Lu Zhu is a Research Associate at DAMTP, University of Cambridge, with broad interests in computational fluid dynamics, machine learning, and data mining in complex flow systems. His current research focuses on the numerical investigation of elastic turbulence in complex geometries.
Publications
Long-wave instabilities of sloping stratified exchange flows
– Journal of Fluid Mechanics
(2024)
983,
a12
(doi: 10.1017/jfm.2024.96)
New insights into experimental stratified flows obtained through physics-informed neural networks
– Journal of Fluid Mechanics
(2024)
981,
r1
(doi: 10.1017/jfm.2024.49)
Geometry of stratified turbulent mixing: Local alignment of the density gradient with rotation, shear and viscous dissipation
– Journal of Fluid Mechanics
(2023)
977,
r5
(doi: 10.1017/jfm.2023.833)
Stratified inclined duct: two-layer hydraulics and instabilities
– Journal of Fluid Mechanics
(2023)
977,
a25
(doi: 10.1017/jfm.2023.871)
Bagged stepwise cluster analysis for probabilistic river flow prediction
– Journal of Hydrology
(2023)
625,
129995
Stratified inclined duct: direct numerical simulations
– Journal of Fluid Mechanics
(2023)
969,
a20
(doi: 10.1017/jfm.2023.502)
A novel linear hybrid model predictive control design: application to a fed batch crystallization process
– Digital Chemical Engineering
(2022)
3,
100033
(doi: 10.1016/j.dche.2022.100033)
Real-time prediction of river chloride concentration using ensemble learning
– Environmental pollution (Barking, Essex : 1987)
(2021)
291,
118116
(doi: 10.1016/j.envpol.2021.118116)
Nonasymptotic elastoinertial turbulence for asymptotic drag reduction
– Physical Review Fluids
(2021)
6,
014601
Inertia-driven and elastoinertial viscoelastic turbulent channel flow simulated with a hybrid pseudo-spectral/finite-difference numerical scheme
– Journal of Non-Newtonian Fluid Mechanics
(2020)
286,
104410
(doi: 10.1016/j.jnnfm.2020.104410)
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