3D-PTV - Particle Tracking Velocimetry

3D-Particle Tracking Velocimetry

an overview

by

Beat Lüthi

Some applied flows one would like to know more about

from Matthias Machacek (2003) PhD Thesis ETH

applied flow in wind tunnel: car

from Matthias Machacek (2003) PhD Thesis ETH

more abstract but still applied flow: delta wing

Some applied flows one would like to know more about

Some applied flows one would like to know more about

G. Wilkesanders, Ch. Skallerud, Univ. of Colorado at Boulder Visualized in rheoscopic fluid made of fish scales in water.

The wake of a bluff body generated a von Karman vortex street

Main idea of 3D-PTV

How to measure a flow field?How to get 3D information?How to get Lagrangian information?How to not disturb the flow?

3D-PTV

Main idea of 3D-PTV

3D-PTV =

image basedthree dimensional Lagrangianflow measurement technique

(Particle Tracking Velocimetry)

flow + CCD cameras + computers = 3D-PTV

Main idea of 3D-PTV

from Matthias Machacek (2003) PhD Thesis ETH

smoke streaks yield ’only’ quantitative information

Main idea of 3D-PTV

from Matthias Machacek (2003) PhD Thesis ETH

3D-PTV yields quantitative, Lagrangian flow trajectories

Main idea of 3D-PTV

from Matthias Machacek (2003) PhD Thesis ETH

… zooming in more: flow details behind delta wing

Main idea of 3D-PTV

from Heinrich Stüer (1999) PhD Thesis ETH

more ’fundamental’ flow: backward facing step

Main idea of 3D-PTV

from Berg (2006) PhD Thesis Risø

’fully fundamental’: isotropic turbulence

Main idea of 3D-PTV

to follow a 3D (!) particle positionas opposed to 2D PIV!

started 1983

……

USA, CornellReynolds number

some 3D-PTV groupsDenmark, Risøparticle dispersion

Switzerland, ETHvelocity derivatives

and many more groups:Eindhoven,Tel Aviv,Göttingen,

list of technical aspects

•flow tracers•illumination•cameras•observation volume•camera callibration•particle detection•from 2D to 3D positions•particle tracking

flow tracers

high tech, accurate, expensive:

Idea: Søren Ott & Jakob Mann, Risø, Denmarkfly ashsieving50-60µm

low tech, accurate, cheap:

illumination

LED array, TU/e

Lorenzo del Castello, Herman Clercx

trend towards smarter solutions

fast digital cameraspixel: 500x500frame rate: 50Hz

pixel: 1000x1000frame rate: 5000Hzorpixel: 250x250frame rate: 80’000Hz

data storage is main bottelneck

particle detection and position

typically the ’image situation’ is far from ideal

camera callibration•teach the cameras with know grid points•problem: how to have space filling target?•solution in part: callibration on flow tracers

from 2D to 3D position

Cam

era

4C

amer

a 3

Cam

era

1C

amer

a 2

x

yz

r(x,y,z,t)

callibration and 2D position accuracy, seeding density, etc.

tracking through consequtive images

tracking criteria:particle must not travel furtherthan their typical spacing

codes available at www.3dptv.schtuff.com

overcome seeding density bottelneck?

K. Hoyer, M. Holzner, ETH

Scanning PTV

idea:scan flowwith thicklaser sheettoget more particles

many dependencies, many choices…

field of view

depth of view opticalworking distance

camerapixel resolution

camerarecording rate

illumination

flow speed

flow scalesone would liketo resolve

particlediameter

number oftracer particles

trackability

final output is the start for analysisif all goes well, one can finally start ’learning’ about the flow

velocity derivativesdifferentiate

convoluted velocity fieldto get

velocity derivatives

challenge to getHIGH SEEDING DENSITY

B. Lüthi ETH, Søren Ott Risø

applicationsflows with:

•turbulence•dilute polymers•2-phases•convection•agregation•reactions•mean shear•entrainment•rotation•bio-medical conditions

emphasis on:

•velocity•velocity gradient•acceleration•dispersion•multi particle

•Lagrangian aspects•(mean) Eulerian flow field

challenge: reach higher Reynolds numbers at full spacial resolution

Some selected outcome