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2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
Frederick H. Abernathy
Nuclear Science and Engineering | Volume 11 | Number 3 | November 1961 | Pages 290-297
Technical Paper | doi.org/10.13182/NSE61-A26006
Articles are hosted by Taylor and Francis Online.
In designing a heterogeneous reactor it is not enough to be able to calculate the nominal temperature of the fuel elements; one must be able to calculate the probability that the surface temperature is either less than a given value or lies between given limits. This paper presents a general method of analyzing this problem and applies the method to the particular case of a heterogeneous, gascooled reactor. It is shown that one need not assume each statistical variable controlling the temperature to be normally distributed; the individual variables can have any distribution. For design purposes, however, one generally must assume that any value of the parameters, between fixed limits, is equally likely, and for this case it is shown that the fuel element surface temperature itself will be adequately approximated by a normal distribution even though the independent variable has a rectangular frequency function.