Line integral convolution Vorticity Finitetime Lyapunov exponent (backward) 
Regular grid:
NetCDF (440 MB)
Amira (460 MB)
VTK (448 MB)
Unstructured grid: VTK (4.83 GB) Citation Simulation of a viscous 2D flow around a cylinder. The fluid was injected to the left of a channel bounded by solid walls with a slip boundary condition. The simulation was done with Gerris flow solver and was resampled onto a regular grid. In the original simulation, the unstructured grid was adaptively discretized based on the vorticity. Over the course of the simulation, the characteristic vonKarman vortex street is forming. The image on the side shows a later time step, in which the street is fully formed. The vortices move with almost constant speed, except directly in the wake of the obstacle, where they accelerate. Regular grid resolution (X x Y x T): 640 x 80 x 1501 Simulation domain: [0.5, 7.5] x [0.5, 0.5] x [0, 15] Reynolds Number: 160 Kinematic viscosity: 0.00078125 Obstacle at (0,0) with radius: 0.0625 

Regular grid:
NetCDF (903 MB)
Amira (922 MB)
VTK (908 MB)
Unstructured grid: VTK (1.68 GB) Citation Simulation of a 2D flow generated by a heated cylinder. To solve the buoyancy problem, the Boussinesq approximation is used. The simulation was done with Gerris flow solver and was resampled onto a regular grid. The turbulent plume contains numerous small vortices that in part rotate around each other. Grid resolution (X x Y x T): 150 x 450 x 2001 Simulation domain: [0.5, 0.5] x [0.5, 2.5] x [0, 20] Obstacle at (0,0.15) with radius: 0.0625 
Vorticity Finitetime Lyapunov exponent (backward) 
Regular grid:
NetCDF (409 MB)
Amira (414 MB)
VTK (412 MB)
Unstructured grid: VTK (518 MB) Citation Simulation of a viscous 2D flow around two cylinders. The fluid was injected to the left of a channel bounded by solid walls with a slip boundary condition. The simulation was done with Gerris flow solver and was resampled onto a regular grid. In the original simulation, the unstructured grid was adaptively discretized based on the vorticity. Initially, a vortex street forms behind the first obstacle, which then flows around two corners. Behind each corner, a standing vortex forms. The latter one blocks half of the flow to the second obstacle, creating a onesided vortex street. Regular grid resolution (X x Y x T): 450 x 150 x 1501 Simulation domain: [0.5, 5.5] x [0.5, 1.5] x [0, 15] Reynolds Number: 160 Kinematic viscosity: 0.00078125 Obstacles at (0,0) and (3,1) both with radius: 0.0625 
Vorticity for Reynolds number: 160 Vorticity for Reynolds number: 320 Vorticity for Reynolds number: 640 Vorticity for Reynolds number: 6400 
Re = 160
Regular grid: NetCDF (17.7 GB) Amira (18.7 GB) VTK (17.9 GB) Unstructured grid: VTK (1.2 GB) Re = 320 Regular grid: NetCDF (17.6 GB) Amira (18.6 GB) VTK (17.8. GB) Unstructured grid: VTK (1.4 GB) Re = 640 Regular grid: NetCDF (17.6 GB) Amira (18.6 GB) VTK (17.9 GB) Unstructured grid: VTK (1.5 GB) Re = 6400 Regular grid: NetCDF (17.6. GB) Amira (18.6 GB) VTK (17.9 GB) Unstructured grid: VTK (1.9 GB) Citation Small ensemble of numerical simulations of an incompressible 3D flow around a half cylinder. Each ensemble member was simulated with a different Reynolds number (Re). The simulations were done with Gerris flow solver and were resampled onto a regular grid. In the original simulation, the unstructured grid was adaptively discretized based on the vorticity. This flow might be useful for ensemble visualization techniques or for tests on flows with varying degree of turbulence. Regular grid resolution (X x Y x T): 640 x 240 x 80 x 151 Simulation domain: [0.5, 7.5] x [1.5, 1.5] x [0.5, 0.5] x [0, 2] Reynolds Numbers: 160, 320, 640, 6400 
Vorticity in wake of the ship 
Regular grid:
NetCDF (12.5 GB)
Amira (13.1 GB)
VTK (12.7 GB)
Unstructured grid: VTK (2.1 GB) Citation Simulation of an incompressible 3D flow around a CAD model of the research vessel Tangaroa. The simulation was done with Gerris flow solver and a region of interest was resampled onto a regular grid. This is one of the example simulations of Gerris flow solver. In the original simulation, the unstructured grid was adaptively discretized based on the vorticity. Regular grid resolution (X x Y x T): 300 x 180 x 120 x 201 Simulation domain: [0.35, 0.65] x [0.3, 0.3] x [0.5, 0.3] x [0, 2] 
LIC with vorticity Finitetime Lyapunov exponent 
NetCDF (108 MB)
Amira (113 MB)
VTK (117 MB)
C++ code Matlab code Python code Citation The double gyre is a periodic timedependent vector field, in which a separating boundary oscillates horizontally between two oppositely rotating vortices. The flow was introduced by Shadden et al. and became the prime benchmark for finitetime Lyapunov exponents. The analytic formular has several parameters that steer magnitude (A), oscillation frequency (omega) and oscillation amplitude (eps). The resampled versions use the standard parameters listed below. The flow is also spatially periodic, which allows variations that contain saddles in the interior of the domain, such as the quad gyre with [0,2] x [1,1] x [0,10]. Grid resolution (X x Y x T): 256 x 128 x 512 Spacetime Domain: [0, 2] x [0, 1] x [0, 10] Standard parameters: A = 0.1, omega = pi/5, eps = 0.25 
Vortex corelines in the Beads problem, image from here 
NetCDF (775 KB)
Amira (13.8 MB)
VTK (837 KB)
C++ code Matlab code Python code Citation Wiebel et al. studied particle motion in a rotating petridish, which proved to become a challenging benchmark for vortex coreline extraction, since the vortex center is moving on a circular path, which is not covered by Galilean invariant vortex extractors. An analytic approximation to this flow was for instance given by Weinkauf and Theisel, which is provided here. The image on the side shows pathlines that are attracted to the true coreline (blue), compared to a Galilean invariant coreline extraction (green). Grid resolution (X x Y x T): 128 x 128 x 512 Simulation domain: [2, 2] x [2, 2] x [0, 2pi] 

