Year
1998
Abstract
The combined thermal/epithermal neutron instrument (CTEN) was designed at Los Alamos to improve measurement accuracy and mitigate self shielding effects inherent in the differential dieaway technique (DDT). A major goal in this research effort has been the development of a calibration technique that incorporates recently developed matrix and self-shielding corrections using data generated from additional detectors and new acquisition techniques. A comprehensive data set containing both active and passive measurements was generated using 26 different matrices and comprising a total of 1400 measurements. In all, 31 flux-and matrix-dependent parameters, 24 positional parameters, two dieaway times, and a correlated ratio were determined from each of the over 1400 measurements. A reduced list of matrix indicators, prioritized using the alternating conditional expectation (ACE) algorithm, was used to train a neural network using a generalized regression technique (GRNN) to determine matrix- and positioncorrected calibration factors. This paper describes the experimental, analytical, and empirical techniques used to determine the corrected calibration factor for an unknown waste drum. Results from a range of cases are compared with those obtained using a mobile DDT instrument and traditional DDT algorithms.