What Is PIV ? - PowerPoint PPT Presentation

1 / 19
About This Presentation
Title:

What Is PIV ?

Description:

Smith, C.R. (1984) 'A synthesized model of the near-wall ... M0 image magnification [-] dt particle-image diameter [m] DI interrogation-spot diameter [m] ... – PowerPoint PPT presentation

Number of Views:66
Avg rating:3.0/5.0
Slides: 20
Provided by: jerrywes
Category:

less

Transcript and Presenter's Notes

Title: What Is PIV ?


1
What Is PIV ?
  • J. Westerweel
  • Delft University of Technology
  • The Netherlands

2
Why use imaging?
  • Conventional methods
  • (HWA, LDV)
  • Single-point measurement
  • Traversing of flow domain
  • Time consuming
  • Only turbulence statistics
  • Particle image velocimetry
  • Whole-field method
  • Non-intrusive (seeding)
  • Instantaneous flow field

After A.K. Prasad, Lect. Notes short-course on
PIV, JMBC 1997
3
Coherent structures in a TBL
Kim, H.T., Kline, S.J. Reynolds, W.C. J. Fluid
Mech. 50 (1971) 133-160.
Smith, C.R. (1984) A synthesized model of the
near-wall behaviour in turbulent boundary
layers. In Proc. 8th Symp. on Turbulence
(eds. G.K. Patterson J.L. Zakin) University of
Missouri (Rolla).
4
PIV optical configuration
5
Multiple-exposure PIV image
6
PIV Interrogation analysis
RP
RD
RD-
RCRF
Double-exposure image
Spatial correlation
Interrogation region
7
PIV result
Turbulent pipe flow Re 5300 10085 vectors
Hairpin vortex
8
Instantaneous vorticity fields
9
Historical development
  • Quantitative velocity data from particle streak
    photographs (1930)
  • Laser speckle velocimetry Youngs fringes
    analysis (Dudderar Simpkins 1977)
  • Particle image velocimetry
  • Interrogation by means of spatial correlation
  • Digital PIV
  • Stereoscopic PIV holographic PIV

10
Definitions for PIV
  • Source density
  • Image density

C tracer concentration m-3 Dz0 light-sheet
thickness m M0 image magnification
- dt particle-image diameter m DI interrogatio
n-spot diameter m
11
The displacement field
  • The fluid motion is represented as a displacement
    field

12
Velocity from tracer motion
Prob(detect) image density (NI)
Low image density
NI ltlt 1
Particle tracking velocimetry
High image density
NI gtgt 1
Particle image velocimetry
13
Evaluation at high image density
Spatial correlation
14
Linear system theory
Input
Output
Impulse response
Test signals
  • Deterministic
  • Stochastic

15
The tracer pattern
  • G(X,t) represents the random pattern of tracer
    particles that moves with the flow

Input
Output
Impulse response
16
The tracer ensemble
  • Consider the ensemble of all realizations of
    G(X,t) for given u(X,t)

Physical space
Phase space
Liouvilles theorem (continuity)
????t? PDF of ??t?
Homogeneous seeding
Incompressible flow
17
Visualization vs. Measurement
18
Inherent assumptions
  • Tracer particles follow the fluid motion
  • Tracer particles are distributed homogeneously
  • Uniform displacement within interrogation region

19
Ingredients
FLOW
sampling
seeding
quantization
Pixelization
illumination
enhancement
Acquisition
imaging
selection
registration
correlation
Interrogation
estimation
RESULT
validation
analysis
Write a Comment
User Comments (0)
About PowerShow.com