Analysis of calibration data for the uranium active neutron coincidence counting collar with attention to errors in the measured neutron coincidence rate

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• 作者：Stephen Croft^a ; ; Tom Burr^b ; Andrea Favalli^c ; Andrew Nicholson^a
• 关键词：Neutron collar ; Fresh LWR fuel assay ; Linear regression ; Errors in predictor
• 刊名：Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
• 出版年：2016
• 出版时间：1 March 2016
• 年：2016
• 卷：811
• 期：Complete
• 页码：70-75
• 全文大小：825 K

文摘

The declared linear density of ²³⁸U and ²³⁵U in fresh low enriched uranium light water reactor fuel assemblies can be verified for nuclear safeguards purposes using a neutron coincidence counter collar in passive and active mode, respectively. The active mode calibration of the Uranium Neutron Collar – Light water reactor fuel (UNCL) instrument is normally performed using a non-linear fitting technique. The fitting technique relates the measured neutron coincidence rate (the predictor) to the linear density of ²³⁵U (the response) in order to estimate model parameters of the nonlinear Padé equation, which traditionally is used to model the calibration data. Alternatively, following a simple data transformation, the fitting can also be performed using standard linear fitting methods. This paper compares performance of the nonlinear technique to the linear technique, using a range of possible error variance magnitudes in the measured neutron coincidence rate. We develop the required formalism and then apply the traditional (nonlinear) and alternative approaches (linear) to the same experimental and corresponding simulated representative datasets. We find that, in this context, because of the magnitude of the errors in the predictor, it is preferable not to transform to a linear model, and it is preferable not to adjust for the errors in the predictor when inferring the model parameters.