Visualization Projects

Encounters between rod-like phytoplankton cells in the ocean

Encounters between rod-like phytoplankton cells in the ocean

Physical scenario: Numerical modeling of encounters between rod-like phytoplankton cells in the ocean.
Simulations: J.-A. Arguedas-Leiva, C. C. Lalescu, M. Wilczek (MPI for Dynamics and Self-Organisation, MPCDF and University of Bayreuth)

Simulation code: TurTLE (Turbulence Tools: Lagrangian and Eulerian)

Visualisation approach (C. Lalescu, MPCDF, 2022):
  • main objective: visualisation of plankton dynamics in turbulence.
  • Intense vorticity structures are shown with a volume rendering - darker regions correspond to faster rotation of the fluid.
  • Cylinders represent individual rods (width increased tenfold for visibility).
  • tool: VTK (through Python wrapper)
  • animation (mp4, 58 MB)

References and further reading:
  • José-Agustín Arguedas-Leiva, Jonasz Słomka, Cristian C. Lalescu, Roman Stocker, and Michael Wilczek.Elongation enhances encounter rates between phytoplankton in  turbulence, PNAS 119 (32) e2203191119 (2022)
IAEA Crowdsourcing Challenge for Materials for Fusion Technology (Winning Team)

IAEA Crowdsourcing Challenge for Materials for Fusion Technology (Winning Team)

Physical scenario: Analysis of the wall material for the plasma vessel in a future fusion power plant simulating radiation damage in the crystalline structure of the material.
Simulations: U. von Toussaint, J. Dominguez   (Max-Planck-Institut für Plasmaphysik)

Main Codes:
  • Quippy (descriptor vectors) based on FORTRAN, Python, libAtoms and QUIP
  • Ovito (Interactive visualization of MD-data)
  • KDTREE2
  • voro++
Visualization approach (M. Rampp, M. Compostella - MPCDF, 2018):
  • main objectives: development of Python scripts for the visualization of defects in the lattice of the Tungsten and Steel crystals. Use of different RGB colour channels for the representation of different descriptors in the lattice. The final colour of each atom, given by the sum in the different channels, is shown together with cloud-like regions depicting voids in the damaged crystal.
  • tool: VisIt
References and further reading:
  • U. von Toussaint, F. J. Dominguez-Gutierrez, M. Compostella, M. Rampp. FaVAD: A software workflow for characterisation and visualizing of defects in crystalline structures  arXiv:2004.08184
Visualization of Turbulence in Direct Numerical Simulations of Fluids

Visualization of Turbulence in Direct Numerical Simulations of Fluids

Physical scenario: Time-dependent, direct numerical simulations of the Navier-Stokes equation in three dimensions.
Simulations: C. Lalescu and M. Wilczek (MPI for Dynamics and Self-Organization)
Simulation Code: BFPS (Big Fluid and Particle Simulator)
Visualization approach (M. Albert, M. Rampp - MPCDF - & C. Lalescu, M. Wilczek - MPI-DS -, 2017-2018):
  • immersive visualization of the flow field ("strength" of turbulence is visualized by iso-surfaces of the the vorticity of the velocity field) by co-moving the camera along the trajectories of passively advected test particles.
  • tool: VisIt
  • Download HD movie (1920x1080, 72 MB, MP4).
  • continued in virtual reality in the context of a collaboration LRZ/MPCDF/MPI-SD
References and further reading:
Visualization of near-field effects in Quantum Nanoplasmonic Dimers

Visualization of near-field effects in Quantum Nanoplasmonic Dimers

Physical scenario: Dynamics of a dimer of Quantum Plasmonic Nanoparticles with 2x297 sodium atoms exposed to an external laser pulse.
Simulations: R. Jestädt, H. Appel (MPI for the Structure and Dynamics of Matter)
Simulation Code: OCTOPUS (Kohn–Sham density functional theory and time-dependent density functional theory calculations)
Visualization approach (M. Compostella, M. Rampp - MPCDF - & H. Appel - MPSD -, 2017):
  • main objectives: development of Python scripts for the visualization of real-time dynamics of complex systems exposed to external electromagnetic fields. Reconstruction of the laser pulse adopted in the OCTOPUS code. Possibility to compose several different views, static images and text labels into the same canvas. Automatic generation of frames for the entire time series running a single command line. Flexibility to produce an introductory movie that presents the physical context before showing the results of the time series.
  • tool: VisIt
References and further reading:
  • A. Varas, P. García-González, J. Feist, F.J. García-Vidal and A. Rubio, Quantum plasmonics: from jellium models to ab initio calculations, Nanophotonics, 5(3), pp. 409-426 (2017) (10.1515/nanoph-2015-0141)
  • A. Castro, H. Appel, Micael Oliveira, C.A. Rozzi, X. Andrade, F. Lorenzen, M.A.L. Marques, E.K.U. Gross, and A. Rubio, Octopus: a tool for the application of time-dependent density functional theory, Phys. Stat. Sol. B 243 2465-2488 (2006) (10.1002/pssb.200642067)
Reaction of CO2 molecule with CaO (001) surface

