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Division Spotlight
Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
Article considers incorporation of AI into nuclear power plant operations
The potential application of artificial intelligence to the operation of nuclear power plants is explored in an article published in late December in the Washington Examiner. The article, written by energy and environment reporter Callie Patteson, presents the views of a number of experts, including Yavuz Arik, a strategic energy consultant.
Michael D. DeChaine, Madeline Anne Feltus
Nuclear Technology | Volume 111 | Number 1 | July 1995 | Pages 109-114
Technical Note | Nuclear Fuel Cycle | doi.org/10.13182/NT95-A35149
Articles are hosted by Taylor and Francis Online.
The code independent genetic algorithm reactor optimization (CIGARO) system has been developed to optimize nuclear reactor loading patterns. It uses genetic algorithms (GAs) and a code-independent interface, so any reactor physics code (e.g., CASMO-3/SIMULATE-3) can be used to evaluate the loading patterns. The system is compared to other GA-based loading pattern optimizers. Tests were carried out to maximize the beginning of cycle keff for a pressurized water reactor core loading with a penalty function to limit power peaking. The CIGARO system performed well, increasing the keff after lowering the peak power. Tests of a prototype parallel evaluation method showed the potential for a significant speedup.