Pui-kuen Yeung

2020

Kartik P. Iyer, Katepalli R. Sreenivasan, and P. K. Yeung (2020): Scaling exponents saturate in three-dimensional isotropic turbulence, Physical Review Fluids, American Physical Society, Vol 5, Num 5, pp054605

2019

Dhawal Buaria, Alain Pumir, Eberhard Bodenschatz, and P. K. Yeung (2019): Extreme velocity gradients in turbulent flows, New Journal of Physics, IOP Publishing Ltd., Vol 21, Num 4, pp043004
Kartik P. Iyer, Jörg Schumacher, Katepalli R. Sreenivasan, and P. K. Yeung (2019): Scaling of locally averaged energy dissipation and enstrophy density in isotropic turbulence, New Journal of Physics, IOP Publishing Ltd., Vol 21, Num 3, pp03316
Kartik P. Iyer, Katepalli R. Sreenivasan, and P. K. Yeung (2019): Circulation in High Reynolds Number Isotropic Turbulence is a Bifractal, Physical Review X, American Physical Society, Vol 9, Num 4, pp041006
X. M. Zhai, K. R. Sreenivasan, and P. K. Yeung (2019): Cancellation exponents in isotropic turbulence and magnetohydrodynamic turbulence, Physical Review E, American Physical Society, Vol 99, Num 2, pp023102

2018

M. P. Clay, D. Buaria, P. K. Yeung, and T. Gotoh (2018): GPU Acceleration of a Petascale Application for Turbulent Mixing at High Schmidt Number Using OpenMP 4.5, Computer Physics Communications, Elsevier BV, Vol 228, pp100-114
P. K. Yeung, K. R. Sreenivasan, and S. B. Pope (2018): Effects of Finite Spatial and Temporal Resolution in Direct Numerical Simulations of Incompressible Isotropic Turbulence, Physical Review Fluids, American Physical Society, Vol 3, Num 6, pp064603

2017

D. Buaria and P.K. Yeung (2017): A highly scalable particle tracking algorithm using partitioned global address space (PGAS) programming for extreme-scale turbulence simulations, Computer Physics Communications, Elsevier B.V., Vol 221, pp246-258
M. P. Clay, D. Buaria, T. Gotoh, and P. K. Yeung (2017): A Dual Communicator and Dual Grid-Resolution Algorithm for Petascale Simulations of Turbulent Mixing at High Schmidt Number, Computer Physics Communications, Elsevier BV, Vol 219, pp313-328
Kartik P. Iyer, Katepalli R. Sreenivasan, and P. K. Yeung (2017): Reynolds Number Scaling of Velocity Increments in Isotropic Turbulence, Physical Review E, American Physical Society, Vol 95, Num 2, pp021101

2016

D. Buaria, P. K. Yeung, and B. L. Sawford (2016): A Lagrangian Study of Turbulent Mixing: Forward and Backward Dispersion of Molecular Trajectories in Isotropic Turbulence, Journal of Fluid Mechanics, Cambridge University Press, Vol 799, pp352-382

2015

D. Buaria, Brian L. Sawford, and P. K. Yeung (2015): Characteristics of Backward and Forward Two-Particle Relative Dispersion in Turbulence at Different Reynolds Numbers, Physics of Fluids, AIP Publishing, Vol 27, Num 10, pp105101
P. K. Yeung, X. M. Zhai, and Katepalli R. Sreenivasan (2015): Extreme Events in Computational Turbulence, Proceedings of the National Academy of Sciences, The National Academy of Sciences, Vol 112, Num 41, pp12633--12638
Kartik P. Iyer, Katepalli R. Sreenivasan, and P. K. Yeung (2015): Refined Similarity Hypothesis Using Three-Dimensional Local Averages, Physical Review E, American Physical Society, Vol 92, Num 6, pp063024

2014

D. Buaria and P. K. Yeung (2014): Challenges in Particle Tracking in Turbulence on a Massive Scale, Association for Computing Machinery, XSEDE '14: Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment, Atlanta, Georgia, U.S.A.
P. K. Yeung and K. R. Sreenivasan (2014): Direct Numerical Simulation of Turbulent Mixing at Very Low Schmidt Number with a Uniform Mean Gradient, Physics of Fluids, AIP Publishing, Vol 26, Num 1, pp015107

2019

Pui–Kuen Yeung, K.R. Sreenivasan (2019): New Insights on Intermittency and Circulation Statistics Obtained from a Massive Turbulence Simulation Database, 2019 Blue Waters Annual Report, pp204-205

2018

Pui-Kuen Yeung, K.R. Sreenivasan, S.B. Pope (2018): Resolution Effects and Extreme Events in Petascale Turbulence Simulations, 2018 Blue Waters Annual Report, pp114-115

2017

Pui-kuen Yeung (2017): Intermittency, Resolution Effects and High Schmidt Number Mixing in Turbulence, 2017 Blue Waters Annual Report, pp166-167

2016

Pui-kuen Yeung (2016): The Complexities of High Reynolds Number Turbulence, 2016 Blue Waters Annual Report, pp134-136

2015

Pui-kuen Yeung (2015): Complexities of High Reynolds-Number Turbulence, 2015 Blue Waters Annual Report, pp110-111

Kartik Iyer, K. Sreenivasan, and P. K. Yeung: Area Rule for velocity circulation


72nd Annual Meeting of the American Physical Society Division of Fluid Dynamics; Seattle, Washington, Nov 25, 2019

P. K. Yeung: Extreme Scale Computing in Turbulence: Physics and Algorithms


Center for Environmental and Applied Mechanics seminar series, The Johns Hopkins University, Baltimore, Maryland, U.S.A., Mar 8, 2019

P.K Yeung: Extreme Events and Acceleration Statistics at High Reynolds Number


24th International Congress of Theoretical and Applied Mechanics; Montréal, Canada, Aug 23, 2016

Pui-kuen Yeung: High-Reynolds-Number Turbulence in a Petascale Computational Laboratory


EuHiT Turbulence Conference; Göttingen, Germany, May 2, 2016

P. K. Yeung, D. Buaria, and B.L. Sawford: Forward and Backward Relative Dispersion at High Reynolds Number


1st International Workshop on Cloud Turbulence; Nagoya, Japan, Mar 5, 2016

Pui-kuen Yeung, X. M. Zhai, and K. R. Sreenivasan: Turbulence at High Resolution: Intense Events in Dissipation, Enstrophy and Acceleration


67th Annual Meeting of the American Physical Society (APS) Division of Fluid Dynamics; San Francisco, California, U.S.A., Nov 24, 2014

Pui-Kuen Yeung: Early Results from High Reynolds Number DNS at 8,192^3 Resolution


2nd International Conference on Mathematical Theory of Turbulence via Harmonic Analysis and Computational Fluid Dynamics (2014); Nara, Japan, Mar 3, 2014

4 more research groups using Blue Waters Early Science System


May 21, 2012

Four additional research teams have begun using the first phase of the Blue Waters sustained-petascale supercomputer to tackle challenging problems in science and engineering. They join six research groups that began using the system in March. The Blue Waters Early Science System, which is made up of 48 Cray XE6 cabinets, represents about 15 percent of the total Blue Waters computational system and is currently the most powerful computing resource available through the National Science Foundation.


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