Visualization of DNS isoT Code ResultsResearch Summary
Mishaal Aleem
Computational Fluid Mechanics LabAeronautics & AstronauticsUniversity of Washington
June 17, 2015
Mishaal Aleem (UW) Visualization of DNS isoT Code Results June 17, 2015 1 / 22
Outline
1 Objective
2 Background
3 Methodology
4 Results
5 Summary & Future Work
6 Acknowledgments
Mishaal Aleem (UW) Visualization of DNS isoT Code Results June 17, 2015 2 / 22
Outline
1 Objective
2 Background
3 Methodology
4 Results
5 Summary & Future Work
6 Acknowledgments
Mishaal Aleem (UW) Visualization of DNS isoT Code Results June 17, 2015 3 / 22
Objective
Research Topic
Research visualization methods for the results of a direct numericalsimulation (DNS) code of droplet-laden isotropic turbulence. Create3-dimensional plots and animations given varying input parameters.
The importance of CFD visualization:
Humans are highly visual creatures and process information based onwhat they see
65% of humans are visual learners [1]The brain processes visual information 60,000 times faster than text [2]40% of all nerve fibers connected to a brain are linked to the retina [2]
Visualization of data is an important part of the validation of thecomputer methods and the physics/math used in the modeling
Visuals can provide insight that may be hard to deduce from theenormous data sets created from a CFD computer code
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Outline
1 Objective
2 Background
3 Methodology
4 Results
5 Summary & Future Work
6 Acknowledgments
Mishaal Aleem (UW) Visualization of DNS isoT Code Results June 17, 2015 5 / 22
Background
Non-evaporating droplet-laden isotropic turbulence
At the initial time, droplets are at rest
Once the simulation begins, droplets interact with turbulence andwith other droplets
Applicable to combustion engine theory
Developed by Michael Dodd (University of Washington)
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Outline
1 Objective
2 Background
3 Methodology
4 Results
5 Summary & Future Work
6 Acknowledgments
Mishaal Aleem (UW) Visualization of DNS isoT Code Results June 17, 2015 7 / 22
Methodology: Set-up I
Compare single phase (droplet-free) case to multiphase(droplet-laden) cases
Compare multiphase cases of various Weber numbers
Weber NumberDimensionless number used where there is an interface between two different fluids,especially for multiphase flows with strongly curved surfaces [3]
We =ρv 2l
σ(1)
ρ = density of fluidv = velocityl = characteristic length (droplet diameter)
σ = surface tension
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Methodology: Set-up II
The visualizations look at the following droplet characteristics:
Droplet Surface (Volume of Fluid = 0.5)
Droplet Velocity (Calculated in post-processing)
The visualizations also consider the following qualities in the domain:
Turbulence Kinetic Energy
Turbulence Dissipation (∼SijSij)
Λ2
Enstrophy
Pressure Transport
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Methodology: Post-Processing
Velocity vectors of the droplets were calculated in Python using ascript from Michael Dodd, created for the 2015 JFM paper, modifiedfor the 3D case
Stored the velocity vector data as simple text files and opened themin the visualization tool
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Methodology: About VisIt
VisIt
Open Source,interactive, scalable,visualization, animationand analysis tool
Can be used to visualizescalar and vector fieldsdefined on 2D and 3Dmeshes
Designed to handle verylarge data sets
HDF5 Reader
Plug-in for to handle the.h5dns code output files
Developed by Darren Adams(University of Illinois)
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Methodology: VisIt Process
Creating Plots
Use the GUI to set upplots, including recordingcommands and savingthe corresponding outputPython script(“Command” option)
Using the recorded codesand referring to the VisItPython manual, createcomplete Python scriptsthat will make all plotsdesired (both Webernumber cases at varioustime steps)
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Outline
1 Objective
2 Background
3 Methodology
4 Results
5 Summary & Future Work
6 Acknowledgments
Mishaal Aleem (UW) Visualization of DNS isoT Code Results June 17, 2015 13 / 22
Initial Plots
Figure 1 : We=0.1, t=1, greendroplets and red Λ2 = -50iso-surfaces, full domain
Figure 2 : We=5, t=1.5, opaquewhite droplets and red Λ2 = -50iso-surfaces, background enstrophycontours, 1
64 domain
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Final Plots - Examples I
Figure 3 : We=0.1, t=2.25, whitetransparent droplets and redΛ2 = −50 iso-surfaces, full domain
Figure 4 : We=5, t=2.25, whitetransparent droplets, red Λ2 = −50iso-surfaces
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Final Plots - Examples II
Figure 5 : We=0.1, t=1.5, whitetransparent droplets, red TKE =0.01 iso-surfaces, grey dropletvelocity vectors, 1
64 domain
Figure 6 : We=5, t=1.5, whitetransparent droplets, red TKE =0.01 iso-surfaces, grey dropletvelocity vectors, 1
64 domain
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Final Plots - Examples III
Figure 7 : We=0.1, t=1.5, whitetransparent droplets, red Enstrophy= 150 iso-surfaces, grey dropletvelocity vectors, 27
8000 domain
Figure 8 : We=5, t=1.5, whitetransparent droplets, red Enstrophy= 150 iso-surfaces, grey dropletvelocity vectors, 27
8000 domain
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Final Plots - Examples III
Figure 9 : We=0.1, t=1.5, whitetransparent droplets, red ptr =0.015 iso-surfaces, blue ptr = -0.015iso-surfaces, grey droplet velocityvectors, 1
64 domain
We = 5 case is still beingcomputed on Hyak ...
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Outline
1 Objective
2 Background
3 Methodology
4 Results
5 Summary & Future Work
6 Acknowledgments
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Summary & Future Work
Summary of completed work:
Introduced to the research topic, CFD, the importance of visualization
Explored the fundamentals of CFD: Linux operating system, supercomputing
Understood the particular scenario being simulated in the code:droplet-laden isotropic turbulence
Updated a post-processing method to calculate droplet velocity vectors
After various iterations, created snapshots of the DNS code results givenvarying Weber numbers at 4 time steps using VisIt visualization software
Future work to be completed:
Create a 3-minute long animation that explores the quantities described
Include side-by-side videos of single-phase and multi-phase casesInclude side-by-side videos of various Weber numbers
Submit the animation to the American Physical Society - Gallery of FluidMotion 2015
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Outline
1 Objective
2 Background
3 Methodology
4 Results
5 Summary & Future Work
6 Acknowledgments
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Acknowledgements
Advisors− Prof. Antonino Ferrante
− Michael Dodd
Computing− University of Washington Hyak
− NSF XSEDE Maverick
References
[1] Why Infographics RuleForbeshttp://www.forbes.com/sites/tjmccue/2013/01/08/what-is-an-infographic-and-ways-to-make-it-go-viral/
[2] Statistics on Visual LearnersStudyMode - KdyiamShttp://www.studymode.com/essays/Statistics-On-Visual-Learners-1211593.html
[3] Weber NumberThe Engineering Toolboxhttp://www.engineeringtoolbox.com/weber-number-d 583.html
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