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Two new partnerships forged in AI and nuclear sectors
The nuclear space is full of companies eager to power new AI development. At the same time, many AI companies want to provide services to the nuclear industry. It should come as no surprise, then, that two new partnerships have recently been announced that further bridge the AI and nuclear sectors.
AtkinsRéalis has announced a partnership with Nvidia that aims to leverage Nvidia’s technologies to deploy “nuclear-powered, large-scale AI factories.” Centrus Energy has announced a partnership with Palantir Technologies to use Palantir’s software in support of Centrus’s plans to expand enrichment capacity.
Sergey V. Bogovalov, Vladimir D. Borman, Ivan V. Tronin, Vladimir N. Tronin
Nuclear Science and Engineering | Volume 194 | Number 12 | December 2020 | Pages 1105-1115
Technical Paper | doi.org/10.1080/00295639.2020.1774229
Articles are hosted by Taylor and Francis Online.
The dependence of the separative power of Iguassu gas centrifuges (GCs) on the rotor diameter and velocity of rotation above m/s is investigated. The separative power is calculated exploring numerical modeling of the gas dynamics and diffusion of the binary mixture in a strong centrifugal field. The separative power is optimized on five internal parameters of the GC: pressure at the wall of the rotor, feed flux, temperature drop along the rotor wall, friction power of the waste scoop and radius of the baffle of the product chamber. The optimized separative power does not depend on the diameter and grows with the velocity as . Optimal values of the internal parameters do not depend on the diameter except optimal pressure, which is inversely proportional to the diameter squared. The optimal pressure grows with velocity as while the optimal feed flux is proportional to . Enrichment of the product flux does not depend on the velocity and diameter in the optimal regime of exploration. Growth of the separative power with is determined by growth of the feed flux with the velocity.