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PARTNERSHIP FOR MULTISCALE GYROKINETIC TURBULENCE

A U.S. Dept. of Energy Scientific Discovery Through Advanced Computing (SciDAC)
Project: Developing supercomputer simulations of multi-scale micro turbulence to
predict plasma confinement in magnetically confined fusion plasmas

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PURPOSE

First-principles-based whole device modeling (WDM) of fusion devices is one of
the great frontiers of computational plasma physics. Ultimately, success will
enable the confident exploration of new ITER scenarios and new reactor concepts
in silico, at greatly reduced cost and over a much wider range of possibilities.
The challenges associated with connecting simulations of physical processes
occurring at vastly different time and space scales to one another are immense
and will require significant investments. In particular, success requires
further intensive development of the most complex physics modules: the
gyrokinetic turbulence kernels. Due in part to significant past SciDAC support,
core tokamak ‘anomalous transport’ is no longer an intractable mystery. A
validated predictive capability now exists for a range of conditions. However,
important problems remain unsolved.

For example: The narrow transport barrier of the H-mode pedestal doubles tokamak
energy confinement, but we cannot predict the conditions required to achieve it,
its energy losses, or its scope for optimization. Internal transport barriers
have proven to be equally challenging. Fluctuations coexisting on ion and
electron gyroradius scales yield to heroic simulations today, but remain
inaccessible on transport time scales and have not been explored in important
parameter regimes. Electromagnetic fluctuations (including microtearing) can be
simulated today, but not in the WDM context. Notably, each of these multiscale
challenges is associated with high performance operating regimes that magnetic
confinement fusion research seeks to exploit in the quest for fusion energy.


GOALS

In this project we will take on these challenges by applying high-fidelity
gyrokinetic simulations to these ‘frontier’ transport problems. In the process,
we will achieve profound scientific breakthroughs while also bringing these
challenging problems within the scope of WDM. Ultimately our team will deliver
to the broader WDM effort advanced 5D gyrokinetic modules for HPC platforms,
designed from the outset to meet three goals. First, these inherently
multi-scale/multifidelity turbulence modules will be validated against
experimental data in a continuing program of focused experimental research.
Second, our modules and algorithms will incorporate recent and inspire new
advances from the applied mathematics and computer science communities, to
guarantee the resilience, extreme scalability, and efficiency required to fit
the stringent requirements of WDM. The third goal is essential: we will confront
‘non-asymptotic’ non-local problems that often lie outside the conventional
local approximation—and thus necessarily, we will experiment with and develop
high-risk, multiscale, multifidelity coupling algorithms that should not be the
responsibility of the main WDM framework team.


NEWS




ABOUT


THE PARTNERSHIP FOR MULTISCALE GYROKINETIC TURBULENCE 

 * David Hatch (Overall Principal Investigator), Frank Jenko, (Max Planck
   Institute for Plasma Physics & University of Texas-Austin), Mike
   Kotschenreuther, Craig Michoski (University of Texas-Austin)
 * Greg W. Hammett (Principal Investigator, Princeton Plasma Physics
   Laboratory), Ammar Hakim (Princeton Plasma Physics Laboratory), Manaure
   Francisquez (2020 -), Noah Mandell (through 2021, now at MIT)
 * Bill Dorland (Principal Investigator, University of Maryland), Ian Abel
 * Lynda LoDestro (Principal Investigator), Andris Dimits (2020-), Jeff Parker
   (up to 2020) (Lawrence Livermore National Laboratory)
 * Darin R. Ernst (Principal Investigator, Massachusetts Institute of
   Technology), Qingjiang Pan (2018-2021), Manaure Francisquez (2018-2020, now
   at PPPL) (Massachusetts Institute of Technology)

COLLABORATORS:

 * Dan Reynolds (SMU—FASTMATH)
 * Cody Balos (LLNL—FASTMATH)
 * Carol Woodward (LLNL—FASTMATH)
 * Shan Hongzhang (LBNL—RAPIDS)
 * Lenny Oliker (LBNL—RAPIDS)
 * Antoine Cerfon (NYU Courant Institute)


ABOUT THIS SITE

For corrections, requests, updates contact Darin Ernst


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