4 papers · 1 filter
Sequential estimation of disturbed aerodynamic flows from sparse measurements via a reduced latent space
Hanieh Mousavi, Anya Jones, Jeff Eldredge
This work presents a fast, uncertainty-aware sequential data assimilation framework for estimating key aerodynamic states (e.g., instantaneous vorticity fields and aerodynamic load…
A practical guide to estimation and uncertainty quantification of aerodynamic flows
Jeff D. Eldredge, Hanieh Mousavi
Many applications in aerodynamics, particularly in closed-loop control, depend on sensors to estimate the evolving state of the flow. This estimation task is inherently accompanied…
Attention on flow control: transformer-based reinforcement learning for lift regulation in highly disturbed flows
Zhecheng Liu, Jeff D. Eldredge
A linear flow control strategy designed for weak disturbances may not remain effective in sequences of strong disturbances due to nonlinear interactions, but it is sensible to leve…
Model-Based Reinforcement Learning for Control of Strongly-Disturbed Unsteady Aerodynamic Flows
Zhecheng Liu, Diederik Beckers, Jeff D. Eldredge
The intrinsic high dimension of fluid dynamics is an inherent challenge to control of aerodynamic flows, and this is further complicated by a flow's nonlinear response to strong di…