The exascale era has brought with it a bevy of fusion energy simulation projects, aiming to stabilize the notoriously delicate—and so far, unmastered—clean energy source that would transform the world virtually overnight. Supercomputers and deep learning have shown promise in being able to predict the destabilizations that derail fusion reactions and determine the necessary corrections to prevent them, but the requisite split-second timing remains out of reach, and many elements of fusion energy reactor operation remain, in general, poorly understood. Now, researchers from the DOE’s Princeton Plasma Physics Laboratory (PPPL) have developed a new computational method for simulating the movement of free electrons during plasma physics experiments, a key roadblock in the simulation of fusion energy.
Like so many fusion energy simulations, the algorithm relates to a key device called a “tokamak” (pictured in header), which uses magnetism to suspend the active plasma particles during the fusion reaction. During this process, electrons careen around the tokamak—called pitch-angle scattering—in a manner that proved difficult to simulate due to its complexity. The PPPL algorithm leaps this hurdle, calculating the probable trajectories of the scattered electrons.
“Solving the stochastic differential equation gives the probability of every path the scattered electrons can take,” said Yichen Fu, a graduate student at PPPL and lead author of the paper describing the research, in an interview with PPPL’s John Greenwald. “However, the trajectories are probabilistic and we don’t know exactly where the electrons would go because there are many possible paths. But by solving the trajectories we can know the probability of electrons choosing every path, and knowing that enables more accurate simulations that can lead to better control of the plasma.”
This better plasma control would stem from changes in how the electric current is channeled into the plasma and an improved understanding of how the pitch-angle scattering can pose dangers to the stability and integrity of the devices involved in the reaction. “This technical advance displays the role of the [Computational Sciences Department at PPPL], said Hong Qin, a principal research physicist at PPPL and coauthor of the paper. “One of its goals is to develop algorithms that lead to improved fusion simulations.” The Computational Sciences Department at PPPL is a relatively new addition, having launched just last year.
This new equation expands on prior research, adding the incorporation of magnetic fields and performing a more rigorous proof of the algorithm’s accuracy. “This gives experimentalists a better theoretical description of what’s going on to help them design their experiments,” Qin said. “Previously, there was no working algorithm for this equation, and physicists got around this difficulty by changing the equation.”
To learn more about this research, read the article from PPPL’s John Greenwald here and read the research paper here.
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