4 papers
Sloshing suppression with a controlled elastic baffle via deep reinforcement learning and SPH simulation
Mai Ye, Yaru Ren, Silong Zhang +3
This study employed smoothed particle hydrodynamics (SPH) as the numerical environment, integrated with deep reinforcement learning (DRL) real-time control algorithms to optimize t…
Adaptive optimization of wave energy conversion in oscillatory wave surge converters via SPH simulation and deep reinforcement learning
Mai Ye, Chi Zhang, Yaru Ren +3
The nonlinear damping characteristics of the oscillating wave surge converter (OWSC) significantly impact the performance of the power take-off system. This study presents a framew…
DRLinSPH: An open-source platform using deep reinforcement learning and SPHinXsys for fluid-structure-interaction problems
Mai Ye, Hao Ma, Yaru Ren +3
Fluid-structure interaction (FSI) problems are characterized by strong nonlinearities arising from complex interactions between fluids and structures. These pose significant challe…
Generalized and high-efficiency arbitrary-positioned buffer for smoothed particle hydrodynamics
Shuoguo Zhang, Yu Fan, Yaru Ren +2
This paper develops an arbitrary-positioned buffer for the smoothed particle hydrodynamics (SPH) method, whose generality and high efficiency are achieved through two techniques. F…