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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Atomic Canyon partners with INL on AI benchmarks
As interest and investment grows around AI applications in nuclear power plants, there remains a gap in standardized benchmarks that can quantitatively compare and measure the quality and reliability of new products.
Nuclear-tailored AI developer Atomic Canyon is moving to fill that gap by entering into a new strategic partnership with Idaho National Laboratory to develop and release the “first comprehensive benchmark suite for evaluating retrieval-augmented generation (RAG) and large language models (LLMs) in nuclear applications.”
Man-Sung Yim, John M. Christenson
Nuclear Technology | Volume 100 | Number 3 | December 1992 | Pages 361-377
Technical Paper | Reactor Operation | doi.org/10.13182/NT92-A34731
Articles are hosted by Taylor and Francis Online.
The control characteristics of a load-following pressurized water reactor are investigated through the application of a nonlinear optimization method to a simplified plant simulator. A model describing the power level control and power distribution control is developed and used to formulate an optimal control problem. In the optimal control problem formulation, all of the safety and system operating limits are included as hard constraints, and the multiple objective functionals are combined into a single performance index. The differences in the calculated optimal load-following control strategies are investigated for the cases of steady-state Tavg (coolant average temperature) program operation and variable Tavg operation at both beginning-of-cycle and near end-of-cycle conditions. The results show that the amount of boron control action for the demanded load variations can be significantly reduced when variable Tavg operation is incorporated into the control policy.