Latest vellum exploration. Rendered with Redshift.

In this focused RnD, I implemented a small-scale fluid simulation algorithm within Flip to accurately resolve adhesion forces. The core algorithm is relatively straightforward: the fluid's surface field is extrapolated into the collider volume, factoring in the contact angle, and is subsequently adjusted and smoothed. Furthermore, a localized viscosity is introduced at the fluid-collider interface to approximate boundary friction.

The simulation operates at a physically accurate real-world scale, utilizing empirical physical constants where the baseline water viscosity is 0.001 and surface tension is 0.072. APIC was chosen as the underlying solver.

While this technique requires a high substep count and is computationally expensive to evaluate, it successfully produces highly nuanced and realistic fluid dynamics.

I tried to simulate some popcorn for a personal project and edited a small breakdown in Houdini 🍿🤗 happy to hear what you guys think 🧐

Playing with new MPM solver and other solvers to make a cup of tea!

mpm #houdini #flip #particles #pyro #tea #ink #simulation

The solver is based on the Wētā FX paper (Guided Two-Way Coupled Bubbles + explicit SPH + manifold advection). The underwater bubble system features a locally resimulated fluid with two-way coupling to the bubbles. The foam is handled via an SPH simulation projected onto a 2D manifold of the water surface. The solver implements standard SPH forces such as viscosity (mu), cohesion (C for strength, beta_c for radius), and surface friction against the water. The original authors apply a particle volume multiplier to the cohesion force. While this is valid and supported as an option in my solver, I prefer using the neighbor's volume multiplier instead of the active particle's volume. To my eye, this yields visually superior foam clustering.

The foam is constrained to the surface via manifold advection: forces are decomposed into tangential and normal components, the normal component is discarded, and particles are projected back onto the water surface using Newton iterations.

I can confidently say this looks significantly better than both the standard Whitewater Solver and POP Fluid workflows. Additionally, POP Fluid lacks support for variable particle radii, which has always been a major limitation for me.

For the past couple of months, I have been developing a subsurface bubble solver featuring two-way coupling between the bubbles and the surrounding water. For me, the limitation of Houdini’s native Whitewater (WW) solver lies in its one-way coupling model: the FLIP vel field pushes the bubbles, while buoyancy is driven by a constant vector. This approach holds up well for mid- and background elements, but falls short for hero-scale simulations, typically forcing artists to rely on a Pyro + POP Advect by Volumes workflow.

The core of the two-way method is that while the water’s vel field drives the bubbles, the bubbles exert an equal reaction back onto the water’s vel - analogous to how Gas Feedback couples RBD with FLIP. Each bubble is treated as an ideal sphere with a radius of f@pscale. Its volume is rasterized onto a voxel grid, serving as the primary multiplier for all forces and operations. By tracking the collective bubble volume, we can derive the displaced liquid volume and adjust density and vel accordingly.

Pressure projection is handled via Gas Project Non Divergent Variational. With a few minor simplifications, I was able to replicate the core logic of the Weta FX paper. There is no synthetic buoyancy vector here: upward motion emerges physically - driven by the fluid pressure gradient from high-pressure zones to low-pressure ones.

As a result, bubble clusters behave organically: larger bubbles exert a stronger influence on the fluid than smaller ones, and their motion no longer feels artificially "glued" to the underlying vel field. Furthermore, the solver remains highly intuitive: the physical parameters are straightforward and, in most production scenarios, work reliably right out of the box.

Made this last year for a project about wildlife. Unfortunately it got scraped but, as always, you learn a lot from such projects.

Modelled, rigged and animated the head, then used vellum for a smoother animation and flesh simulation. After that it was a matter of getting all the tendrils also modelled and simulated. I think I used a VDB Mesh in the end at the time.

Check out my portfolio: https://www.artstation.com/jteixeirafx

Used a 2D Pyro solver to advect particles for this abstract particle simulation. Rendered with Karma XPU in Houdini 22.

By Milen Piskuliyski.
Software: Houdini, Maya, Arnold, Substance 3D Painter
Portfolio: https://www.artstation.com/artwork/5W2XOP

More paradigm tests now with its native white water solver. Rendered with Karma

Would appriciate your follow on my Instagram page

Focused on heavy rainfall, water splashes, wet surfaces and cinematic night mood.
Final compositing done in Nuke.

Just came of a big project with wifi_retina to do the cloth simulation on Xyz Studios project done for National Basketball Association (NBA) 🏀🏀!!

We created a procedural setup in Houdini that took their animated alembic characters then positioned cloth, ran simulation, and deformed high res geometry all in one pass.

For more behind the scenes work check out our work on insta @ahenkona.cg & @wifi_retina.

Collaborate project @jit_effect & @calars_art

Made a little ident for work. Vdb advection in a solver. Lots of help from the elders scrolls of OD forum.

Some surface tension tests I started a while ago and finally decided to finish up. The main reference was typical slow motion commercial stock footage of fruit.

Used proximity masks against the apple colliders and ground to dynamically adjust viscosity, surface tension, and forces to simulate adhesion. A simple wetness map solver was used to drive roughness and diffuse map parameters during render.

Apple models are free 3D scans.

Rendered with Karma XPU.