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UID:0-427@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20170628T163000

DTEND;TZID=Asia/Jerusalem:20170628T173000

DTSTAMP:20230530T180824Z

URL:https://aerospace.technion.ac.il/events/disturbance-source-identificat
 ion-for-flow-control/

SUMMARY:Disturbance Source Identification for Flow Control
DESCRIPTION:Lecturer:Igal Gluzman\n Faculty:Department of Aerospace Enginee
 ring\n Institute:Technion – Israel Institute of Technology\n Location:Cl
 assroom 165\, ground floor\, Library\, Aerospace Eng.\n Zoom: \n Abstract:
  \n Details: \n We present a novel approach for identifying disturbance so
 urces in wall-bounded shear flows\, which can prove useful for active cont
 rol of boundary layer transition from laminar to turbulent flow. The idea 
 underlying this research is to consider the flow state\, as measured in se
 nsors\, as a mixture of sources\, and to use Blind Source Separation (BSS)
  techniques to recover the separate sources and their unknown mixing proce
 ss.\nWe begin by introducing a BSS method based on the Independent Compone
 nt Analysis (ICA) technique\, and provide physics-based criteria for prope
 r sensor placement in order to successfully separate Tollman-Schlichting (
 TS) wave disturbances. We verify these criteria by successfully implementi
 ng the ICA method in appropriate computer simulations of shear flow.\nTo a
 lleviate the limitations of the ICA-based source identification technique\
 , we next present a BSS method based on the Degenerate Unmixing Estimation
  Technique (DUET). This method can be used to identify any (a priori unkno
 wn) number of sources by using the data acquired by only two sensors.  We
  adapt and apply the DUET method to identify disturbance sources in measur
 ed mixtures comprising TS waves and wave-packets. Furthermore\, we extend 
 the DUET-based method to also determine the propagation velocity vector of
  each of the identified sources by using sensor signals from three differe
 nt locations in the flow field.  The viability of the method is demonstra
 ted via numerical simulations and specially-designed wind-tunnel experimen
 ts.\nThe BSS-based identification methods presented in this work rely on t
 he capability to accurately measure velocity signal mixtures using nonline
 ar flow sensors\, such as hot-wire flow velocity probes. This gives rise t
 o the problem of fast and accurate sensor calibration. To address this iss
 ue we have developed a Gaussianization-based statistical calibration techn
 ique for estimating the nonlinear calibration curve of hot-wire probes.  
 The method uses as input a measured sequence of voltage samples\, correspo
 nding to different unknown flow velocities in the desired  operational ra
 nge\, and only two measured voltages along with their known (calibrated) f
 low velocities. The novel calibration method is validated against standard
  calibration methods using data acquired by hot-wire probes in wind-tunnel
  experiments.
CATEGORIES:Seminars
LOCATION:Classroom 165\, ground floor\, Library\, Aerospace Eng.

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DTSTART:20170324T030000

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