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2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Fusion Science and Technology
November 2025
Latest News
AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
Seong-Heon Seo, Wonho Choe, Hong-Young Chang, Seung-Ho Jeong
Fusion Science and Technology | Volume 37 | Number 1 | January 2000 | Pages 89-95
Technical Paper | doi.org/10.13182/FST00-A125
Articles are hosted by Taylor and Francis Online.
The Korea Advanced Institute of Science and Technology (KAIST)-Tokamak Data Acquisition System (KDAS) was originally developed for KAIST-Tokamak (R/a = 0.53 m/0.14 m). It operates on a distributed system based on personal computers and has a driver-based hierarchical structure. Since KDAS can be dynamically composed of any number of available computers, and the hardware-dependent codes can be thoroughly separated into external drivers, it exhibits excellent system performance flexibility and extensibility and can optimize various user needs. It collectively controls the VXI, CAMAC, GPIB, and RS232 instrument hybrids. With these useful and convenient features, it can be applied to any computerized experiment, especially to fusion-related research. The system design and features are discussed in detail.