21 citations · 48 across the 10 of their papers we have counts for
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…
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…
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…
Low-Order Flow Reconstruction and Uncertainty Quantification in Disturbed Aerodynamics Using Sparse Pressure Measurements
Hanieh Mousavi, Jeff D. Eldredge
This paper presents a novel machine-learning framework for reconstructing low-order gust-encounter flow field and lift coefficients from sparse, noisy surface pressure measurements…