u/DocumentFederal

Hi everyone,

I’m working on a computer graphics course project and would really appreciate feedback from people with experience in computer graphics, CFD, SPH, adaptive meshing, adaptive mesh refinement, computational grid, irregular (organic) unstructured quadrilateral/hexagonal grid generation, or scientific visualization.

The project started from two separate interests:

1. A GPU particle-based (Lagrangian grid-free) fluid simulation in Unity, inspired by Sebastian Lague’s fluid simulation work (https://www.youtube.com/watch?v=rSKMYc1CQHE).
2. A custom organic irregular quadrilateral/hexagonal grid that I had previously built in Unity, inspired by Oskar Stålberg's Townscaper game. I'm a bit concerned about using this grid, since Oskar used it more for creativity/artistic reasons in his game, to get that organic European look for his town assets (https://x.com/OskSta/status/1147881669350891521).

More recently, I came across the paper (is it okay that it's 20+ years old?) “A Solution-Adaptive Grid Generation Scheme for Atmospheric Flow Simulations” (https://www.researchgate.net/publication/2379446_A_Solution-Adaptive_Grid_Generation_Scheme_for_Atmospheric_Flow_Simulations), which gave me the idea to combine these two directions. I am not trying to reproduce the full atmospheric solver from the paper. Instead, I’m trying to reinterpret the solution-adaptive grid-generation idea in a real-time graphics context.

My current implementation is roughly:

• A GPU particle-fluid simulation, where particles carry position, velocity, density, etc.
• A custom organic irregular quadrilateral grid.
• A regular uniform quad grid as a comparison baseline (or maybe something else?).
• A bridge that samples the fluid state and assigns an importance value to each adaptive grid cell.
• Cells are dynamically refined/coarsened based on particle count, density, velocity, or combined importance.
• The grid itself is CPU-side topology, while the fluid simulation and importance sampling are GPU-side in Unity.
• The organic grid boundary can also be used as the physical fluid collision boundary.

The part I am unsure about is the scientific meaning framing.

Since the fluid simulation is particle-based/Lagrangian, the adaptive grid is not actually solving the fluid equations directly. Instead, the grid adapts to the particle solution field. So the project is more of a hybrid particle-grid / scientific visualization / adaptive representation prototype than a traditional grid-based CFD solver.

My tentative research question is something like:

How effectively can a particle-based fluid simulation drive solution-adaptive refinement of an organic irregular quadrilateral grid in real time, and how does this compare to a regular uniform adaptive grid?

To make this project idea scientifically meaningfull I need to make the evaluation look like a research investigation, not only a demo. So basically, I need to ground this exploratory investigation idea into state-of-the-art evaluation methods for my approach. I struggle with this part as well.

I might be considering evaluating (do correct me if this seems incorrect or too much or too unnecessary):

• FPS / frame time
• adaptation time
• active cell count
• base cell count
• max refinement level
• particle count scalability
• percentage of particles covered by refined cells
• percentage of refined cells that are empty/wasted
• organic grid vs uniform grid performance and adaptive behavior
• possibly mesh-quality metrics such as aspect ratio, angle quality, or cell area variation

My doubts are:

1. Is this hybrid approach scientifically meaningful, even though the adaptive grid is not the main fluid solver?
2. Is comparing an organic irregular adaptive grid against a uniform adaptive grid a valid research-style comparison?
3. Would it be more correct to frame this as adaptive scientific visualization / adaptive spatial representation rather than CFD accuracy?
4. What evaluation metrics would make this feel like a serious graphics/scientific computing project rather than just a creative Unity demo?
5. Are there related methods or papers I should reference, especially around particle-grid coupling, adaptive mesh refinement, scientific visualization, or fluid-driven level of detail?

I would be grateful for any critique, suggestions, or warnings. I especially want to make sure I am not overclaiming what the project does. My goal is to present it honestly as a research-inspired real-time graphics prototype with a meaningful evaluation, not as a fully validated CFD solver. My interests lie more in the computational grid, spatial discretisation, computational geometry, implicit representation, shape representation, uncovering shapes, geometries, patterns, and structures in a space, and the spatial intelligence side of research, rather than physics itself.

Any help would be appreciated! Let me know if you need more info regarding this.

Thanks in advance!