Seokkoo Kang

Hanyang University — South Korea

Environmental Science · Physical Sciences

25h-index2.6kcitations90works9.02yr avg
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Research Topics

Hydrology and Sediment Transport Processes(35), Fluid Dynamics and Turbulent Flows(24), Hydraulic flow and structures(20), Fluid Dynamics and Vibration Analysis(17), Lattice Boltzmann Simulation Studies(16)

Publications90 total

A Comparative Analysis of Logarithmic Law, Reynolds Stress, and Turbulence Kinetic Energy Methods for Bed Shear Stress Estimation in Complex Open‐Channel Flow
Water Resources Research·2024· 5 citedOpen Access
Flume Experiments for Flow around Debris Accumulation at a Bridge
KSCE Journal of Civil Engineering·2024· 13 cited
Experimental and numerical study on the flow characteristics around spur dikes at different length-to-depth ratios
Advances in Water Resources·2023· 13 cited
On the Morphodynamics of a Wide Class of Large‐Scale Meandering Rivers: Insights Gained by Coupling LES With Sediment‐Dynamics
Journal of Advances in Modeling Earth Systems·2023· 25 citedOpen Access
Understanding the Way Machines Simulate Hydrological Processes—A Case Study of Predicting Fine-Scale Watershed Response on a Distributed Framework
IEEE Transactions on Geoscience and Remote Sensing·2023· 4 cited
Virtual Flow Solver - Geophysics: A 3D Incompressible Navier-Stokes Solver
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)·2023Open Access
Lagrangian dynamics of contaminant particles released from a point source in New York City
Physics of Fluids·2022· 4 citedOpen Access
On the morphodynamics of a wide class of large-scale meandering rivers: Insights gained by coupling LES with sediment-dynamics
arXiv (Cornell University)·2022· 2 citedOpen Access
Wake interactions of two horizontal axis tidal turbines in tandem
Ocean Engineering·2022· 31 citedOpen Access
Large-Eddy Simulation of Wakes of Waked Wind Turbines
Energies·2022· 12 citedOpen Access
Data‐Driven Prediction of Turbulent Flow Statistics Past Bridge Piers in Large‐Scale Rivers Using Convolutional Neural Networks
Water Resources Research·2021· 32 cited
Publisher's Note: “A computational study of expiratory particle transport and vortex dynamics during breathing with and without face masks” [Phys. Fluids <b>33</b>, 066605 (2021)]
Physics of Fluids·2021
Data-driven physics-informed prediction of turbulent flow statistics past bridge piers in large-scale rivers using convolutional neural networks
arXiv (Cornell University)·2021Open Access
Turbulent flow characteristics around a non-submerged rectangular obstacle on the side of an open channel
Physics of Fluids·2021· 26 citedOpen Access
Discharge Characteristics of Drainage Gates on Saemangeum Tidal Dyke, South Korea
KSCE Journal of Civil Engineering·2021· 3 cited
Fluid dynamics simulations show that facial masks can suppress the spread of COVID-19 in indoor environments
AIP Advances·2020· 1 citedOpen Access
Video: How far is far enough and can facial masks suppress the spread of COVID-19?
2020Open Access
Fluid dynamics simulations show that facial masks can suppress the\n spread of COVID-19 in indoor environments
arXiv (Cornell University)·2020Open Access
Mean flow and turbulence characteristics around single-arm instream structures
Journal of Hydraulic Research·2020· 13 cited
High-fidelity three-phase flow simulation of flash and riverine floods in real-life waterways
2020· 1 cited
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Frequent Co-authors

Fotis Sotiropoulos(21), Ali Khosronejad(20), Xiaolei Yang(8), Craig Hill(5), Iman Borazjani(5), Jiyong Lee(4), Kyung Hwa Cho(4), Young Mo Kim(4), Kevin Flora(4), Antoni Calderer(3), E. M. Sparrow(3), Jeongsook Jeon(3), Trung Bao Le(3), Dionysios Angelidis(3), Zexia Zhang(3), Young-Kyu Kim(3), Tae Hoon Yoon(2), Ajay B. Limaye(2), Jong‐Oh Kim(2), Anvar Gilmanov(2)