ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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Isotopes & Radiation
Members are devoted to applying nuclear science and engineering technologies involving isotopes, radiation applications, and associated equipment in scientific research, development, and industrial processes. Their interests lie primarily in education, industrial uses, biology, medicine, and health physics. Division committees include Analytical Applications of Isotopes and Radiation, Biology and Medicine, Radiation Applications, Radiation Sources and Detection, and Thermal Power Sources.
2021 ANS Winter Meeting and Technology Expo
November 30–December 3, 2021
Washington, DC|Washington Hilton
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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How will you celebrate Nuclear Science Week?
It’s the third week of October, and Nuclear Science Week, first recognized in 2009, has arrived! Nuclear Science Week is an annual opportunity to celebrate nuclear science; recognize the professionals who apply it to solving the world’s most pressing problems; encourage nuclear professional development and networking; and share information with students, educators, and community members about the vital role of nuclear science in the lives of all people.
Panagiotis Zacharis, Graeme West, Gordon Dobie, Timothy Lardner, Anthony Gachagan
Nuclear Technology | Volume 202 | Number 2 | May-June 2018 | Pages 153-160
Technical Paper | dx.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.