Download A Case Study in the Visualization of Supernova Simulation Data

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

Cytoplasmic streaming wikipedia, lookup

Transcript
A Case Study in the
Visualization of
Supernova Simulation Data
Ed Bachta
Visualization and Interactive Spaces Lab
Overview





Introduction
Lagrangian-Eulerian Advection
Software Design
Results
Future Work
A Core-collapse Supernova








Begins with a star of 8+ solar masses
Eventually, fusion produces Fe in the core
Pressure from fusion loses to gravitation
Material falls inward, increasing density
Neutrinos radiated at a rate of 1057 /s
Strong force halts collapse
Remaining material rebounds off the core
Shock wave carries material away from the core
Simulation





Doug Swesty & Eric Myra, SUNY Stony Brook
Exploring the role of convection
Radiation hydro code scales to 1000s of procs
2 spatial dimensions (soon to be extended to 3)
20 groups of neutrinos at different energies
Lagrangian-Eulerian Advection



A process for visualizing vector
fields, valid for unsteady flows
Noise is advected along the
flow, generating an image as
output
Results


Single frames portray
instantaneous flow
Animations simulate motion of
material in flow
Vector plot
LEA
“Lagrangian-Eulerian Advection for
Unsteady Flow Visualizaion”
v
Noise at t-1





Lagrangian
step
Eulerian
step
Particles seeded randomly each iteration
Backward integration finds upstream cell
Color of upstream cell advected forward
Results blended temporally with bias toward most recent
Jobard, Erlebacher, Hussaini (IEEE Vis & CG 2002 [8:3])
LEA Animated



Applied to velocity
Propagation of light and
dark areas indicates
direction of flow
Areas where noise remains
have near-zero velocities
Software



Vis modules provided by the Visualization Tool
Kit (VTK)
LEA filter for VTK developed at the Swiss
National Supercomputing Centre
Scripts programmed in Python
Results

Combination of LEA with:

Scalar data representations



Via colormaps
Via iso-contours
Vector data comparisons

Via visualization of dot products
LEA & Scalars
Velocity & Entropy

Shows the development of
regions of high entropy in
upper convective zones
LEA & Iso-Contours
LEA & Optical Depth

The iso-contour where optical
depth = 1 describes the surface
of last scattering
1
8
2
3


Generated for each energy group
Our results show that these
contours vary with energy group
and evolve along with the shock
LEA & Dot Products
Advective vs. Radiative NeutrinoFlux

Radiative neutrino flux


Advective neutrino flux


Tendency to propagate outward
Effect of convection
Dot product indicates:



“Constructive” flux
“Destructive” flux
Orthogonal flux
Comparison Over Energy
Comparison of Gradients

Lagrangian multipliers:





∂rf (r) = λ ∂rg(r)
Describes a set of points where the iso-contours of f(r)
and g(r) are tangential
A positive λ indicates parallel gradients
A negative λ indicates anti-parallel gradients
Very similar to our dot product analysis

The dot product reveals orthogonal conditions
Entropy & Temp.

Using our visualization
scheme, we can see:




Where the gradients are ||
Where they are anti-||
Where they are orthogonal
How this relates to the flow
of a vector field
Future Work



Extending the framework to support iteration
Developing new visualization techniques
Enabling remote visualization


Intended for batch processing
Investigating Web Services