Douglas Kelley

Professor of Mechanical Engineering

  • Rochester NY UNITED STATES

Douglas Kelley studies the performance of liquid metal batteries.

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Areas of Expertise

Mixing in Metals Casting
Liquid Metal Batteries
Grid-Scale Energy Storage
Fluid Dynamics of the Brain's Waste Removal System
Coherent Structures in Reactive Mixing

Biography

Douglas H. Kelley is a professor of mechanical engineering and a staff scientist at the Laboratory for Laser Energetics. His research interests include fluid dynamics of the brain’s waste removal system, mixing in the inner ear, liquid metal batteries and grid-scale energy storage, mixing in metals casting, and coherent structures in reactive mixing. Prof. Kelley is an NSF CAREER Award winner (2016) and has earned more than $26 million as principal investigator or co-PI, of which $9.7 million is as PI.

Education

Virginia Tech

BS

Electrical Engineering

2000

Auburn University

MS

Physics

2004

University of Maryland

PhD

Physics

2009

Selected Articles

Sensitivity analysis on a network model of glymphatic flow

Journal of the Royal Society Interface

Douglas H. Kelley, Kimberly A. S. Boster, Jeffrey Tithof, Douglas D. Cook, and John H. Thomas

2022-06-01

Intracranial cerebrospinal and interstitial fluid (ISF) flow and solute transport have important clinical implications, but limited in vivo access to the brain interior leaves gaping holes in human understanding of the nature of these neurophysiological phenomena. Models can address some gaps, but only insofar as model inputs are accurate. We perform a sensitivity analysis using a Monte Carlo approach on a lumped-parameter network model of cerebrospinal and ISF in perivascular and extracellular spaces in the murine brain.

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Oscillations of the large-scale circulation in experimental liquid metal convection at aspect ratios 1.4–3

Journal of Fluid Mechanics

Douglass H. Kelley, Jonathan S. Cheng, Ibrahim Mohammad, Bitong Wang, Declan F. Keogh, and Jarod M. Forer

2022-10-06

We investigate the scaling properties of the primary flow modes and their sensitivity to aspect ratio in a liquid gallium (Prandtl number Pr=0.02) convection system through combined laboratory experiments and numerical simulations. We survey cylindrical aspect ratios 1.4≤Γ≤3 and Rayleigh numbers 104≲Ra≲106. In this range the flow is dominated by a large-scale circulation (LSC) subject to low-frequency oscillations. In line with previous studies, we show robust scaling of the Reynolds number Re with Ra and we confirm that the LSC flow is dominated by a jump-rope vortex (JRV) mode whose signature frequency is present in velocity and temperature measurements.

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Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows

Proceedings of the National Academy of Sciences

Douglass H. Kelley, Kimberly A.S. Boster, Shengze Cai, and Antonio Ladrón-de-Guevara,

2023-03-29

Diseases such as Alzheimer’s and small vessel disease are linked to alterations of flow in the perivascular spaces that surround cerebral blood vessels and transport water-like fluids around brain tissue. Understanding the function, failure, and potential rehabilitation of the system depends on high-fidelity, in vivo quantification of flow rates, pressure, and shear stress, which have previously been unavailable. We show that artificial intelligence velocimetry (AIV), which integrates sparse two-dimensional (2D) in vivo velocity measurements with physics-informed neural networks, can accurately infer high-resolution pressure and shear stresses.

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