FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation

• URL: http://arxiv.org/abs/2604.17149v2
• Date: Sat, 25 Apr 2026 03:55:48 GMT
• Title: FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation
• Abstract summary: FlowRefiner is a flow matching-based iterative refinement framework for 3D turbulent flow simulation.<n>The proposed framework is broadly applicable to iterative refinement problems in scientific modeling.
• Score: 22.1793816007531
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Accurate autoregressive prediction of 3D turbulent flows remains challenging for neural PDE solvers, as small errors in fine-scale structures can accumulate rapidly over rollout. In this paper, we propose FlowRefiner, a flow matching-based iterative refinement framework for 3D turbulent flow simulation. The method replaces stochastic denoising refinement with deterministic ODE-based correction, uses a unified velocity-field regression objective across all refinement stages, and introduces a decoupled sigma schedule that fixes the noise range independently of refinement depth. These design choices yield stable and effective refinement in the small-noise regime. Experiments on large-scale 3D turbulence with rich multi-scale structures show that FlowRefiner achieves state-of-the-art autoregressive prediction accuracy and strong physical consistency. Although developed for turbulent flow simulation, the proposed framework is broadly applicable to iterative refinement problems in scientific modeling.

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