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AI and productivity growth
Craig Piercycpiercy@ans.org
This month’s issue of Nuclear News focuses on supply and demand. The “supply” part of the story highlights nuclear’s continued success in providing electricity to the grid more than 90 percent of the time, while the “demand” part explores the seemingly insatiable appetite of hyperscale data centers for steady, carbon-free energy.
Technically, we are in the second year of our AI epiphany, the collective realization that Big Tech’s energy demands are so large that they cannot be met without a historic build-out of new generation capacity. Yet the enormity of it all still seems hard to grasp.
or the better part of two decades, U.S. electricity demand has been flat. Sure, we’ve seen annual fluctuations that correlate with weather patterns and the overall domestic economic performance, but the gigawatt-hours of electricity America consumed in 2021 are almost identical to our 2007 numbers.
Cheng Peng, Jian Deng, Jiang Wu
Nuclear Science and Engineering | Volume 198 | Number 11 | November 2024 | Pages 2190-2208
Research Article | doi.org/10.1080/00295639.2023.2292930
Articles are hosted by Taylor and Francis Online.
Because of its superior thermal-hydraulic qualities, liquid sodium has been applied to a variety of industries, including energy storage, solar energy, sodium-cooled fast reactors, and aerospace. However, fires brought on by sodium leaks at high pressure can have major thermodynamic repercussions and put employees and equipment in use at risk directly or indirectly. As a result, a realistic and accurate forecast of the combustion behavior of sodium droplet swarm can offer technical backing for the use of liquid sodium in engineering as well as a way of sodium fire prevention and control. Spray dynamics (droplet settling, droplet particle size distribution, etc.), combustion kinetics (premixed combustion, gas phase combustion, etc.), sodium aerosol diffusion, and other specialized phenomena all contribute to the complex process of sodium droplet swarm combustion. The NACOM code created by Brookhaven National Laboratory for sodium droplet swarm combustion is utilized in this paper as a framework. The code is first validated using the benchmark of the sodium droplet swarm combustion tests carried out by prestigious institutions. The validation results demonstrate that the code’s drag model, droplet combustion model, and heat transfer model are to blame for the significantly overestimated thermodynamic effects of sodium droplet swarm combustion. NACOM is subsequently developed twice for the authors’ previously developed vapor-liquid two-layer-structure drag model, chemical kinetic combustion model, and suitable heat transfer coefficient. It is then thoroughly assessed for the separate-effects tests and integral-effects test. The evaluation results demonstrate that the optimized drag model accelerates the settling of sodium droplets due to the consideration of the sodium-vapor drag reduction effect, reducing the thermodynamic effects of liquid sodium combustion; the optimized premixed combustion model can accurately predict the low-temperature sodium droplet swarm combustion conditions, resolving the issue of serious misvaluation of the original version of NACOM. The associated research findings can serve as valuable resources and tools for deeper comprehension of the combustion effects and mechanisms of sodium droplet swarm under various operating settings (such as leakage rate and oxygen concentration).
