knowledge-assisted visualization of turbulent combustion simulations chaoli wang, hongfeng yu,...

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Knowledge-Assisted Visualization of Turbulent Combustion Simulations Chaoli Wang, Hongfeng Yu, Kwan- Liu Ma

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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, HO2, and OH

– 93GB in total

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

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

Our solution

create distancevolume

plot partialhistogram

specify transferfunction

preprocessing

compute voxelimportance

volumerendering

distance threshold d

runtime

Transfer function specification

d = 0.02 d = 0.05

Visualization result

d = 0.10 d = 0.20

Visualization result

Video demos

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

Thank you!

Extra slides

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

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

Compression result

original compressed (~20x)

Compression result

original compressed (~20x)