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2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Christmas Light
’Twas the night before Christmas when all through the house
No electrons were flowing through even my mouse.
All devices were plugged by the chimney with care
With the hope that St. Nikola Tesla would share.
Andrei V. Gribok, Ibrahim K. Attieh, J. Wesley Hines, Robert E. Uhrig
Nuclear Technology | Volume 134 | Number 1 | April 2001 | Pages 3-14
Technical Paper | NURETH-9 | doi.org/10.13182/NT01-A3181
Articles are hosted by Taylor and Francis Online.
Inferential sensing is a method that can be used to evaluate parameters of a physical system based on a set of measurements related to these parameters. The most common method of inferential sensing uses mathematical models to infer a parameter value from correlated sensor values. However, since inferential sensing is an inverse problem, it can produce inconsistent results due to minor perturbations in the data. This research shows that regularization can be used in inferential sensing to produce consistent results. Data from Florida Power Corporation's Crystal River nuclear power plant (NPP) are used to give an important example of monitoring NPP feedwater flow rate.