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Argonne: Where AI research meets education and training
Last September, in the Chicago suburb of Lemont, Ill., Argonne National Laboratory hosted its first AI STEM Education Summit. More than 180 educators from high schools, community colleges, and universities; STEM administrators; and experts in various disciplines convened at “One Ecosystem, Many Pathways–Building an AI-Ready STEM Workforce” to discuss how artificial intelligence is reshaping STEM-related industries, including the implications for the nuclear engineering classroom and workforce.
K. N. Prasad, W. A. Jester, F. J. Remick
Nuclear Technology | Volume 24 | Number 2 | November 1974 | Pages 252-259
Technical Paper | Analysis | doi.org/10.13182/NT74-A31481
Articles are hosted by Taylor and Francis Online.
Post-cutting chip activation analysis has been developed for the study of tool wear. In this technique, chips produced during machining are analyzed by neutron activation for a tracer that occurs in the tool. Tungsten was used as a tracer that was inherently present in the tool, and europium was used as a tracer that was added to the tool during its production. It was found that europium fails to effectively meet all the requirements of a tracer in the tool. By using the tungsten in high-speed steel tools and Ti—6Al—4 V alloy work material, it was shown that (a) a random selection of chips was ineffective in providing useful tool wear information and (b) the traditionally ignored break-in period of tool wear could be used to predict tool life to within the same margin of error as conventional methods, but with potential savings in time and cost.