Ian Ochs, a graduate student in the Program in Plasma Physics, has won a Porter Ogden Jacobus Fellowship, the most prestigious of the honorific fellowships that the University awards annually for academic excellence. The award goes to only one student in each of the four graduate school divisions — humanities, social sciences, natural and physical sciences, and engineering.
A nuclear fusion reactor in which a magnetic field keeps charged, hot plasma moving in a doughnut-shaped vacuum container.
A key issue for scientists seeking to bring the fusion that powers the sun and stars to Earth is forecasting the performance of the volatile plasma that fuels fusion reactions. Making such predictions calls for considerable costly time on the world’s fastest supercomputers. Now researchers at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) have borrowed a technique from applied mathematics to accelerate the process.
Scientists seeking to bring the fusion that powers the sun and stars to Earth must deal with sawtooth instabilities — up-and-down swings in the central pressure and temperature of the plasma that fuels fusion reactions, similar to the serrated blades of a saw. If these swings are large enough, they can lead to the sudden collapse of the entire discharge of the plasma. Such swings were first observed in 1974 and have so far eluded a widely accepted theory that explains experimental observations.
Consistent with observations
Creating and controlling on Earth the fusion energy that powers the sun and stars is a key goal of scientists around the world. Production of this safe, clean and limitless energy could generate electricity for all humanity, and the possibility is growing closer to reality. Now a landmark report released this week by the American Physical Society Division of Plasma Physics Community Planning Process proposes immediate steps for the United States to take to accelerate U.S.
Simple model proves remarkably effective
An improved method for sustaining high heat.
Researchers at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) have used Artificial Intelligence (AI) to create an innovative technique to improve the prediction of disruptions in fusion energy devices — a grand challenge in the effort to capture on Earth the fusion reactions that power the sun and stars.
Ten advances that highlight the Laboratory's wide-ranging achievements over the past 10 years.
What does the future hold for the development of fusion energy as a safe, clean and virtually limitless source of power to generate electricity? To find out, the Andlinger Center for Energy and Environment at Princeton University spoke with Steve Cowley, director of the U.S. Department of Energy’s Princeton Plasma Physics Laboratory (PPPL) and Princeton University professor of astrophysical sciences, and Egemen Kolemen, a PPPL physicist and assistant professor of mechanical and aerospace engineering and the Andlinger Center.
The American Physical Society (APS) has recognized a summer intern at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) for producing an outstanding research poster at the world-wide APS Division of Plasma Physics (DPP) gathering last October. The student, Marco Miller, a senior at Columbia University majoring in applied physics, used machine learning to accelerate a leading PPPL computer code known as XGC as a participant in the DOE’s Summer Undergraduate Laboratory Internship (SULI) program in 2019.
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