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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.
Mathew W. Swinney, Douglas E. Peplow, Bruce W. Patton, Andrew D. Nicholson, Daniel E. Archer, Michael J. Willis
Nuclear Technology | Volume 203 | Number 3 | September 2018 | Pages 325-335
Technical Paper | doi.org/10.1080/00295450.2018.1458558
Articles are hosted by Taylor and Francis Online.
The detection of radioactive sources in an urban setting is greatly complicated by natural background radiation, which emanates from various materials including roadways, sidewalks, soil, and building exteriors. The method presented and demonstrated here represents an effort to characterize the concentration of naturally occurring radioactive material (NORM) in these types of materials. The location surveyed in this work was the Fort Indiantown Gap Combined Arms Collective Training Facility in Lebanon County, Pennsylvania. Over 70 measurements with a high-purity germanium detector were performed to ascertain the NORM concentrations present in the soil, asphalt, gravel, concrete, and walls found throughout the site. Monte Carlo radiation transport calculations were used to obtain detector responses for these various geometries and materials to convert these measurements into NORM concentration estimates. Finally, synthetic spectra were simulated using the predicted source terms and compared to actual measurements, showing acceptable agreement.