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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
Standards Program
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.
Panagiotis Zacharis, Graeme West, Gordon Dobie, Timothy Lardner, Anthony Gachagan
Nuclear Technology | Volume 202 | Number 2 | May-June 2018 | Pages 153-160
Technical Paper | doi.org/10.1080/00295450.2017.1421803
Articles are hosted by Taylor and Francis Online.
Pressure tubes are critical components of CANDU reactors and other pressurized heavy water–type reactors because they contain the nuclear fuel and the coolant. Manufacturing flaws as well as defects developed during in-service operation can lead to coolant leakage and can potentially damage the reactor. The current inspection process of these flaws is based on manually analyzing ultrasonic data received from multiple probes during planned, statutory outages. Recent advances in ultrasonic inspection tools enable the provision of high-resolution data of significantly large volumes. This highlights the need for an efficient autonomous signal analysis process. Typically, automation of ultrasonic inspection data analysis is approached by knowledge-based or supervised data-driven methods. This work proposes an unsupervised data-driven framework that requires no explicit rules or individually labeled signals. The framework follows a two-stage clustering procedure that utilizes the Density-Based Spatial Clustering of Applications with Noise density-based clustering algorithm and aims to provide decision support for the assessment of potential defects in a robust and consistent way. Nevertheless, verified defect dimensions are essential in order to assess the results and train the framework for unseen defects. Initial results of the implementation are presented and discussed, with the method showing promise as a means of assessing ultrasonic inspection data.