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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.
Chaung Lin, Dih-Hua Yang
Nuclear Technology | Volume 122 | Number 3 | June 1998 | Pages 318-329
Technical Paper | Reactor Operations and Control | doi.org/10.13182/NT98-A2873
Articles are hosted by Taylor and Francis Online.
A fuzzy logic controller (FLC) has been designed to control the water level in an advanced boiling water reactor (ABWR). The performance was comparable to that of a proportional-integral controller. However, the feedwater flow rate did not change smoothly to the steady state. Therefore, a method based on input-output data was adopted to prevent this problem. The data required for deriving the fuzzy rules were the results of various instances of satisfactory manual control of an ABWR simulation model. To construct the membership functions of the linguistic variable, the data were clustered using the fuzzy C-means method. The fuzzy rules were then generated from the data. Because the control actions were not guaranteed to be proper in all the cases and the data were not complete for all the possible operation conditions, the fuzzy rules were modified and extra rules were added based on human knowledge so that satisfactory performance can be achieved. Nevertheless, the method is helpful in deriving a set of important control rules at the beginning stage of design, especially when the importance of the linguistic variables is not clear. The simulation results showed that the designed controller followed the desired control action, which was imposed on the designed data, and the performance of the controller was better than the previously designed FLC.
