Nuclear-data evaluation based on direct and indirect measurements with general correlations

Conference · Fri Jan 01 00:00:00 EST 1988

OSTI ID:5123652

Muir, D W

Optimum procedures for the statistical improvement, or updating, of an existing nuclear-data evaluation are reviewed and redeveloped from first principles, consistently employing a minimum-variance viewpoint. A set of equations is derived which provides improved values of the data and their covariances, taking into account information from supplementary measurements and allowing for general correlations among all measurements. The minimum-variance solutions thus obtained, which we call the method of ''partitioned least squares,'' are found to be equivalent to a method suggested by Yu. V. Linnik and applied by a number of authors to the analysis of fission-reactor integral experiments; however, up to now, the partitioned-least-squares formulae have not found widespread use in the field of basic data evaluation. This approach is shown to give the same results as the more commonly applied Normal equations, but with reduced matrix inversion requirements. Examples are provided to indicate potential areas of application. 10 refs.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• DOE Contract Number: W-7405-ENG-36
• OSTI ID: 5123652
• Report Number(s): LA-UR-88-1697; CONF-880546-5; ON: DE88010916
• Resource Relation: Conference: International conference on nuclear data for science and technology, Mito, Japan, 30 May 1988
• Country of Publication: United States
• Language: English

Related Subjects

73 NUCLEAR PHYSICS AND RADIATION PHYSICS
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
NUCLEAR DATA COLLECTIONS
CORRELATIONS
DATA COMPILATION
DATA COVARIANCES
LEAST SQUARE FIT
MODIFICATIONS
STATISTICAL MODELS
DATA
INFORMATION
MATHEMATICAL MODELS
MAXIMUM-LIKELIHOOD FIT
NUMERICAL SOLUTION
651000* - Nuclear Physics
990230 - Mathematics & Mathematical Models- (1987-1989)