paths to 3d piv
Download
Skip this Video
Download Presentation
Paths to 3D PIV

Loading in 2 Seconds...

play fullscreen
1 / 43

Paths to 3D PIV - PowerPoint PPT Presentation


  • 141 Views
  • Uploaded on

Through 2D Recording. Multiple Projection. Scanning. Digital Image Processor. Through 3D Recording. Stroboscope. Paths to 3D PIV. Holography. Recording. Reconstruction. Laser Pulse. Laser Beam. 8ns. CCD. Interrogation camera. Hologram. 3D flow seeded with particles.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Paths to 3D PIV' - sue


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
paths to 3d piv
Through 2D Recording

Multiple Projection

Scanning

Digital Image

Processor

  • Through 3D Recording

Stroboscope

Paths to 3D PIV

Holography

principle of hpiv
Recording

Reconstruction

Laser

Pulse

Laser

Beam

8ns

CCD

Interrogation

camera

Hologram

3D flow seeded with particles

Double Exposure

Holocine (time resolved)

t2 t2+ Dt

t1 t1+ Dt

t2

t3

t1

Principle of HPIV

Displacement

Velocity

advantage of holography
Advantage of holography
  • True 3D imaging
  • Instantaneous Volumetric
  • High Information Capacity(106 - 109 Particles)
  • Real-Time Recording but Off-line Data Transfer & Processing
how to get true 3d imaging
How to get true 3D imaging?

Phase Preservation

O=Oexp[i(f-wt)]

or: O=Osin(f-wt)

How to record f?

Any light sensitive media records intensity

I=|O|2 =O2

Need to “encode” phase finto some intensity modulation

encoding phase
Encoding Phase

-- Use interference of coherent light!

E= R+ O

Reference wave Object wave

where R = R exp[i(j-wt)] , O=Oexp[i(f-wt)]

Recorded Intensity:

I=|R+O|2 = R2 + O2 +2ROsin(f-j)

principle of holography
0

x

q

z

B

e

c

n

e

r

e

Hologram

f

e

R

Recording

y

Virtual Image

0

x

Real Image

q

m

a

z

Object

e

B

e

c

n

e

r

e

f

e

m

R

Hologram

a

e

Reconstruction

Principle of Holography

O

I =|R+O|2= R2 + O2 +2ROsin(f-j)

R

I =(R+O)(R+O)*

= R2 + O2 + R*O+RO*

O*

T ~ R2 + O2 + R*O+RO*

Usually R= exp(-iwt)

T ~ 1+ O2 + O + O*

O

experimental demonstration
Experimental Demonstration

Reference beam, object beam

Virtual, real image

*Transmission or Reflection Hologram?

Setup Considerations:

Coherence length vs. path length difference

Exposure energy: In the linear range

R:O ratio

transmission or reflection hologram
Transmission or Reflection Hologram

Reflection hologram created by 2 plane waves traveling towards opposite sides

(Volume Hologram)

Transmission hologram created by 2 plane waves traveling towards the same side

reflection hologram
Reflection Hologram

Bragg Condition

2dsinq=ml

in line gabor holography
Reference wave

LASER

Object wave

Viral Image

Real Image

LASER

In-line (Gabor) Holography

Traditional for particle fields

  • Simple geometry
  • Low coherence & energy requirement
  • Speckle noise

(limit seeding density & seeding depth)

  • Large depth of focus
  • (practically only 2D vectors)
speckle noise in line hologram
Speckle Noise (in-line hologram)

Ok= S ok= Skexp(ifk) : Random Walk

Reconstruction field of an in-line hologram for an ensemble of particles: B + S ok+ S o*k

Type-I speckle -- interference between B and the scattered waves Major Source of Speckle

Type-II speckle -- self-interference of the scattered waves.

slide12
Speckle noise: decrease Signal-to-Noise Ratio

40 particles /mm3

6 particles /mm3

1 particle /mm3

off axis holography as solution
In-Line HPIV:
  • Simple Geometry
  • Lower Coherence Required
  • Intrinsic Speckle Noise
  • Lower Seeding Density