Reaction of CO2 molecule with CaO (001) surface

Physical scenario:
Adsorption of a CO2 molecule onto a CaO surface.
Simulations: A. Mazheika, S. V. Levchenko & M. Scheffler (Fritz-Haber-Institut)
Simulation Code: FHI-aims (Fritz Haber Institute ab initio molecular simulations)
Visualization approach (M. Compostella & M. Rampp, MPCDF, 2017):
  • main objectives: interactive data exploration, visualization of the modifications in the electron density during the interaction of a CO2 molecule with a CaO surface.
  • tools: VisIt, Blender
  • Download movie (1920x1080, 25 MB, MP4).
References and further reading:
Evolution of electron localization functions during molecular scattering

Evolution of electron localization functions during molecular scattering

Physical scenario: Top: scattering of a proton off a C2H4 molecule. Bottom: effect of the propagation of a laser pulse through a molecule of azulene (C10H8). Simulations: H. Appel (MPI for the Structure and Dynamics of Matter) Simulation Code: OCTOPUS (Kohn–Sham density functional theory and time-dependent density functional theory calculations) Visualization approach (M. Compostella & M. Rampp, MPCDF, 2016):
  • main objectives: interactive data exploration, visualization of the evolution of electron localization functions during molecular scattering and during interaction with a laser pulse.
  • tool: VisIt
References and further reading:
  • X. Andrade, D. A. Strubbe, U. De Giovannini, A. H. Larsen, M. J. T. Oliveira, J. Alberdi-Rodriguez, A. Varas, I. Theophilou, N. Helbig, M. Verstraete, L. Stella, F. Nogueira, A. Aspuru-Guzik, A. Castro, M. A. L. Marques, and A. Rubio, Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems, Physical Chemistry Chemical Physics 17 31371-31396 (2015) (arXiv:1501.05654)
  • A. Castro, H. Appel, Micael Oliveira, C.A. Rozzi, X. Andrade, F. Lorenzen, M.A.L. Marques, E.K.U. Gross, and A. Rubio, octopus: a tool for the application of time-dependent density functional theory, Phys. Stat. Sol. B 243 2465-2488 (2006) (10.1002/pssb.200642067)
  • M.A.L. Marques, Alberto Castro, George F. Bertsch, and Angel Rubio, octopus: a first-principles tool for excited electron-ion dynamics, Comput. Phys. Commun. 151 60-78 (2003) (10.1016/S0010-4655(02)00686-0)
  • Theory Department at MPSD
Neutrino-driven core collapse supernova (Type-II) explosion in 3D

Neutrino-driven core collapse supernova (Type-II) explosion in 3D

Astrophysical scenario: Neutrino-driven explosion of a low-mass iron-core star
Simulation: T. Melson, A. Marek, F. Hanke & H.-Th. Janka (MPI for Astrophysics)
Simulation Code: VERTEX (3D Hydrodynamics & Boltzmann neutrino transport)
Visualization approach (E. Erastova & M. Rampp, RZG, 2014):
  • main objectives: interactive data exploration, visualization of the dynamics of large-scale hydrodynamical instabilities ("SASI")
  • tool: VisIt
References and further reading:
Direct numerical simulations of (decaying) turbulence in Keplerian flow at Re=200.000

Direct numerical simulations of (decaying) turbulence in Keplerian flow at Re=200.000

Physical scenario: Turbulence in an astrophysical disc with Keplerian velocity profile
Simulation: L. Shi, M. Avila, B. Hof. (FAU Erlangen, IST Austria, Max Planck Institute for Dynamics and Self-Organization)
Simulation Code: NSCOUETTE (Pseudo-spectral Navier-Stokes solver)
Visualization (M. Rampp, RZG, 2014-2016):
  • main objectives: interactive data exploration, visualization of the turbulent intensity (streamwise vorticity)
  • tool: VisIt
  • Download movie (1920x1080, 13 MB, MPEG4).
References:
Neutrino-driven core collapse supernova (Type-II) dynamics in 3D

Neutrino-driven core collapse supernova (Type-II) dynamics in 3D

Astrophysical scenario: Neutrino-driven explosion of a massive star Simulation: F. Hanke, A. Marek, B. Müller, & H.-Th. Janka (MPI for Astrophysics) Simulation Code: VERTEX (3D Hydrodynamics & Boltzmann neutrino transport) Visualization approach (E. Erastova & M. Rampp, RZG, 2013):
  • main objectives: interactive data exploration, visualization of the dynamics of large-scale hydrodynamical instabilities ("SASI")
  • tool: VisIt
  • youtube movie
References:
  • F. Hanke, B. Mueller, A. Wongwathanarat, A. Marek, H.-Th. Janka: SASI Activity in Three-Dimensional Neutrino-Hydrodynamics Simulations of Supernova Cores (arXiv:1303.6269)
  • Stellar Hydrodynamics at MPA
Visualization of bird migration

