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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Deep Space: The new frontier of radiation controls
In commercial nuclear power, there has always been a deliberate tension between the regulator and the utility owner. The regulator fundamentally exists to protect the worker, and the utility, to make a profit. It is a win-win balance.
From the U.S. nuclear industry has emerged a brilliantly successful occupational nuclear safety record—largely the result of an ALARA (as low as reasonably achievable) process that has driven exposure rates down to what only a decade ago would have been considered unthinkable. In the U.S. nuclear industry, the system has accomplished an excellent, nearly seamless process that succeeds to the benefit of both employee and utility owner.
Jacob A. Farber, Daniel G. Cole, Ahmad Y. Al Rashdan, Vaibhav Yadav
Nuclear Technology | Volume 205 | Number 8 | August 2019 | Pages 1043-1052
Technical Paper – Special section on Big Data for Nuclear Power Plants | doi.org/10.1080/00295450.2018.1534484
Articles are hosted by Taylor and Francis Online.
This paper presents data-driven methods to detect loss-of-coolant accidents (LOCAs) in the primary side of a pressurized water reactor. Process data for a variety of accident scenarios have been generated and collected using a generic pressurized water reactor simulator. The data have been used to train kernel density functions, which estimate nonparametric probability density functions based on training data. These density functions have then been used with Bayesian hypothesis testing and maximum likelihood estimation to detect the onset of the LOCAs and to identify where in the primary side the leaks have occurred. The methods have been able to detect the LOCAs for all scenarios tested with an average detection delay of one-seventh the time for the reactor to trip. Furthermore, the methods have been able to correctly identify the leak locations for 92.3% of the scenarios tested, with higher success rates for larger leaks.