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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Dry Ice Blasting: A Game-Changer for Safe Cleaning and Decontamination in Nuclear Power Plants
The nuclear energy industry is critical not only for meeting the world’s growing demand for electricity but also for advancing global decarbonization goals. As the sector evolves—through life extensions of existing plants, decommissioning, innovations like small modular reactors (SMRs) and microreactors, and new facility construction—the need for safe, efficient, and environmentally responsible maintenance and decommissioning continues to grow. Whether a plant is coming online, operating beyond its original design life, or entering decommissioning, cleanliness and operational integrity remain non-negotiable. That’s where dry ice blasting stands out—a powerful, safe cleaning method ideally suited for the high-stakes demands of nuclear environments.
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.