normalized mode shape of instability wave θ = phase function φ = normalized mode shape of instability wave ω = radian frequency of instability wave Subscripts c = crossflow direction i = initial or reference location (typically chosen to be lower branch neutral station for primary instability and inflow location of x/c=0.502 for secondary instability) init = initial or reference location (used interchangeably with subscript i) ins = instability wave lb = lower branch neutral station for the instability mode of interest L = linear amplification phase N = nonlinear amplification phase r = roughness w = wall τ = edge streamline direction Superscripts + = wall units

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“…A wing glove was designed by TAMU, with the glove leading-edge sweep of 34.6 deg with a maximum possible chord Reynolds number approaching 30 × 10 6 . The details of the glove design and analyses using computational fluid dynamics and stability-analysis codes have been given in [26][27][28][29][30].…”

mentioning

confidence: 99%

Discrete-Roughness-Element-Enhanced Swept-Wing Natural Laminar Flow at High Reynolds Numbers

Malik

Liao

et al. 2015

AIAA Journal

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Nonlinear parabolized stability equations and secondary-instability analyses are used to provide a computational assessment of the potential use of the discrete-roughness-element technology for extending swept-wing natural laminar flow at chord Reynolds numbers relevant to transport aircraft. Computations performed for the boundary layer on a natural-laminar-flow airfoil with a leading-edge sweep angle of 34.6 deg, freestream Mach number of 0.75, and chord Reynolds numbers of 17 × 10 6 , 24 × 10 6 , and 30 × 10 6 suggest that discrete roughness elements could delay laminar-turbulent transition by about 20% when transition is caused by stationary crossflow disturbances. Computations show that the introduction of small-wavelength stationary crossflow disturbances (i.e., discrete roughness element) also suppresses the growth of most amplified traveling crossflow disturbances.

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Computational Analysis of the G-III Laminar Flow Glove

Cited by 17 publications

References 37 publications

Uncertainty Quantification Based Receptivity Modelling of Crossflow Instabilities Induced by Distributed Surface Roughness in Swept Wing Boundary Layers

Uncertainty Quantification Based Receptivity Modelling of Crossflow Instabilities Induced by Distributed Surface Roughness in Swept Wing Boundary Layers

Towards Bridging the Gaps in Holistic Transition Prediction via Numerical Simulations

Discrete-Roughness-Element-Enhanced Swept-Wing Natural Laminar Flow at High Reynolds Numbers

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