Multi-time delay, multi-point linear stochastic estimation of a cavity shear layer velocity from wall-pressure measurements

2013 ◽  
Vol 25 (1) ◽  
pp. 017101 ◽  
Author(s):  
Davide Lasagna ◽  
Matteo Orazi ◽  
Gaetano Iuso
Keyword(s):  
Time Delay ◽  
Shear Layer ◽  
Wall Pressure ◽  
Stochastic Estimation ◽  
Pressure Measurements ◽  
Linear Stochastic Estimation ◽  
Layer Velocity

Calculation of tunnel wall interference from wall-pressure measurements

1988 ◽  
Vol 92 (911) ◽  
pp. 36-53 ◽  
Author(s):  
P. R. Ashill ◽  
R. F. A. Keating
Keyword(s):  
Experimental Evaluation ◽  
Solid Wall ◽  
Wall Pressure ◽  
Wind Tunnels ◽  
Pressure Measurements ◽  
Complex Flows ◽  
Tunnel Wall ◽  
Model Flow ◽  
Good Agreement

Summary A method is described for calculating wall interference in solid-wall wind tunnels from measurements of static pressures at the walls. Since it does not require a simulation of the model flow, the technique is particularly suited to determining wall interference for complex flows such as those over VSTOL aircraft, helicopters and bluff shapes (e.g. cars and trucks). An experimental evaluation shows that the method gives wall-induced velocities which are in good agreement with those of existing methods in cases where these techniques are valid, and illustrates its effectiveness for inclined jets which are not readily modelled.

Distortion reconstruction in S-ducts from wall static pressure measurements

2018 ◽  
Vol 28 (5) ◽  
pp. 1134-1155 ◽  
Author(s):  
Pierre Grenson ◽  
Eric Garnier
Keyword(s):  
Static Pressure ◽  
Active Flow Control ◽  
Hybrid Approach ◽  
Reconstruction Algorithm ◽  
Stochastic Estimation ◽  
Pressure Measurements ◽  
Reconstruction Algorithms ◽  
Detached Eddy Simulation ◽  
Flow Distortion ◽  
Content Type

Purpose This paper aims to report the attempts for predicting “on-the-fly” flow distortion in the engine entrance plane of a highly curved S-duct from wall static pressure measurements. Such a technology would be indispensable to trigger active flow control devices to mitigate the intense flow separations which occur in specific flight conditions. Design/methodology/approach Evaluation of different reconstruction algorithms is performed on the basis of data extracted from a Zonal Detached Eddy Simulation (ZDES) of a well-documented S-Duct (Garnier et al., AIAA J., 2015). Contrary to RANS methods, such a hybrid approach makes unsteady distortions available, which are necessary information for reconstruction algorithm assessment. Findings The best reconstruction accuracy is obtained with the artificial neural network (ANN) but the improvement compared to the classical linear stochastic estimation (LSE) is minor. The different inlet distortion coefficients are not reconstructed with the same accuracy. KA2 coefficient is finally identified as the more suited for activation of the control device. Originality/value LSE and its second-order variant (quadratic stochastic estimation [QSE]) are applied for reconstructing instantaneous stagnation pressure in the flow field. The potential improvement of an algorithm based on an ANN is also evaluated. The statistical link between the wall sensors and 40-Kulite rake sensors are carefully discussed and the accuracy of the reconstruction of the most used distortion coefficients (DC60, RDI, CDI and KA2) is quantified for each estimation technique.

scholarly journals Stochastic Estimation and Non-Linear Wall-Pressure Sources in a Separating/Reattaching Flow

2002 ◽  
Author(s):  
A. Naguib ◽  
L. Hudy ◽  
W. M. Humphreys
Keyword(s):  
Flow Field ◽  
Surface Pressure ◽  
Wall Pressure ◽  
Stochastic Estimation ◽  
Piv Measurements ◽  
Non Linear ◽  
The Mean ◽  
The Individual ◽  
Plate Geometry ◽  
Shed Light

Simultaneous wall-pressure and PIV measurements are used to study the conditional flow field associated with surface-pressure generation in a separating/reattaching flow established over a fence-with-splitter-plate geometry. The conditional flow field is captured using linear and quadratic stochastic estimation based on the occurrence of positive and negative pressure events in the vicinity of the mean reattachment location. The results shed light on the dominant flow structures associated with significant wall-pressure generation. Furthermore, analysis based on the individual terms in the stochastic estimation expansion shows that both the linear and non-linear flow sources of the coherent (conditional) velocity field are equally important contributors to the generation of the conditional surface pressure.

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