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Pol Suárez

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Open access Jul 2026

Flow separation control of an infinite wing section via multi-agent reinforcement learning

This is the first study in which a fully three-dimensional computational fluid dynamics simulation has been employed to train a DRL model for active flow control in wings, suggesting promising directions for extending DRL-based strategies to higher Reynolds numbers and more complex wing configurations where prior physical knowledge may be limited.

R. Montalà, B. Font, Pol Suárez et al. · 0 citations
#protein folding Open access Aug 2026

The HydroGym reinforcement learning platform for fluid dynamics.

HydroGym is introduced, a solver-independent reinforcement learning platform providing more than 60 validated, openly available flow control environments spanning from canonical laminar flows to complex turbulent flows, with systematic progression in the Reynolds number up to Re = 4 × 105, and Mach number variations in two and three dimensions.

Christian Lagemann, Sajeda Mokbel, Miro Gondrum et al. · 1 citation