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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.
R. H. Jabs, W. A. Jester
Nuclear Technology | Volume 30 | Number 1 | July 1976 | Pages 24-32
Technical Paper | Reactor Siting | doi.org/10.13182/NT76-A31620
Articles are hosted by Taylor and Francis Online.
A low-level radiation monitoring system for the continuous detection of gaseous effluents, both at the point of release and at the boundary of nuclear facilities, has been developed. The prototype system can achieve sensitivities on the order of 10-10 µCi/ml for certain noble gas radioisotopes and provide continuous isotopic identification and monitoring. The system also provides the ability to place a sodium iodide [Nal(Tl)] detector in the natural environment unattended for long durations and perform continuous gammaray spectroscopy. A unique calibration technique using clathrates of the various inert gases was utilized in evaluating the system’s detection efficiency and sensitivity. Field testing of the system was successfully conducted at a nuclear power generating station. The system’s limitations were also evaluated and are mainly due to the relatively poor resolution of Nal(Tl) detectors and the complexity of the gamma-ray spectra resulting from the gaseous effluent emitted by nuclear power reactors.