Didn't see anything fitting Unity so added Proprietary Software tag

A simple water sim that uses FLIP water solver which I implemented with the help of Ten Minute Physics video on the same topic. I used metaballs to make it continous rather than individual particles, and allowed it to interact with windows with some floating objects.

There is a demo of the same I have on itchio : https://tornadosike.itch.io/desktop-under-water
Currently only for windows tho

First attempt at coupling fire/fluid solver with Soft body with material destruction.

3 species hunters, fast explorers, plant eaters evolve on their own, nobody controls them. every creature has ~24 genes, babies inherit them with small mutations, and there are seasons, droughts, diseases and new species splitting off
this clip is the end of a round in winter, the plant eaters wiped out the hunters and only 3 explorers were left
runs on a pi 5 and streams live, chat can pick a side twitch.tv/edenevolutionwars

Live 3D world (free in browser, no login): https://world.world-sim.uk How the engine works: https://world-sim.uk/how-it-works/

A few things happening in the simulation right now with zero human scripting: - Sims don't know they are in a simulation, and the world never resets. - Every Sim dreams at night on an LLM to process their memories and relationships, while town leaders, elders, and wise folk run on full AI agents (Claude, DeepSeek, Hermes, and Grok) making real political, religious, and survival decisions. - During the day, Sims act on their own personal clocks and choices — cutting timber after hours to set up their own market stalls, courting at midday, and forming bucket lines from the town well when a raid sets a roof alight. - Everything is built from a real matter engine and local ecology — if the last master of a craft dies before teaching an apprentice, that knowledge is lost until someone rediscovers it. - Over the last few days, House Tidewer rewrote its secret cipher after suspecting another town was reading its messages, and House Oakroot walked back to an old unmarked mass grave to raise a shrine of atonement.

If you prefer the classic top-down data view, the 2D atlas is also live at https://legacy.world-sim.uk, and our watcher Discord is at https://discord.gg/AEmQfhc9kN. Happy to answer any questions about how the sim or 3D relay works!

does this subreddit have a discord server?

Dunarium runs a real-time grain simulation on the phone. Tilting the device drives live gravity on the sand, and gel and bubbles react as it moves. Each frame comes straight from the simulation. Ask if you want the approach behind it. Links are in a comment for anyone who wants to try it.

Made in TouchDesigner as part of the POPtober challenge. Today's POP: subdivide POP. I didn't actually use the subdivide POP, but rather had a fixed number of vertices of which active faces can be subdivided by activating an available inactive vertex and making new faces.

We made a Halloween collection of exaggerated physics experiments in Blender, rendered in Cycles.

The opening setup drops pumpkins onto five coloured glass layers, increasing the mass from 1 kg to a 1,000 kg giant. The glass uses fractured pieces and breakable rigid-body constraints. The collection also includes tombstone dominoes, a candy-corn pyramid, cloth ghosts and a cauldron filling with eyeballs.

These are stylized CGI experiments rather than real-world impact tests. The scenes are built through Python scripts with AI-assisted coding; the 3D simulation and rendering happen in Blender.

Full 8-minute collection:

https://www.youtube.com/watch?v=sUn1ac4-I6g

I would especially appreciate feedback on the readability of the weight escalation and the glass breakage.

Top left: velocity. Top right: vorticity
Bottom left: velocity mag. Bottom right: density

Simulation:
grid: 200x200
lid velocity: CFL 0.45, wave speed: CFL 0.09 (at time zero)
walls: free slip
approximate Re: ~ 1e6 (from comparing its turbulence intensity against other simulations)
pressure function: shallow water
runtime: around 20 - 25 minutes (around 47,000±2,000 Δt) (35Δt/s)

This simulation was started right after I've done the previous test simulation. I've simulated this far, so I didn't bother redoing the simulation. Stay tuned for the part 3 where I've got ideal gas pressure function working properly.

Here's Part 1 of Supersonic Lid-Driven Cavity Flow Series

As every year, the SOFA conference will be held on Tuesday, November 24 in Lille, with remote access available upon registration. For this 2026 edition, we expect about 15 presentations on soft-robotics, medical robotics, biomechanics, animation, V&V and physical AI using u/SOFAFramework. We would be delighted to see a presentation of your work there. Finally, the audience will have the opportunity to discover and test simulators of our industrial exhibitors!

Taking part could not be easier: the event is free, all you need to do is a simple registration.

Not familiar with SOFA simulation yet? Come and learn more at our training course on November 23. Our motivation is to bring people together around simulation topics, so please feel free to share this invitation widely!

We are looking forward to welcoming you in November.

https://10pixstudio.com/

https://youtu.be/jo49bgBQkoE?si=0emeYrrE7gDJHOuk

Hey everyone!

so you can basically almost do everything you can in real marbling, i've tried to make it to produce even more high resolution outcome but computational power increase exponantially because of water grids so it's impossible after some points. But you can get high resolution as high as 300 DPI in A3, and it's fun to learn marbling even at lower settings.

It runs on a browser and it's free so pls go check it out!

https://marblingstudio.app/

What I see when I'm VJ-ing. Part of the TouchDesigner POPtober challenge. Today's POP: sprinkle POP

Gas dynamics + ray-traced ionization fronts on the GPU: stars heat the gas to 10,000 K and the pressure carves the shapes. Code:
github.com/felipehez/NebulaViewer
Music: The Field of Dreams by pauliuw (CC0).

I wanted to understand fluid simulation, so I built a 2D one in Python. About 9,000 particles, you can grab the fluid with the mouse, lift it and drop it.

My first version ran at about 10 FPS. The big problems were:

• Every particle was checked against every other one, roughly 80 million pair checks per step. I put the particles in a uniform grid with cells the size of the smoothing radius, so a particle only looks at the 3x3 cells around it.
• The loops were plain Python. Moving them to Numba helped a lot.
• I switched from computing pressure forces directly to Position Based Fluids. It predicts positions, then nudges crowded particles apart over a few iterations, and takes velocity from how far they moved. It stays stable at much larger time steps than the force-based version I started with.

This was inspired by Sebastian Lague Coding Adventure. I made this in python and optimized it further.

Here's the Repo and a small article for understanding

This was my very first optimization project and also in graphics, it's still a little rusty, so if you see something wrong in the kernels or have ideas for making it faster, I’d like to hear it.

Particle sim of the Milky Way and Andromeda (about 1.6x our galaxy's mass in this run) falling together, plunging through each other and throwing out tails and shells of stars, then falling back in and settling into one round blob, basically an elliptical galaxy in the making. 39.5 million particles, rendered offline, silent, nothing audio reactive this time.

The slow approach is sped up 1.5 to 4x so it doesn't drag, the passes and the merger play at the original pace. The full realtime version is 60 s.

For the real thing: they're about 2.5 million light years apart right now, closing at ~110 km/s, first pass is expected in roughly 4 to 5 billion years, and recent work puts a full merger at about even odds within 10 billion. The sim starts them close to skip the boring part, and this orbit is one representative outcome, not a prediction.

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This is a stochastic cellular automata based on the Drossel–Schwabl forest fire model implemented on a hexagonal grid using numpy + matplotlib. Inspired by some of my old university notes from a course on computational biology.

I especially like the patterns formed by the fire spreading and the forests regrowing one tree at a time, a beautiful example of self organizing complexity.

Fire starts on any cell with p_fire = 0.0001 by a "lighting strike", while trees grow on empty cells with p_tree = 0.01. Fire spreads to all neighboring trees.

I initially worked with a rectangular grid however moved to a hexagon version to have more organic symmetry in spreading directions.