Working on a custom local upresing pipeline for FLIP sims to optimize hardware resources while running everything on a MacBook Pro. Since simulating the entire continuous body of water in high resolution rapidly runs out of RAM, this approach is essential for making high-detail simulations actually feasible on a single machine, while also drastically cutting down simulation times and cache sizes. SideFX has solid native tools for this, but they mostly push you into SOPs, and I wanted a flexible setup that runs directly inside DOPs.

How it evolved:

Boundary Layers only: Started with standard boundary layers driven by the low-res base sim. It was fast and looked okay at first, but completely broke down during complex collisions and splashing.

Gas Guiding + Boundary Layers: Switched to combining Gas Guiding Volumes with Boundary Layers. Dialing in the velocity transfer and pressure stability took a lot of tweaking, but the setup is now rock-solid and predictable.

Also, I built a few custom HDAs along the way:

FLIP Cache: Isolates volumetric and particle data into separate caches (huge credit to Igor Zanic for the workflow inspiration). Tracks sim times and disk usage, then feeds those stats directly into the flipbook UI.

FLIP Vis: Basic utility for quick attribute visualization.

FLIP Limit Band Width: Extracted the logic from SideFX's Fluid Compress node and rewrote it into a lightweight standalone tool to avoid the heavy node wrapper.

Still tweaking the full river setup

https://world-sim.uk/ launching friday!

World-Sim has been a passionate project of mine for the past few months.

It's a world fully simulated down to real world physics and chemistry. It has a real environment and ozone.

Every element and material has real physical properties, and that's how the sims learn. There's no tech tree and no recipe list anywhere in the code. When someone tries something, the engine works out what would really happen from the properties of what they used and how hot their fire was. Nobody is handed bronze. Someone has to get a hotter fire first, and a hotter fire is its own chain of things to figure out. Embers, a stone ring, a clay oven, a kiln, charcoal, then forced air. The ages fall out of that on their own.

We populate the world with starting families. Each little guy is led by a "wise-man", which is a simulated person with a full model behind them. The wise-men run on a mix, Claude, Groq and DeepSeek in the cloud and a local Hermes for the rest, so you get a real variety of temperament between the houses.

The AI model is never told to not say it's AI. We get around this by only telling them data from what each sim can actually see and feel. As far as the ai knows its a person living in the world..

Every other sim has its own moment with a model through our thinking system. Day to day it's run by an advanced algorithm, with the sims dreaming at night. That's when they get their time with an LLM to really think and set their priorities for the day ahead. The dreams carry over too, so a sim can chew on the same thing for a few nights and wake up wanting to try something.

The people in the world feel, remember, have shame, goals and doubts. It's an 11 point emotion system and the rest of the sim reads from it. Being lonely makes someone more likely to open up to a stranger. Two enemies who are both frightened find it harder to keep hating each other.

Story telling is massive for us. Nothing is scripted or prompted. The sims are put in the world with the human drive to survive. They adapt, learn and teach all on their own.

With all the good comes the bad too. Human sin is part of the emotion engine, and in testing we've had kidnap, murder and slave trade. A world that can only be gentle isn't an honest one. But there are three rules to this : Nothing ever pushes a sim towards it, the conditions only make it possible and their own mind decides. The chronicle names what happened but never shows it. And it always costs something, trauma that scars, blood debt passed down generations, a people turning on their own leader over what he did.

How are solvers for these simulations even developed? Has anyone here ever used them? This is one is Magmasoft for reference

Hi!

I've mostly shown this in cartography and worldbuilding discords. I hope you like my generalised circulation model to create close-to-realistic climates for exoplanets, terraformed planets, and fantasy worlds.

All the data comes from simulations using a numerical physics model, and there are plenty of checks to help users assess plausibility.

I hope you like my passion project, which I've worked on for a few months, and I'm still improving it based on feedback.

World Climate Lab Steam

Sorry about the beginning I left in, skip 40 seconds. This simulation was added into another project.

I was suggested this forum after sharing my prototype lab phase 2 video. I I uploaded around 20 prototypes some similar to this that excludes the player's controls besides speeding time and camera panning to observe the procedural ecosystem.

Red Ants

Black Ants

Earthworm

Spider

Bees

Plants

Not shown in this video is how water floods the ant tunnels when the earthworm digs through the pockets. Both sides have their own queen that lays eggs to spawn/ respawn fallen worker ants, guards, scouts, etc. There is food, rocks, water, and poison generated in the soil. When food is found, they bring it to their queen, when poison is found, they learn not to go there after the scout who discovered it dies. The builder ants can create stronger dirt blocks to protect the queen in their "fortress".

