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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

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a case study in the visualization of supernova simulation data

A Case Study in the Visualization of Supernova Simulation Data

Ed Bachta

Visualization and Interactive Spaces Lab

overview
Overview
  • Introduction
  • Lagrangian-Eulerian Advection
  • Software Design
  • Results
  • Future Work
a core collapse supernova
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
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
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
“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
LEA Animated
  • Applied to velocity
  • Propagation of light and dark areas indicates direction of flow
  • Areas where noise remains have near-zero velocities
software
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
Results
  • Combination of LEA with:
    • Scalar data representations
      • Via colormaps
      • Via iso-contours
    • Vector data comparisons
      • Via visualization of dot products
velocity entropy
Velocity & Entropy
  • Shows the development of regions of high entropy in upper convective zones
lea optical depth
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
advective vs radiative neutrinoflux
Advective vs. Radiative NeutrinoFlux
  • Radiative neutrino flux
    • Tendency to propagate outward
  • Advective neutrino flux
    • Effect of convection
  • Dot product indicates:
    • “Constructive” flux
    • “Destructive” flux
    • Orthogonal flux
comparison of gradients
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
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
Future Work
  • Extending the framework to support iteration
  • Developing new visualization techniques
  • Enabling remote visualization
    • Intended for batch processing
    • Investigating Web Services