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Michael D Graham

Showing results (11-20 of 53) with videos related to

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Physical Review Letters|February 14, 2012
Dynamics on the laminar-turbulent boundary and the origin of the maximum drag reduction asymptoteLi Xi, Michael D Graham
Proceedings of the National Academy of Sciences of the United States of America|January 14, 2021
Discovering multiscale and self-similar structure with data-driven waveletsDaniel Floryan, Michael D Graham
Physical Review. E|August 20, 2021
Symmetry reduction for deep reinforcement learning active control of chaotic spatiotemporal dynamicsKevin Zeng, Michael D Graham
Physical Review. E|July 22, 2020
Deep learning to discover and predict dynamics on an inertial manifoldAlec J Linot, Michael D Graham
Physical Review. E|April 19, 2023
Deep learning delay coordinate dynamics for chaotic attractors from partial observable dataCharles D Young, Michael D Graham
Chaos (Woodbury, N.Y.)|July 30, 2022
Data-driven reduced-order modeling of spatiotemporal chaos with neural ordinary differential equationsAlec J Linot, Michael D Graham
Biophysical Journal|March 16, 2017
Buckling Instabilities and Complex Trajectories in a Simple Model of Uniflagellar BacteriaFrank T M Nguyen, Michael D Graham
Langmuir : the ACS Journal of Surfaces and Colloids|March 9, 2005
Role of desorption kinetics in determining marangoni flows generated by using electrochemical methods and redox-active surfactantsGuiyu Bai, Michael D Graham, Nicholas L Abbott
Physical Review Letters|November 22, 2002
Toward a structural understanding of turbulent drag reduction: nonlinear coherent states in viscoelastic shear flowsPhilip A Stone, Fabian Waleffe, Michael D Graham
Physical Review Fluids|November 29, 2019
Dynamics of deformable straight and curved prolate capsules in simple shear flowXiao Zhang, Wilbur A Lam, Michael D Graham
Pageof 6

Showing results (11-20 of 53) with videos related to

Sort By:
Pageof 6
Physical Review Letters|February 14, 2012
Dynamics on the laminar-turbulent boundary and the origin of the maximum drag reduction asymptoteLi Xi, Michael D Graham
Proceedings of the National Academy of Sciences of the United States of America|January 14, 2021
Discovering multiscale and self-similar structure with data-driven waveletsDaniel Floryan, Michael D Graham
Physical Review. E|August 20, 2021
Symmetry reduction for deep reinforcement learning active control of chaotic spatiotemporal dynamicsKevin Zeng, Michael D Graham
Physical Review. E|July 22, 2020
Deep learning to discover and predict dynamics on an inertial manifoldAlec J Linot, Michael D Graham
Physical Review. E|April 19, 2023
Deep learning delay coordinate dynamics for chaotic attractors from partial observable dataCharles D Young, Michael D Graham
Chaos (Woodbury, N.Y.)|July 30, 2022
Data-driven reduced-order modeling of spatiotemporal chaos with neural ordinary differential equationsAlec J Linot, Michael D Graham
Biophysical Journal|March 16, 2017
Buckling Instabilities and Complex Trajectories in a Simple Model of Uniflagellar BacteriaFrank T M Nguyen, Michael D Graham
Langmuir : the ACS Journal of Surfaces and Colloids|March 9, 2005
Role of desorption kinetics in determining marangoni flows generated by using electrochemical methods and redox-active surfactantsGuiyu Bai, Michael D Graham, Nicholas L Abbott
Physical Review Letters|November 22, 2002
Toward a structural understanding of turbulent drag reduction: nonlinear coherent states in viscoelastic shear flowsPhilip A Stone, Fabian Waleffe, Michael D Graham
Physical Review Fluids|November 29, 2019
Dynamics of deformable straight and curved prolate capsules in simple shear flowXiao Zhang, Wilbur A Lam, Michael D Graham
Pageof 6