21 citations · 22 across the 4 of their papers we have counts for
5 papers
A learning-based joint flow and kinematic state estimation for bodies in highly disturbed flows
Hanieh Mousavi, Anya Jones, Jeff Eldredge
Accurate estimation of unsteady aerodynamic flows from sparse measurements remains a fundamental challenge, particularly in the presence of strong disturbances, unknown body kinema…
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…
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…
Bayesian Inference for Estimating Heat Sources through Temperature Assimilation
Hanieh Mousavi, Jeff D. Eldredge
This paper introduces a Bayesian inference framework for two-dimensional steady-state heat conduction, focusing on the estimation of unknown distributed heat sources in a thermally…