New Algorithm Optimizes Electron Cyclotron Heating Control in DIII-D Tokamak
Researchers have developed the ECH Optimization (ECHO) algorithm to precisely control electron cyclotron heating deposition profiles in the DIII-D tokamak, a key facility for fusion research. The algorithm uses a neural network surrogate model combined with genetic optimization to adjust gyrotron mirror angles and power in real-time. This advance improves tokamak control flexibility for heating, current drive, and plasma stability while maintaining robustness against hardware failures.
Scientists at DIII-D have deployed a new optimization algorithm called ECHO that enhances control of Electron Cyclotron Heating (ECH), a critical heating and plasma control system in tokamak fusion reactors. The algorithm works by using a parallelized neural network surrogate of the TORBEAM code combined with a genetic optimizer to determine optimal gyrotron mirror angles and power levels in real-time, enabling precise targeting of heating deposition locations. The system has been experimentally validated using electron cyclotron emission (ECE) measurements and post-experiment ray tracing analysis, demonstrating reliable performance even when gyrotrons fail or plasma parameters change significantly. ECH serves multiple functions in tokamaks including auxiliary heating, localized current drive for scenario development, MHD stability control, and impurity removal. The algorithm's multitasking capability and robustness to hardware failures represent a significant advance for tokamak operations and future fusion reactor designs.
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- arXiv physicsCenter
Robust Control of ECH Deposition Profiles on DIII-D
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