Solution of a nuclear reactor parameter identification problem

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solutionofnuclea00brai.pdf (4.03 MB)
Authors
Brain Cánepa, Oscar Eduardo
Subjects
Regression analysis
Parameter identification
Nuclear reactor
Advisors
Gerba, Alex, Jr.
Date of Issue
1971-06
Date
June 1971
Publisher
Monterey, California ; Naval Postgraduate School
Language
en_US
Abstract
A continuous identification of parameters is performed on a simulated fast breeder nuclear reactor system using hybrid computation and applying techniques of statistical regression analysis and exponentially-mapped-past functions. Output states which are not directly measurable are estimated by use of a Kalman filter. The method developed in this study is applied to a numerical example which demonstrates that unknown parameters can be identified within 3% of their actual value, with signal noise ratios as low as 10:1 in the measured states. The example also demonstrates that convergence occurs in a reasonably short time.
Type
Thesis
Description
URI
https://hdl.handle.net/10945/15899
Series/Report No
Department
Department of Electrical Engineering
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
87 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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Copyright is reserved by the copyright owner
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