Visualization of bird migration

Bird migration is studied at the Max Planck Institute for Ornithology. Data from GPS loggers carried by birds are correlated with wind and topography data to better understand the migration.
This animated visualization first shows points in 3d space only (i.e. raw data from a GPS logger). The points are then connected to represent the migration path. Then, the underlying topography is added followed by arrows representing the wind field.
The second part of the animation is fully time dependent. The camera follows the bird, and it becomes evident that the bird reacts to changes in the wind field and to the topography.
Download movie (1280x720, 55 MB, MPEG4).
More information: Visualization by K. Reuter, RZG.
Core collapse supernova (Type-II) explosion dynamics in 3D

Core collapse supernova (Type-II) explosion dynamics in 3D

Astrophysical scenario: Neutrino-driven explosion of a massive star Simulation: F. Hanke, A. Marek, B. Müller, & H.-Th. Janka (MPI for Astrophysics) Simulation Code: PROMETHEUS (3D Hydrodynamics) with simplified neutrino physics. Visualization approach (E. Erastova & M. Rampp, RZG, 2011):
  • main objectives: interactive data exploration, visualization of the dynamics of large-scale hydrodynamical instabilities ("SASI")
  • 400 x 60 x 120 zones on a non-uniform, time-dependent polar grid, approx. 1000 HDF5 output files a 1 GB
  • tool: VisIt
References:
Visualization of Tracer Particles in Turbulent Magnetohydrodynamic Convection

Visualization of Tracer Particles in Turbulent Magnetohydrodynamic Convection

Physical Scenario: Turbulent convection of an electrically conducting fluid or plasma.
Simulation: J. Pratt, W.-C. Müller (Max-Planck-Institute for Plasma Physics).
Visualization: Passive tracer particles and a background field are displayed simultaneously as functions of time. Visualization approach by K. Reuter (RZG) using VisIt.
Visualization and Quantitative Analysis of Point Data from Smoothed-Particle Hydrodynamics (SPH) Simulations

Visualization and Quantitative Analysis of Point Data from Smoothed-Particle Hydrodynamics (SPH) Simulations

Challenge Output from SPH simulations is usually given by point clouds with millions of entities (billions in future), each of which contains local information on physical quantities such as temperature or mass density. While specialized tools produce visually appealing volume renderings (e.g. SPLOTCH), most state-of-the-art visualization packages fail to handle point clouds properly.
On the other hand, these packages offer a plethora of attractive possibilities for quantitative data analysis of gridded data, e.g., for producing contour plots on arbitrary planes through the simulation domain.
Solution
A code package was developed at RZG to create unstructured grids from SPH point data.  The fast three dimensional Delaunay triangulation provided by qhull is used.  The resulting unstructured grid is written together with the point data in a legacy file format which can be read by applications such as Paraview or VisIt.  A serial domain decomposition technique is implemented to keep the memory footprint of the program low.  Hence, datasets of arbitrary size can be handled.
Cooperation Klaus Reuter (RZG), Claudia Simion (TUM), Claudio Dalla Vecchia (MPE), Markus Rampp (RZG), Sadegh Khochfar (MPE) Source code The code package may be obtained upon request for use on RZG systems. References
Mixing Instabilities in Type-II Supernova Explosions

Mixing Instabilities in Type-II Supernova Explosions

Astrophysical scenario: 3D-Simulations of Mixing Instabilities in Type-II Supernova Explosions
Simulation: N. Hammer, H.-Th. Janka, E. Müller (MPI for Astrophysics)
Simulation Code: PROMETHEUS
Visualization approach (M. Rampp, 2009/2010):
  • main objectives: exploration, quantitative analysis and visualization of the dynamics and morphology of the nuclear composition
  • rectilinear (polar) grids with 500x180x360 zones per timestep
  • tool: VisIt ("multi-channel" volume rendering, isosurfaces, 2D-slices)
Results: References:
Merger of a white dwarf binary system

Merger of a white dwarf binary system

Astrophysical scenario: Merger of a white dwarf binary system as a Type Ia supernova progenitor
Simulation: R.Pakmor et al. (MPI for Astrophysics)
Simulation Code: GADGET
Visualization approach (E. Erastova, M. Rampp, 2009/2010):
  • approx. 2 Million SPH particles per timestep
  • tool: Splotch (ray-casting tailored to visualization of SPH data)
Results: References:
Merging Neutron Stars

