Skip to main content
U.S. Department of Energy
Office of Scientific and Technical Information

Variance estimation for radiation analysis and multi-sensor fusion.

Conference ·
OSTI ID:1027042

Variance estimates that are used in the analysis of radiation measurements must represent all of the measurement and computational uncertainties in order to obtain accurate parameter and uncertainty estimates. This report describes an approach for estimating components of the variance associated with both statistical and computational uncertainties. A multi-sensor fusion method is presented that renders parameter estimates for one-dimensional source models based on input from different types of sensors. Data obtained with multiple types of sensors improve the accuracy of the parameter estimates, and inconsistencies in measurements are also reflected in the uncertainties for the estimated parameter. Specific analysis examples are presented that incorporate a single gross neutron measurement with gamma-ray spectra that contain thousands of channels. The parameter estimation approach is tolerant of computational errors associated with detector response functions and source model approximations.

Research Organization:
Sandia National Laboratories
Sponsoring Organization:
USDOE
DOE Contract Number:
AC04-94AL85000
OSTI ID:
1027042
Report Number(s):
SAND2010-6745C
Country of Publication:
United States
Language:
English

Similar Records

Unbalanced Nested Random Effects Estimation of Variance Components
Conference · Tue Feb 21 23:00:00 EST 2023 · OSTI ID:1959005

Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices
Journal Article · Tue May 15 00:00:00 EDT 2018 · SIAM/ASA Journal on Uncertainty Quantification · OSTI ID:1480021

Estimation of sensor measurement errors in reactor coolant systems using multi-sensor fusion
Journal Article · Fri Feb 19 23:00:00 EST 2021 · Nuclear Engineering and Design · OSTI ID:1771903