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An expert-systems approach to automatically determining flaw depth within CANDU pressure tubes

Lardner, Timothy and West, Graeme and Dobie, Gordon and Gachagan, Anthony (2017) An expert-systems approach to automatically determining flaw depth within CANDU pressure tubes. In: 10th International Topical Meeting on Nuclear Plant Instrumentation, Control and Human Machine Interface Technologies, 2017-06-11 - 2017-06-15, Hyatt Regency. (In Press)

Text (Lardner-etal-ITMNPI-2017-An-expert-systems-approach-to-automatically-determining-flaw-depth)
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Delayed Hydride Cracking (DHC) is a crack growth mechanism that occurs in zirconium alloys, including the pressure tubes of CANDU reactors. DHC is caused by hydrogen in solution in zirconium components being diffused to any flaws present, resulting in an increased concentration of hydrogen within these flaws. An increased hydrogen concentration can lead to brittleness, followed by cracking, in high-stress regions of a pressure tube. Regular in-service ultrasonic inspection of CANDU pressure tubes aim to locate and classify any flaws that pose a potential for DHC initiation. A common approach to inspection is the use of a bespoke tool containing multiple ultrasonic transducers to ensure that each point on the pressure tube is inspected from a minimum of three angles during a scan. All flaws from within the inspected pressure tubes must be characterized prior to restarting the reactor, thus the time-consuming analysis process lies on the critical outage path. This process is manually intensive and often requires a significant amount of expert knowledge. A modular system to automatically process outage data to provide decision support to analysts has been developed. This system saves time on the critical outage path while providing repeatable and explicable measurements. Part of the analysis process requires the depth of all flaws to be measured, which is often the most time consuming stage of the analysis process. This paper describes an approach that utilizes captured analysts knowledge to perform automatic flaw depth estimation.