Simulating an oblique drop impact on a shallow liquid pool with FluidX3D @ProjectPhysX

Uploaded February 2020 | Updated September 2026, 2 weeks ago

FluidX3D is a real time 3D fluid simulation based on the lattice Boltzmann method. It is written in OpenCL C (GPU code) and optimized to the physical limit (video memory bandwith, ~520GB/s).

All demonstrations are simulated and visualized on a Nvidia Titan Xp. The video is sped up by 16x, so it was about 10 minutes of compute time for all simulations combined. Graphics are done with the OpenCL C version of Line3D, the fastest graphics engine ever written for primitive shapes like lines, dots and circles. It can handle up to 2 billion lines per second.

The free surface is done with the volume-of-fluid (VoF) extension to LBM. It allows simulating free surfaces with a sharp interface layer.
The volume force (gavity) is implemented with the Gou forcing scheme.

Visualization of the surface is done with the marching cubes algorithm (implemented in OpenCL C).
paulbourke.net/geometry/polygonise

Hardware Setup:
CPU: Intel Core i7-8700K @ 4.5GHz all core
GPU: Nvidia Titan Xp
RAM: 2x8GB Corsair Vengeance LPX DDR4 3200MHz CL16
Mainboard: ASUS ROG STRIX Z370-I GAMING
SSD 1: Samsung 970 PRO 512GB
SSD 2: Samsung 860 EVO 1TB
CPU Cooler: Cooltek LP53
PSU: Corsair SF600
Housing: Fractal Design Node 202

Timestamps:
0:00 - Intro
0:04 - 0 degree
0:12 - 15 degree
0:19 - 30 degree
0:26 - 45 degree
0:33 - 60 degree
0:39 - 75 degree

More information at projectphysx.de

Simulating an oblique drop impact on a shallow liquid pool with FluidX3D

$I wrote this Real Time RayTracer from Scratch in 1 Week. Hybrid Rasterization + Raytracing Demo I wrote this real time OpenCL raytracer in one week from scratch and without any external libraries. Timestamps 0:00 Intro 0:02 1 Sphere 0:29 64 Spheres 1:34 Triangles - reflection 2:23 Triangles - reflection+refraction 4:10 How it works 4:39 Outro This project was first inspired by this awesome video from the YouTuber NamePointer: https://youtu.be/lKIytgt3KXM It is surprisingly easy: From the camera, shoot a ray through every pixel. Reflect the ray off the first surfaces in its way, reflect the reflection 2 more times. Finaly when the reflected ray hits the skybox, mix all the colors to paint the original pixel with. The GPU does this for all 2 Million pixels on the screen in parallel. I implemented: - ray-sphere intersection - ray-triangle intersection (Möller-Trumbore algorithm) - reflection as well as refraction with Snells law - hybrid rasterize-raytrace approach: First rasterize triangles and instead of the pixel color save their IDs in the bitmap. Then the raytrace kernel looks up the ID to immediately get the first intersecting triangle. This way the first intersection and reflection are basically free, so the shiny Stanford bunny with 70k triangles runs at 200+fps. Because I wrote the raytracer in OpenCL, it runs on any OpenCL capable device (GPUs, CPUs, even my Samsung phone). No proprietary RTX hardware required. Music: Unfound - Promenade$

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$Liquid metal on a speaker (Slow Mo Guys), but as simulation The Slow Mo Guys did a video about liquid gallium on a vibrating speaker membrane, wondering what it would look like in simulation: https://youtu.be/A9J1gkw9BI0?t=135 Well, I can now simulate liquid metal with my FluidX3D software, and it even runs in real time. Note that I couldnt do the simulation with 1:1 the physical parameters of liquid gallium, as it just wouldnt be stable. The parameters that I used are (in lattice units): box size 128x128x96, density rho=1, kinematic shear viscosity nu=0.01, force per volume f=0.0005, surface tension sigma=0.005, peak velocity of speaker membrane u=0.09, frequency of speaker freq=0.01. The raytracer here does reflections only at a depth of 2, so 1-3 rays per pixel. The simulation software used is FluidX3D, an OpenCL implementation of the lattice Boltzmann method. FluidX3D runs at peak hardware efficiency on the worlds fastest data-center GPUs, on gaming GPUs and CPUs and it even runs my smartphone. The fluid simulation is done with the lattice Boltzmann method (LBM) with the Volume-of-Fluid (VoF) extension and piecewise linear interface construction (PLIC) for surface tension. VoF-LBM provides a 3D grid with fluid fill levels, used as isovalues for marching-cubes, which generates a contiguous triangle mesh representing the water surface. Marching-cubes: http://paulbourke.net/geometry/polygonise/ Raindrop simulations: https://doi.org/10.1186/s43591-021-00018-8 Volume-of-Fluid: https://doi.org/10.3390/computation10020021 Esoteric-Pull: https://doi.org/10.3390/computation10060092 FP32/FP16 mixed precision: https://www.researchgate.net/publication/362275548_Accuracy_and_performance_of_the_lattice_Boltzmann_method_with_64-bit_32-bit_and_customized_16-bit_number_formats FluidX3D: https://doi.org/10.15495/EPub_UBT_00005400 With raytracing I shoot light rays from the camera through the 3D isogrid. For each grid cell that a ray traverses, I run marching-cubes to generate the triangles on-the-fly, then check for ray-triangle intersections with any of these triangles. If the ray intersects, I dont use the flat-face-surface nromal of the triangle, as this would lead to visual artifacts on the reflected/refracted rays. Instead, I interpolate the surface normal at the intersection point in order to have a smoothly appearing surface. How does surface normal interpolation work with marching-cubes? I get the normals directly at the lattice points with gradient (central derivative) on the isogrid, then do trilinear interpolation to the intersection point. This is only computed once, after the intersection point has been found. The 3D lattice that the LBM provides already is one of the ideal acceleration structures for raytracing. Any ray only has to check for possible intersections with isosurface triangles contained within the traversed grid cells. This makes it - when the lattice is not too large - even run in real time on any OpenCL 1.2 capable GPU with enough memory. No RTX or professional GPU required. Also see the most realistic raindrop simulation ever done: https://youtu.be/9Rfu9ZqW894 Timestamps: 0:00 intro 0:03 simulation start 0:29 almost melts the GPU 1:15 pressure waves from speaker membrane 1:32 isosurface mesh generation 2:15 outro #FluidX3D #OpenCL #Raytracing #GPU #LBM$

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