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The human factor in licensing and operating the next generation of nuclear plants
As human factors specialists working at the intersection of human performance and nuclear operations, we are witnessing one of the nuclear sector’s most significant transitions in decades. The emergence of small modular reactors, microreactors, and other advanced designs is reshaping the industry’s landscape. Digital instrumentation and controls, passive safety systems, and increased automation are creating opportunities for greater safety margins and more flexible operation. These same features also fundamentally redefine what it means to “operate” a nuclear plant. Interactions among human roles, automation, and passive systems shape how people maintain awareness, exercise judgment, and intervene when necessary. These developments affect both operational realities and the regulatory foundations on which nuclear safety is built.
Masashi Ueda, Katsuma Tomobe, Keiichi Setoguchi, Akira Endou
Nuclear Technology | Volume 137 | Number 2 | February 2002 | Pages 163-168
Technical Note | Materials | doi.org/10.13182/NT02-A3265
Articles are hosted by Taylor and Francis Online.
The response of a sensor depends on its operating conditions, and thus it is desirable to develop an in-service method for response time estimation. The applicability of the autoregressive (AR) model for this purpose was examined in the case of the fuel subassembly outlet coolant thermocouples and the primary circuit electromagnetic flowmeter (EMF) of Monju, the prototype fast breeder reactor in Japan.The use of an AR model with exogenous input (ARX model) is possible when the physical variable to be sensed can be observed by an alternative means with a faster response time than that of the sensor in question. In the case of the subassembly outlet thermocouple, the temperature output from an eddy-current sensor, during pseudorandom reactor power variation, served as the exogenous input.In respect to the thermocouple response, AR and ARX modeling were shown to be applicable, and the transient responses thus derived agreed well with each other and with the results measured by means of a step change in sodium temperature.However, the primary circuit EMF response time, estimated using the AR model, decreased with increasing flow rate even when approaching the rated flow, demonstrating that the method was not completely applicable. Nevertheless, it can be concluded that the response is faster than that estimated in the rated condition.