Estimation of the Flowfield from Surface Pressure Measurements in an Open Cavity

Murray, Nathan E.; Ukeiley, Lawrence

doi:10.2514/2.2035

Cited by 76 publications

(30 citation statements)

References 16 publications

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“…However, examination of the correlation between the PIV measurements revealed that there was some level of correlation, although relatively small, between the surface pressure and the velocity for most locations in the shear layer. These low levels are in contrast to similar correlations observed in numerical simulation results of an open cavity in a Mach 1.5 flow as reported in Murray and Ukeiley (2003). This is due to the fact that in the numerical simulations the cavity was dominated by a resonant condition, and the additional noise that is inherent to physical experiments was absent.…”

Section: Velocity-pressure Correlationscontrasting

confidence: 55%

Shear Layer Dynamics in Resonating Cavity Flows

Ukeiley¹,

Murray²

2004

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Section: Velocity-pressure Correlationscontrasting

confidence: 55%

Shear Layer Dynamics in Resonating Cavity Flows

Ukeiley¹,

Murray²

2004

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“…The computation of these coefficients which is time independent is similar to the one proposed by Murray and Ukeiley [37].…”

Section: Quadratic Stochastic Estimation (Qse)mentioning

confidence: 54%

Quadratic stochastic estimation of far‐field acoustic pressure with coherent structure events in a 2D compressible plane mixing layer

Druault

Sagaut

2009

Numerical Methods in Fluids

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SUMMARYMathematical tools based on cross correlations between aerodynamic quantities of interest inside the shear flow region and the radiated sound pressure are used to investigate noise generation mechanisms in a plane compressible mixing layer. An original methodology relying on an efficient coupling between proper orthogonal decomposition (POD) and stochastic estimation procedures is developed to analyze the main aerodynamic mechanisms that govern noise production. POD is used to split the instantaneous flow fluctuations as the sum of three components: the large-and small-scale coherent structures (LCS and SCS) and the background quasi-Gaussian fluctuations. Based on this flow partitioning, quadratic stochastic estimation is implemented to estimate the far-field acoustic pressure associated with each flow component. The far field acoustic pressure associated with both LCS and SCS is then investigated. By analyzing the RMS and temporal spectra of the far-field acoustic pressure, it is observed that the SCSs, as defined thanks to the POD basis, are responsible for the main part of the noise emission.

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“…Based on the same motivation of predicting velocity fields, linear stochastic estimation (LSE) as first introduced by Adrian [29] has also been used for the same purpose. Examples of this can be found in the work of Glauser [26], Hudy [27], Murray [33] and Taylor [35], who have used LSE in combination with scalar pressure measurements to obtain a complete description of the velocity fields for different geometries, such as backward facing steps, axi-symmetric jets and cavities. Various extensions of LSE have been explored in the work of Hudy [27], Tinney [32] and others.…”

Section: Introductionmentioning

confidence: 97%