Real-Time 3D Simulation of Heat-Induced Air Turbulence

Abstract

Heat-induced air turbulence produces complex, depth-dependent image distortions that are challenging to reproduce interactively because thermally driven flow must be coupled with refractive light transport. Existing real-time methods often rely on single-view 2D screen-space warps that break multi-view coherence and do not model a 3D refractive volume. We present a real-time, fully 3D Lagrangian framework that models the full pipeline from thermal transport to density variation to optical refraction. Our system augments compressible Smoothed Particle Hydrodynamics (SPH) with temperature transport, buoyancy, and pressure-driven motion to capture rising plumes and turbulent mixing. We render the resulting continuous refractive-index field via curved ray tracing to model light bending in 3D. To reconcile physical fidelity with interactive performance, we introduce spatially adaptive step-size integration for curved-ray tracing, refining steps near strong refractive-index gradients while relaxing them in smooth regions to preserve temporal stability and high-frequency distortion detail without uniform oversampling. The system runs at interactive rates (about 40 fps in our prototype) and matches depth-dependent, multi-view-consistent distortions observed in real video captures more closely than image-based baselines.

Figures (9)

• Figure 1: Overview of the proposed real-time heat-induced 3D fluid model and curved ray tracing approach. Rays traveling inside the fluid volume follow curved paths due to refractive index gradients, while rays outside the volume are rendered using standard straight ray tracing.
• Figure 2: Overview of the simulation and rendering pipeline. The system models heat transfer through source-particle and particle-particle interactions, updating temperature, buoyancy, and velocity accordingly. These attributes drive updates to particle position, density, and pressure. The updated particle states are rendered via curved ray tracing through camera views $C_1, C_2$.
• Figure 3: Our simulation and rendering results. For a complete set of better visual effects, please see Figure \ref{['fig:results']}, and the dynamic video results in Supplementary materials.
• Figure 4: 2D dissection of our heat-driven particle system. The bottom square marks the heat source. Initially (left), the system is quiescent. Once activated, particles absorb heat, rise, and spread turbulence throughout the domain (left to right). Colors denote velocity magnitude, from slow (blue) to fast (red).
• Figure 5: 3D illustration of curved ray tracing with adaptive step size. Red regions indicate higher density, while blue regions indicate lower density. We can tell that our adaptive step size implementation can effectively reduce the sampling points during ray-tracing.