62 citations · 62 across the 6 of their papers we have counts for
7 papers
A packet-level digital hardware twin for commissioning megahertz diagnostic edge AI and plasma control system integration in tokamaks
Semin Joung, Abhilasha Dave, Luca Scomparin +6
High-bandwidth plasma diagnostics increasingly provide inputs to machine learning and signal-processing algorithms intended for real-time tokamak control, but the complete path fro…
FPGA-Accelerated Real-Time Diagnostics at DIII-D Using the SLAC Neural Network Library for ML Inference
Abhilasha Dave, Semin Joung, SangKyeun Kim +11
In this work, we demonstrate the deployment of a hardware-accelerated machine learning (ML) inference system integrated into a real-time processing at the DIII-D tokamak fusion rea…
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…
Bayesian neural network for plasma equilibria in the Korea Superconducting Tokamak Advanced Research
Semin Joung
Fusion-graded plasmas are one of the physically complex systems, resulting in continuous establishment of plasma theories for unclarified physical phenomena in order to thoroughly…
Automatic Identification of Edge Localized Modes in the DIII-D Tokamak
Finn H. O'Shea, Semin Joung, David R. Smith +1
Fusion power production in tokamaks uses discharge configurations that risk producing strong Type I Edge Localized Modes. The largest of these modes will likely increase impurities…
Deep neural network Grad-Shafranov solver constrained with measured magnetic signals
Semin Joung, Jaewook Kim, Sehyun Kwak +7
A neural network solving Grad-Shafranov equation constrained with measured magnetic signals to reconstruct magnetic equilibria in real time is developed. Database created to optimi…
Bayesian with Gaussian process based missing input imputation scheme for reconstructing magnetic equilibria in real time
Semin Joung, Jaewook Kim, Sehyun Kwak +7
A Bayesian with GP(Gaussian Process)-based numerical method to impute a few missing magnetic signals caused by impaired magnetic probes during tokamak operations is developed such…