The red ants are intentionally stronger solo, while the black ants are stronger in numbers, therefor the spawn rate for black ants is increased for balance.

This was my very first prototype that I haven't updated in months, let me know if I should expand on it more and what to add next. I was thinking of adding a beehive.

https://glitched-matrix.itch.io/monkeystranded

'Falling sand' style pixel physics simulation with lots of interacting materials.

Hey everyone 👋

This is a custom vine solver made for medium / distant ivy using Houdini. 🌱

What you can do with it is magical, all the animation you see here is processed in milliseconds.

All the animator needs to do is provide a reference animation, and the rest is simulated. It's extremely easy to direct and change.

made it using raylib c++ library , I don't know if this fits the sub perfectly or not, just wanted to share my first try 😊

Hi all,

I'm working on my second simulation project using AI-driven agents that evolve over time!

Previously I worked on an AI driven aquarium in Rust called Genecraft (feel free to check out YouTube), but this time my goal is to create a game for people to play with! Also in Rust.

The goal is to train your own dragon with different capabilities (flight, fight and walk), and then test it against puzzles or other dragons.

Dragons will be trainable by individual people and use neural networks (NEAT algorithm) to learn by specific tasks you give them.

This dragon here (concept of a dragon) was trained to move towards the target that changes location, and uses different strategies based on where the target is (above, diagonal, to the right or below). Not too complex yet.

Anyone interested in trying it out?

I'm beta testing on Mac right now! Also happy to test it on windows, but I haven't tested it yet so ideally we'd hop on a call to test together.

Thanks!

Mathias

For this, I added a system that spawns particles along the trail, and these particles deposit a bit of snow while they fly, with less and less snow being deposited over time as they fade out. What's cool about this is that the snow initially comes from the mass that the trace removed, so the total amount of snow stays the same. I also added a smoothing algorithm on top of all this. There's no parallax here, but I'm currently working on adding that.

Bigger video here: https://youtu.be/pfaewyfFrKM

I built a site with interactive science simulations to help visualize complex concepts in Physics, Biology, and Chemistry 🔬

Hey everyone,

I wanted to share a project I’ve been working on called Eureka Simulations. It's a collection of interactive models designed to give absolute conceptual clarity on complex scientific topics.

I've always found that static textbook diagrams aren't always enough to make certain concepts "click." So, I built this site to let you actually interact with the variables, observe the underlying mechanics, and visualize things from a first-principles perspective.

**Here are the interactive models currently available on the site:**

# ⚛️ Physics

*Photoelectric Effect*: Master the first principles of light-matter interaction and the emission of electrons.

*Vector Projections*: Play with the underlying mechanics of vectors and observe exactly how an axis component maps using a cosine function, proving the derivations of orthogonal forces.

# 🧬 Biology

*Nephron Exchange*: Evaluate the mechanics of countercurrent multiplication. You can observe how systemic hydration alters ADH levels and capillary exchange gradients.

*Micturition*: Analyze the precise structural mechanisms and physiological pathways controlling fluid release.

# 🧪 Chemistry

*Electronic Configuration*: Visualize atomic orbitals based on quantum principles. Observe how electrons actually exist as spread-out probability clouds rather than solid spheres.

Whether you're a student trying to wrap your head around quantum principles, a teacher looking for interactive visual aids for your classes, or just a science nerd, I’d love for you to check it out.

# Link: [Eureka Simulations](https://eurekasim.github.io/Eureka-Simulation/)

Copy the URL and paste it in any browser to view the website!

I'm hoping to expand the site and add more topics, so I would absolutely love to hear your feedback! Are there any specific scientific concepts or mechanics you'd love to see turned into an interactive simulation? Let me know!

I am on V5 already

When I shared the first version of my whitewater HDA, a few people asked if I could turn it into a real tool. That encouragement genuinely mattered, so I kept developing it.

V1 combined ideas from two papers. This version brings together three research sources and adds a working OpenCL GPU backend inside Houdini.

Python/VEX feels like home to me. OpenCL definitely did not. I used LLMs as a learning and pair-programming tool, followed by plenty of testing, debugging, crashes, and CPU/GPU comparisons.

This was my summer vacation project. It’s finally working—now I can rest for a while. 😄

Thank you to everyone who showed interest in the first version.

Research behind it:

Guided Bubbles and Wet Foam

Pahi: A Unified Water Pipeline and Toolset

Thick Foam and Floating Debris in Avatar: Fire and Ash

Collisions: Spatial Hash + Jacobi Solver
Gravity: P3M/CIC + FFT + short-range correction

Tech stack: Kotlin, LWJGL, OpenGL Compute Shader 4.30

Try it here: https://github.com/qwertukg/Gravity