Acoustic Liner Drag Measurements

Gustavsson, Jonas; Yang, Zhigang; Cattafesta, Louis N.; Kreitzman, Jordan R.

doi:10.2514/6.2019-2683

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…Monte Carlo simulations were then performed to estimate the corresponding uncertainty (Table 1). More details about the control volume method can be found in Gustavsson et al (2019). We find that most of the measurement techniques give similar estimates or measurement of u τ and τ w , except the wall shear stress sensor.…”

Section: Experiments and Verificationmentioning

confidence: 89%

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Unscented Kalman filter (UKF)–based nonlinear parameter estimation for a turbulent boundary layer: a data assimilation framework

Pan¹,

Zhang²,

Gustavsson³

et al. 2020

Meas. Sci. Technol.

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A turbulent boundary layer is an essential flow case of fundamental and applied fluid mechanics. However, accurate measurements of turbulent boundary layer parameters (e.g., friction velocity u τ and wall shear τ w ), are challenging, especially for high speed flows (Smits et al., 2011). Many direct and/or indirect diagnostic techniques have been developed to measure wall shear stress (Vinuesa et al., 2017). However, based on different principles, these techniques usually give different results with different uncertainties. The current study introduces a nonlinear data assimilation framework based on the Unscented Kalman Filter that can fuse information from i) noisy and gappy measurements from Stereo Particle Image Velocimetry, a Preston tube, and a MEMS shear stress sensor, as well as ii) the uncertainties of the measurements to estimate the parameters of a turbulent boundary layer. A direct numerical simulation of a fully developed turbulent boundary layer flow at Mach 0.3 is used first to validate the data assimilation algorithm. The algorithm is then applied to experimental data of a flow at Mach 0.3, which are obtained in a blowdown wind tunnel facility. The UKF-based data assimilation algorithm is robust to uncertain and gappy experimental data and is able to provide accurate estimates of turbulent boundary layer parameters.

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Section: Experiments and Verificationmentioning

confidence: 89%

“…M C simulations are then performed 10 4 times to estimate the corresponding uncertainty shown in table 2. More details about the control volume method can be found in Gustavsson et al (2019).…”

Section: Experiments and Verificationmentioning

confidence: 99%

Unscented Kalman filter (UKF)–based nonlinear parameter estimation for a turbulent boundary layer: a data assimilation framework

Pan¹,

Zhang²,

Gustavsson³

et al. 2020

Meas. Sci. Technol.

Self Cite

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“…Additionally, these experiments suggest that it is possible to reduce the drag penalty without harming the noise attenuation. Gustavsson et al (2019) performed experiments over several acoustic liner geometries and reported a drag increase of between 30 % and 50 %, without incoming acoustic waves, arguing that the added drag might be even larger in the presence of incoming noise.…”

Section: Introductionmentioning

confidence: 99%

Turbulence and added drag over acoustic liners

2023

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We present pore-resolved compressible direct numerical simulations of turbulent flows grazing over perforated plates, that closely resemble the acoustic liners found on aircraft engines. Our direct numerical simulations explore a large parameter space including the effects of porosity, thickness and viscous-scaled diameter of the perforated plates, at friction Reynolds numbers $\textit {Re}_\tau = 500\unicode{x2013}2000$ , which allows us to develop a robust theory for estimating the added drag induced by acoustic liners. We find that acoustic liners can be regarded as porous surfaces with a wall-normal permeability and that the relevant length scale characterizing their added drag is the inverse of the wall-normal Forchheimer coefficient. Unlike other types of porous surfaces featuring Darcian velocities inside the pores, the flow inside the orifices of acoustic liners is fully turbulent, with a magnitude of the wall-normal velocity fluctuations comparable to the peak in the near-wall cycle. We provide clear evidence of a fully rough regime for acoustic liners, also confirmed by the increasing relevance of pressure drag. Once the fully rough asymptote is reached, canonical acoustic liners provide an added drag comparable to that of sand-grain roughness with viscous-scaled height matching the inverse of the viscous-scaled Forchheimer permeability of the plate.

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Passive acoustic liners for aero-engine noise control: A review

Ma,

Wang,

et al. 2024

Mechanics of Advanced Materials and Structures

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Acoustic Liner Drag Measurements

Cited by 4 publications

References 6 publications

Unscented Kalman filter (UKF)–based nonlinear parameter estimation for a turbulent boundary layer: a data assimilation framework

Unscented Kalman filter (UKF)–based nonlinear parameter estimation for a turbulent boundary layer: a data assimilation framework

Turbulence and added drag over acoustic liners

Passive acoustic liners for aero-engine noise control: A review

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