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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.”
K. H. G. Ashbee
Nuclear Technology | Volume 95 | Number 3 | September 1991 | Pages 366-371
Technical Note | Radioactive Waste Management | doi.org/10.13182/NT91-A34584
Articles are hosted by Taylor and Francis Online.
Whenever a volume expansion ΔV works against a confining pressure p, such as that which is generated by water of crystallization at encapsulated salts, it is appropriate to use Clapeyron’s equation to estimate the temperature coefficient of that pressure: where ΔVh and ΔSh are, respectively, the volume increase and the entropy decrease for any small increment of water of crystallization. The term ΔSh, and hence dp/dT, is negative because water molecules that take up crystal lattice sites are effectively immobilized. A negative dp/dT means that the confining pressure increases with decreasing temperature, and it is this feature that makes water of crystallization a particularly unwelcome phenomenon in decaying, and therefore cooling, radioactive waste.