3 papers
physics.flu-dyn2026
A hybrid proper orthogonal decomposition and diffusion framework for reduced-order forecasting of turbulent flow dynamics
Rodrigo Abadia-Heredia, Xiangrui Zou, Manuel Lopez-Martin +2
Forecasting turbulent flow dynamics requires a balance between predictive fidelity and computational efficiency. Diffusion-based generative models can represent complex spatiotempo…
physics.flu-dyn2026
Divergence-aware adaptive prediction framework for accelerating CFD simulations of unsteady flows
Xiangrui Zou, Zhuoqun Zhao, Guillermo Barragán +1
Reliable long-horizon prediction remains a challenge for data-driven CFD surrogates, because offline-trained models accumulate autoregressive errors and lose accuracy when operatin…
physics.flu-dyn2025
Generative artificial intelligence and hybrid models to accelerate LES in reactive flows: Application to hydrogen/methane combustion
Xiangrui Zou, Rodrigo Abadia-Heredia, Laura Saavedra +3
With increasing emphasis on carbon neutrality, accurate and efficient combustion prediction has become essential for the design and optimization of new generation combustion system…