NetCDF (54 MB)
Amira (56.3 MB)
VTK (57.5 MB)
C++ code Matlab code Python code Citation This analytic data set contains four vortices. The flow is made unsteady by performing a uniform reference frame rotation. User parameters are a scaling factor of the magnitude (scale) and the speed of the reference frame rotation (al_t). The vortex centers are positioned at t=0 at ± 2^(1/2). The construction of the data set is described here in Section 7.2. This data set is a good benchmark for reference frame invariant flow feature extraction, since simple Galilean invariance is not enough. Grid resolution (X x Y x T): 128 x 128 x 512 Spacetime domain: [2, 2] x [2, 2] x [0, 2pi] Standard parameters: scale = 1, al_t = 1 

NetCDF (30.1 MB)
Amira (31 MB)
VTK (29.9 MB)
C++ code Matlab code Python code Citation This analytic vector field describes the phase space of a duffing oscillator with forcing and damping. For the standard parameters, the vector fields contains a saddletype periodic orbit. Grid resolution (X x Y x T): 128 x 128 x 512 Spacetime domain: [2, 2] x [2, 2] x [0, 4] Standard parameters: alpha = 0.25, beta = 0.4 
Line integral convolution 
NetCDF (311 MB)
Amira (317 MB)
VTK (313 MB)
Citation This synthetic vector field represents a simple model of a vonKarman vortex street generation and was constructed by Jung, Tel and Ziemniak as cogradient to a stream function. The obstacle is positioned at (0,0) and has a radius=1. In the LIC image on the side, the flow in the interior of the obstacle has not been set to zero. Note that only two vortices are present at the same time. In the files above, we sampled four periods onto a regular grid. Grid resolution (X x Y x Z): 450 x 200 x 500 Spatial domain: [3, 7] x [2, 2] x [1.107, 5.535] 

NetCDF (16.9 MB)
Amira (17.7 MB)
VTK (17.0 MB)
Citation This synthetic model of a tornado was created by Roger Crawfis and was made available as C code here. We scaled the flow to a larger domain and sampled it onto a regular grid. If higher resolutions are required, simply run the C code. Grid resolution (X x Y x Z): 128 x 128 x 128 Spatial domain: [10, 10] x [10, 10] x [10, 10] 