Learning Interface Breakup: A Geometry-Conditioned Latent Surrogate for Spray Formation

• URL: http://arxiv.org/abs/2606.16587v1
• Date: Mon, 15 Jun 2026 11:32:36 GMT
• Title: Learning Interface Breakup: A Geometry-Conditioned Latent Surrogate for Spray Formation
• Abstract summary: High-fidelity volume-of-fluid (VOF) simulations with adaptive mesh refinement (AMR) are too expensive for iterative design exploration.<n>We introduce a geometry-conditioned latent surrogate trained on 797 two-phase nozzle simulations that addresses this by encoding the AMR cell-density field.<n>On held-out simulations, the method accurately captures key interface dynamics while reducing inference time to 0.045 seconds per trajectory.
• Score: 16.92031035309742
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Designing spray nozzles requires predicting how geometry shapes transient two-phase breakup, but high-fidelity volume-of-fluid (VOF) simulations with adaptive mesh refinement (AMR) are too expensive for iterative design exploration. Standard surrogate models are also challenged by this setting because both the liquid--gas interface and the underlying adaptive discretization evolve across time and geometries. We introduce a geometry-conditioned latent surrogate trained on 797 two-phase nozzle simulations that addresses this by encoding the AMR cell-density field, rather than the full multi-channel flow state, as a compact proxy for where the solver concentrates resolution. From this representation, the model reconstructs transient density evolution and nozzle geometry, and a lightweight second stage recovers the remaining flow variables. On held-out simulations, the method accurately captures key interface dynamics while reducing inference time to 0.045 seconds per trajectory, corresponding to a speed-up of more than $6\times10^4$ relative to Basilisk CFD. These results suggest that AMR refinement structure can serve as a compact and learnable representation for geometry-conditioned surrogate modeling of transient two-phase flows.

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