From the 1 of 11 linked papers with an AI index.
11 papers
Can Explicit Subgrid Models Enhance Implicit LES Simulations? A Very High-Order Solver Perspective
Gonzalo Rubio, Gerasimos Ntoukas, Miguel Chávez-Módena +5
The paper studies how explicit Vreman subgrid‑scale models interact with the inherent numerical dissipation of very high‑order discontinuous Galerkin methods for turbulent flow sim…
Scaling WaterLily.jl with MPI and an improved geometric multigrid solver
Bernat Font, Marin Lauber, Tzu-Yao Huang +1
We present recent performance-oriented developments in WaterLily, a scale-resolving incompressible flow solver written in pure Julia that runs seamlessly on CPUs and GPUs of any ve…
Acceleration of an algebraic multigrid pressure solver using graph neural networks
Eric Chillón, Artur K. Lidtke, Nguyen Anh Khoa Doan +1
Solving the pressure-Poisson equation remains the primary computational bottleneck in incompressible unstructured flow solvers primarily due to the inherent sensitivity of traditio…
High-lift Wing Separation Control via Bayesian Optimization and Deep Reinforcement Learning
Ricard MontalÃ, Bernat Font, Oriol Lehmkuhl +2
This study investigates active flow control (AFC) of a 30P30N high-lift wing at a Reynolds number Re = 450,000 and angle of attack = 23 using wallresolved large-ed…
Deep Reinforcement Learning in Action: Real-Time Control of Vortex-Induced Vibrations
Hussam Sababha, Bernat Font, Mohammed Daqaq
This study showcases an experimental deployment of deep reinforcement learning (DRL) for active flow control (AFC) of vortex-induced vibrations (VIV) in a circular cylinder at a hi…
SmartFlow: A CFD-solver-agnostic deep reinforcement learning framework for computational fluid dynamics on HPC platforms
Maochao Xiao, Yuning Wang, Felix Rodach +15
Deep reinforcement learning (DRL) is emerging as a powerful tool for fluid-dynamics research, encompassing active flow control, autonomous navigation, turbulence modeling and disco…