Merging Neutron Stars

Astrophysical scenario: Dynamic merger phase of a binary neutron star system Simulation: A.Bauswein & H.-Th.Janka (MPI for Astrophysics) Simulation Code: relativistic smoothed particle hydrodynamics (SPH) code by Oechslin et al.
Visualization approach (M. Rampp, 2009):
  • approx. 500000 SPH particles per timestep
  • tools: Splotch (ray-casting tailored to visualization of SPH data), VisIt
Results: References:
Impact of Type Ia Supernovae on Binary Companions

Impact of Type Ia Supernovae on Binary Companions

Astrophysical scenario: Impact of type Ia supernova on its main sequence binary companion
Simulation: R.Pakmor (MPI for Astrophysics)
Simulation Code: GADGET
Visualization approach (M. Rampp, R.Bruckschen, RZG, R.Pakmor, 2009):
  • approx. 9 Million SPH particles per timestep
  • tool: Splotch (ray-casting tailored to visualization of SPH data)
Results: References:
MHD Turbulence Simulations

MHD Turbulence Simulations

Physical scenario: study of basic theoretical aspects of turbulence in plasmas in the framework of magnetohydrodynamics (MHD) Simulation: W.C. Müller (IPP) Simulation Code: MHD Visualization approach (S.Malapaka, IPP & R.Bruckschen, RZG, 2008/2009):
  • main objectives: exploration, analysis and visualization of massive datasets
  • rectilinear (cartesian) grids with 10243...20483 zones
  • tool: VisIt (parallel ray-casting, isosurfaces, ...)
References: Independent Max-Planck Junior Research Group "Computational Studies of Turbulence in Magnetized Plasmas"'
Core collapse supernova (Type-II) explosion

Core collapse supernova (Type-II) explosion

Astrophysical scenario: neutrino-driven explosion of a massive star
Simulations: A.Marek, R. Buras, H.Th.Janka (MPI for Astrophysics)
Simulation Code: VERTEX (Boltzmann neutrino radiation hydrodynamics in 2D)
Visualization approach (M. Rampp, RZG, 2008/2009):
  • main objectives: interactive data exploration, visualization of the dynamics of large-scale hydrodynamical instabilities ("SASI")
  • 500 x 128 zones on a non-uniform, time-dependent polar grid
  • tool: VisIt (parallel ray-casting)
Results: References:
Turbulence in Fusion Plasmas

Turbulence in Fusion Plasmas

Physical scenario: fluctuations in a thermonuclear fusion plasma (tokamak geometry) Simulation: M.Püschel, F.Jenko (IPP) Simulation Code: GENE (gyrokinetic turbulence) Visualization approach (R.Bruckschen & J.Mejia, RZG, 2007):
  • main objectives: animation and interactive analysis of time-dependent data sets (3D impression, dynamics), development of a tailored visualization toolkit
  • mapping of flux-tube coordinates to real space (torus) sampled by 1280 x 480 x 96 grid points
  • out-of-core shader-based method
  • point-based pseudo volume rendering
  • Java application (JOGL API) for portability
References: Helmholtz-University Young Investigators Group "Theory and ab-initio simulation of plasma turbulence"
Thermonuclear Supernova (Type-Ia) explosion

Thermonuclear Supernova (Type-Ia) explosion

Astrophysical scenario: thermonuclear deflagration of a white dwarf star Simulation: F.Röpke, W. Hillebrandt (MPI for Astrophysics) Simulation Code: SUCCESs (finite volume hydrodynamics + level-set method for thermonuclear burning fronts) Visualization approach (R.Bruckschen, RZG, 2007):
  • main objectives: combined volume rendering of the complete time-dependent dataset
    • stellar structure: scalar density field on the moving, rectilinear 10243 grid
    • deflagration front: level set renderend as a semi-transparent cloud of points
  • out-of-core rendering with hybrid display (point based/volume rendering)
  • interactive preview, movie mode with high fidelity transparency
References:
The "Millenium simulation" (formation and evolution of structure in the universe)

The "Millenium simulation" (formation and evolution of structure in the universe)

Astrophysical scenario: formation and evolution of structure in the universe Simulation: V.Springel, S.White (MPI for Astrophysics) Simulation code: GADGET-2 (cosmological N-body/SPH), ~ 1010 particles in 3D Visualization approach (R.Bruckschen, RZG, 2006):
  • main objectives: interactive exploration ("fly-through") of individual time-slices at full resolution
  • visibility-based out-of-core method using a spatial subdivision scheme
  • quantization based on local bounding boxes (low error)
  • GPU shader based de-quantification and rendering
References:
  • V. Springel et al. Simulations of the formation, evolution and clustering of galaxies and quasars. Nature (2005).
  • Galaxy Formation Group at MPA
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