1 citations · 1 across the 9 of their papers we have counts for
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FPGA-Accelerated Real-Time Beam Emission Spectroscopy Diagnostics at DIII-D Using the SLAC Neural Network Library for ML Inference
Abhilasha Dave, James Russell, Mudit Mishra +9
Achieving reliable real-time control of tokamak plasmas is essential for sustaining high-performance operation in next-generation fusion reactors. A major challenge is the accurate…
One-shot acceleration of transient PDE solvers via online-learned preconditioners
Mikhail Khodak, Min Ki Jung, Brian Wynne +2
Data-driven acceleration of scientific computing workflows has been a high-profile aim of machine learning (ML) for science, with numerical simulation of transient partial differen…
ZERNIPAX: A Fast and Accurate Zernike Polynomial Calculator in Python
Yigit Gunsur Elmacioglu, Rory Conlin, Daniel W. Dudt +2
Zernike polynomials serve as an orthogonal basis on the unit disc, and have proven to be effective in optics simulations, astrophysics, and more recently in plasma simulations. Unl…
Parallelized Real-time Physics Codes for Plasma Control on DIII-D
A. Rothstein, K. Erickson, R. Conlin +2
A real-time safe multi-threading library was developed on the DIII-D plasma control system to optimize the realtime TORBEAM and real-time STRIDE physics codes. These physics codes…
Enabling Integrated AI Control on DIII-D: A Control System Design with State-of-the-art Experiments
Andrew Rothstein, Hiro Joseph Farre-Kaga, Jalal Butt +7
We present the design and application of a general algorithm for Prediction And Control using MAchiNe learning (PACMAN) in DIII-D. Machine learing (ML)-based predictors and control…
Omnigenous umbilic stellarators
R. Gaur, D. Panici, T. M. Elder +6
To better understand the dependence of the magnetic field structure in the plasma edge on the plasma boundary shape, in the context of X-point and island divertor designs, we defin…