Effect of Small Surface Deformations on the Stability of Tollmien–Schlichting Disturbances

Thomas, Christian; Mughal, Shahid; Roland, Hannah; Ashworth, Richard; Martínez-Cava, Alejandro

doi:10.2514/1.j056821

Cited by 18 publications

(5 citation statements)

References 36 publications

(70 reference statements)

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“…(2016), Thomas et al. (2018) and Raposo (2020). The resulting neutral stability curves for and two different Reynolds numbers are presented in figure 8.…”

Section: Numerical Resultsmentioning

confidence: 98%

“…We use a standard compressible Orr-Sommerfeld solver to calculate and track the most unstable two-dimensional instabilities for a range of frequencies. This code has been used and validated extensively -the reader is referred to Mughal (2006), Thomas et al (2016), Thomas et al (2018) and Raposo (2020). The resulting neutral stability curves for α = 0 • and two different Reynolds numbers are presented in figure 8.…”

Section: Stability Analysismentioning

confidence: 99%

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Acoustic-roughness receptivity in subsonic boundary-layer flows over aerofoils

et al. 2021

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The generation of a viscous–inviscid instability through scattering of an acoustic wave by localised and distributed roughness on the upper surface of a NACA 0012 aerofoil is studied with a time-harmonic compressible adjoint linearised Navier–Stokes approach. This extends previous work by the authors dedicated to flat plate geometries. The key advancement lies in the modelling of the inviscid acoustic field external to the aerofoil boundary layer, requiring a numerical solution of the convected Helmholtz equation in a non-uniform inviscid field to determine the unsteady pressure field on the curved aerofoil surface. This externally imposed acoustic pressure field subsequently drives the acoustic boundary layer, which fundamentally determines the amplitudes of acoustic-roughness receptivity. A study of receptivity in the presence of Gaussian-shaped roughness and sinusoidally distributed roughness at Mach number $M_\infty =0.4$ and Strouhal numbers $\mathcal {S} \approx \{46,69,115\}$ shows the effects of various parameters, most notably angle of attack, angle of incidence of the externally imposed plane acoustic wave and geometry of surface roughness; the latter is varied from viewpoint of its placement on the aerofoil surface and its wavelength. The parametric study suggests that non-parallel effects are quite substantial and that considerable differences arise when using parallel flow theory to estimate the optimal width of Gaussian-shaped roughness elements to provoke the greatest response. Furthermore, receptivity amplitudes for distributed roughness are observed to be generally higher for lower angles of attack, i.e. for less adverse pressure gradients. It is also shown that the boundary layer is more receptive to upstream-travelling acoustic waves.

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“…(2016), Thomas et al. (2018) and Raposo (2020). The resulting neutral stability curves for and two different Reynolds numbers are presented in figure 8.…”

Section: Numerical Resultsmentioning

confidence: 98%

Section: Stability Analysismentioning

confidence: 99%

Acoustic-roughness receptivity in subsonic boundary-layer flows over aerofoils

et al. 2021

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“…Traditional numerical methods used to predict the transition, such as Local Stability Theory (LST) [11] or Parabolized Stability Equations (PSE) [14], have given satisfactory results for dealing with smooth cases or with surface defects of restricted dimensions. However, the effect of a surface irregularity on the transition is poorly taken into account by these methods because of the assumptions made on the base flow.…”

Section: Introductionmentioning

confidence: 99%

Neural Prediction Model for Transition Onset of a Boundary-Layer in Presence of 2D Surface Defects

Rouviere

Pascal

Méry

et al. 2022

AIAA SCITECH 2022 Forum

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Predicting the laminar to turbulent transition is an important aspect of computational fluid dynamics because of its impact on skin friction. Traditional methods of transition prediction do not make it possible to consider configurations where the boundary layer develops in presence of surface defects (bumps, steps, gaps, etc.). A neural network approach is used in this paper, based on an extensive database of boundary layer stability computations in presence of gap-like surface defects. These computations consists on linearized Navier-Stokes calculations and provide informations on the effect of surface irregularity geometry and aerodynamic conditions on the transition to turbulence. Physical and geometrical parameters characterizing the defect and the flow are provided to a neural network whose outputs inform about the effect of a given gap on the transition through the Δ𝑁 method.

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“…Although the above study was limited to the control of linear stationary cross-flow disturbances in the incompressible swept Hiemenz boundary layer, the strategy could easily be extended to encompass other forms of disturbance (TS waves, travelling cross-flow), complex compressible flow systems 45 and aerofoil bodies 73,74 . Additionally, nonlinear effects were ignored that become significant as perturbations achieve larger magnitudes, which may impede the optimised control mechanisms ability to dampen disturbance development.…”

Section: Discussionmentioning

confidence: 99%

Optimizing control of stationary cross-flow vortices excited by surface roughness

Thomas

Mughal

2022

Physics of Fluids

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Stationary cross-flow vortices are excited within the swept Hiemenz boundary layer via surface roughness and actively controlled using an optimally configured control device. Control is modelled using localised wall motion, but in practice the optimisation strategy could be applied to other laminar flow control technologies. A sensor-control iterative procedure, based on solutions of the forward and adjoint linearised Navier--Stokes equations, is applied to both feedforward and feedback loop systems. The former strategy only allows the control settings to be configured once, while the latter approach permits the repeated reoptimisation of the control device. Surface roughness establishes a stationary cross-flow disturbance with a pre-defined set of flow conditions, but an unknown amplitude and phase. A sensor measures the local amplitude of the perturbation and relays the information to the control mechanism. Solutions of the adjoint linearised Navier--Stokes equations are coupled with the sensor measurements to configure and optimise the control mechanism, and establish an anti-phase wave that brings about destructive wave interference. The amplitude of the stationary cross-flow instability is reduced by an order $10^3$ for the feedforward system, while amplitude reductions of the order $10^3$ per iteration and $10^8$ overall are realisable for the feedback modelling approach. Similar levels of flow control are realisable for a multiple controller configuration. However, stationary cross-flow disturbances could not be eliminated indefinitely. Inevitably, the cross-flow instability started to grow again, albeit at a considerably lower magnitude. The analysis is extended to include the effects of systematic error in the sensors measuring capability.

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Effect of Small Surface Deformations on the Stability of Tollmien–Schlichting Disturbances

Cited by 18 publications

References 36 publications

Acoustic-roughness receptivity in subsonic boundary-layer flows over aerofoils

Acoustic-roughness receptivity in subsonic boundary-layer flows over aerofoils

Neural Prediction Model for Transition Onset of a Boundary-Layer in Presence of 2D Surface Defects

Optimizing control of stationary cross-flow vortices excited by surface roughness

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