34 citations · 162 across the 20 of their papers we have counts for
21 papers
Equivariant Neural Prediction of the Stokes Resistance Tensors for Arbitrary Microparticle Shapes
Sanjay Pradeep, David Dandy, Candace S. J. Tsai +1
The Stokes-flow hydrodynamics of an irregular microparticle is encoded by its grand resistance matrix, a 6x6 tensor whose translational and rotational blocks (A and C) govern settl…
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…
Quantification and Classification of Carbon Nanotubes in Electron Micrographs using Vision Foundation Models
Sanjay Pradeep, Chen Wang, Matthew M. Dahm +2
Accurate characterization of carbon nanotube morphologies in electron microscopy images is vital for exposure assessment and toxicological studies, yet current workflows rely on sl…
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…
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…
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…
Deep reinforcement learning of airfoil pitch control in a highly disturbed environment using partial observations
Diederik Beckers, Jeff D. Eldredge
This study explores the application of deep reinforcement learning (RL) to design an airfoil pitch controller capable of minimizing lift variations in randomly disturbed flows. The…
An adaptive ensemble filter for heavy-tailed distributions: tuning-free inflation and localization
Mathieu Le Provost, Ricardo Baptista, Jeff D. Eldredge +1
Heavy tails is a common feature of filtering distributions that results from the nonlinear dynamical and observation processes as well as the uncertainty from physical sensors. In…
Bayesian inference of vorticity in unbounded flow from limited pressure measurements
Jeff D. Eldredge, Mathieu Le Provost
We study the instantaneous inference of an unbounded planar flow from sparse noisy pressure measurements. The true flow field comprises one or more regularized point vortices of va…
A low-rank ensemble Kalman filter for elliptic observations
Mathieu Le Provost, Ricardo Baptista, Youssef Marzouk +1
We propose a regularization method for ensemble Kalman filtering (EnKF) with elliptic observation operators. Commonly used EnKF regularization methods suppress state correlations a…
Experimental quantification of unsteady leading-edge flow separation
Julien Deparday, Xiaowei He, Jeff D. Eldredge +2
We propose here a method to experimentally quantify unsteady leading-edge flow separation on aerofoils with finite thickness. The methodology relies on the computation of a leading…
A method of immersed layers on Cartesian grids, with application to incompressible flows
Jeff D. Eldredge
The immersed boundary method (IBM) of Peskin (J. Comput. Phys., 1977), and derived forms such as the projection method of Taira and Colonius (J. Comput. Phys., 2007), have been use…
Planar potential flow on Cartesian grids
Diederik Beckers, Jeff D. Eldredge
Potential flow has many applications, including the modelling of unsteady flows in aerodynamics. For these models to work efficiently, it is best to avoid Biot-Savart interactions.…
Ensemble-filtered vortex modeling of strongly disturbed aerodynamic flows
Mathieu Le Provost, Jeff D. Eldredge
The task of dynamic flow estimation is to construct an approximation of an evolving flow---and particularly, its response to disturbances---using measurements from available sensor…
Lift Coefficient Estimation for a Rapidly Pitching Airfoil
Xuanhong An, David R. Williams, Jeff D. Eldredge +1
We develop a method for estimating the instantaneous lift coefficient on a rapidly pitching airfoil that uses a small number of pressure sensors and a measurement of the angle of a…
The mean transport of inertial particles in viscous streaming flows
Mathieu Le Provost, Jeff D. Eldredge
Viscous streaming has emerged as an effective method to transport, trap, and cluster inertial particles in a fluid. Previous work has shown that this transport is well described by…
Transport of inertial particles by viscous streaming in arrays of oscillating probes
Kwitae Chong, Scott D. Kelly, Stuart T. Smith +1
A novel mechanism for the transport of microscale particles in viscous fluids is demonstrated. The mechanism exploits the trapping of such particles by rotational streaming cells e…
Hydrodynamics of undulatory fish schooling in lateral configurations
Li Jeany Zhang, Jeff D. Eldredge
The thrust benefits of lateral configurations of two-dimensional undulating fish-like bodies are investigated using high-fidelity numerical simulation. The solution of the Navier--…