Virtual

Hologram

Real

Hologram

Image

Image

Reference

Reference

Beam

Beam

Reconstruction

Recording

In-line HPIV

Virtual

Image

Reference

Real

Reference

Beam

Image

Beam

Hologram

Illuminating

Beam

Hologram

Recording

Reconstruction

Off-axis HPIV

Off-Axis Holography as Solution

Off-axis HPIV:

  • Higher SNR
  • Higher Seeding Density
  • Complex Geometry
  • Higher Coherence Required
slide14
IROV - In-line Recording Off-axis Viewing Holography
  • IROV: Use side scattering
  • Suppresses speckle noise
  • Reduces image depth of focus

Making In-line based HPIV feasible

Meng & Hussain (1995): Appl. Opt. 34, 1827

slide15
IROV Experimental Setup

Recording

Reconstruction

use of high frequency fringes on in line holograms
Use of High-Frequency Fringes on In-Line Holograms
  • Negligible influence of forward scattering: Since |OL| << |R|,
  • IL << I sig
irov suppresses speckle noise
IROV suppresses speckle noise

Reconstruction field of an in-line hologram for an ensemble of particles: B + S ok+ S o*k

  • Completely avoids type-I speckle
  • greatly reduces type-II speckle

Off-axis Viewing: receives onlyS o*k

slide18
Improved SNR by IROV

In-line Viewed

IROV

reduction of depth of focus by irov
+100 mm

In focus

-100 mm

Reduction of Depth of Focus by IROV

In-line: Fraunhofer diffraction

0 degree

20 degree

irov data processing genetic algorithm particle pairing
IROV Data Processing: Genetic Algorithm Particle Pairing

Interrogation Cell

4’

3’

5’

3

4

2’

2

6’

5

1’

1

7’

6

7

  • Low density requires intelligent pairing
  • GA searches large solution space
slide24
Genetic Algorithm

Particle Pairing

slide25
Large solution space

Why Genetic Algorithm?

Many possibilities to pair particles

Need to numerate and filter

  • Conventional searching methods
  • Computation intensive
  • Difficult to incorporate intelligence
  • Time consuming
  • Genetic Algorithm
  • Efficient in searching large space
  • Built-in intelligence to follow fluid dynamics
  • Fast and inherent parallel processing speed
slide27
Two Approaches of HPIV

Developed at LFD

Off-axis HPIV

high-end

In-line (IROV) HPIV

low-cost

slide29
Dual-Reference Off-Axis Technique
  • High Seeding Density Allowed
  • Small Depth of Focus
  • Image Separation Removes
  • Direction Ambiguity
  • Complex Optical Geometry
  • High Energy Laser Required
  • High Coherence of Beam
  • Needed
slide31
Concise Cross Correlation(CCC) Algorithm
  • Matching by particle groups
  • Uses particle centroids only
  • Group shifting for matching
  • Decomposition of operation
  • Low data volume / high compression rate
  • High-speed processing
slide33
Phase-Locked Vortex

Side View

Top View

vortab flow hpiv measurement result
Vortab Flow: HPIV Measurement Result
  • Amount of Data: 400,000 Vectors
  • Mean Velocity: 16.67 cm/sec.
fundamental challenges
Hologram captures 3D instantly

HPIV =

3D Information

Transfer & Processing

Turbulent

Flow Field

Flow Field

Reconstruction

Fundamental Challenges
  • 3D Signal Decoding
  • Complex Flow Mapping
  • Large DataQuantity
  • User-friendly?
slide40
Holographic

Flow Visualization

a Tool for Studying 3D

Coherent Structures and Instabilities

Kansas State University, ISSI,

Wright Laboratory, WP/AFB

slide41
Off-Axis HFV of Vortex Flame

(c)

(b)

(a)

Holographic Images of Three Vortex-Flame Systems Photographed

from Two Angles (a)

or Using Two Magnifications (b and c).

slide42
IROV HFV of Turbulent Milk Drop

Holographic Images of A Milk Drop Undergoing Bag Instability (a, b)

Holographic Images of A Turbulent Milk Drop (a) and Its Downstream Breakdown (b, c)

slide43
Naturally, HPIV is an ideal diagnostic tool for studying particulate phase

- 3D and dynamically

ad