knowledge-assisted visualization of turbulent combustion simulations
DESCRIPTION
Knowledge-Assisted Visualization of Turbulent Combustion Simulations. Chaoli Wang, Hongfeng Yu, Kwan-Liu Ma. Turbulent combustion simulations. Direct numerical simulations Time-varying, multivariate data 800 * 686 * 217, 450MB 53 time steps 4 variables: mixfrac , chi , HO 2 , and OH - PowerPoint PPT PresentationTRANSCRIPT
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Knowledge-Assisted Visualization of Turbulent Combustion Simulations
Chaoli Wang, Hongfeng Yu, Kwan-Liu Ma
![Page 2: Knowledge-Assisted Visualization of Turbulent Combustion Simulations](https://reader036.vdocuments.mx/reader036/viewer/2022062407/56812e3a550346895d93aa95/html5/thumbnails/2.jpg)
Turbulent combustion simulations
• Direct numerical simulations
• Time-varying, multivariate data – 800 * 686 * 217, 450MB– 53 time steps
– 4 variables: mixfrac, chi, HO2, and OH
– 93GB in total
![Page 3: Knowledge-Assisted Visualization of Turbulent Combustion Simulations](https://reader036.vdocuments.mx/reader036/viewer/2022062407/56812e3a550346895d93aa95/html5/thumbnails/3.jpg)
Visualization-specific task
• Scientific interests– Observe variable relationships close to the mixfrac surface– Bring out more the lower values of other variables
The mixed rendering of the mixfrac (isovalue = 0.2) and the HO2 variables
![Page 4: Knowledge-Assisted Visualization of Turbulent Combustion Simulations](https://reader036.vdocuments.mx/reader036/viewer/2022062407/56812e3a550346895d93aa95/html5/thumbnails/4.jpg)
Challenges
• Data ranges of other variables close to the surface are unknown
• Only value-based transfer function may bring out undesired visualization contents
• Lack of control over the amount of information shown around the surface
![Page 5: Knowledge-Assisted Visualization of Turbulent Combustion Simulations](https://reader036.vdocuments.mx/reader036/viewer/2022062407/56812e3a550346895d93aa95/html5/thumbnails/5.jpg)
Our solution
create distancevolume
plot partialhistogram
specify transferfunction
preprocessing
compute voxelimportance
volumerendering
distance threshold d
runtime
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Transfer function specification
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d = 0.02 d = 0.05
Visualization result
![Page 8: Knowledge-Assisted Visualization of Turbulent Combustion Simulations](https://reader036.vdocuments.mx/reader036/viewer/2022062407/56812e3a550346895d93aa95/html5/thumbnails/8.jpg)
d = 0.10 d = 0.20
Visualization result
![Page 9: Knowledge-Assisted Visualization of Turbulent Combustion Simulations](https://reader036.vdocuments.mx/reader036/viewer/2022062407/56812e3a550346895d93aa95/html5/thumbnails/9.jpg)
Video demos
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Summary
• Knowledge-assisted visualization– Domain knowledge: isovalue, ranges of intere
sts– Derived knowledge: distance volume and parti
al histogram– Importance-driven visualization
• Future work– Time-varying, multivariate data compression
• Utilize domain knowledge• Visualization-specific compression
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Thank you!
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Extra slides
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Visualization-specific compression
• Regions of interest are around the given surface
• Data precision can thus vary according to the distance to the surface
• Our solution– Non-uniform quantization– Space-time coherence utilization– Decompression on the fly using graphics
hardware
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Compression result
• Compression ratio: ~20x– Each voxel only uses less than 2 bits per vari
able on the average
• Advantages– Reduce data transfer among disk to main me
mory, and main memory to video memory– Fast offline compression and online decompre
ssion– Preserve fine details near the surface and mai
ntain the overall image quality
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Compression result
original compressed (~20x)
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Compression result
original compressed (~20x)