Solution of a nuclear reactor parameter identification problem
By:  Oscar Educardo Brain Canepa
Publisher: Naval Postgraduate School
Published: 1971
Place of publication: Monterey, California
Language: eng
Number of pages: 87
Description: 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. (Author)
Notes: "June 1971".

Thesis (Degree of E.E.)--Naval Postgraduate School, June 1971.

Bibliography: l. 85-86.

Approved for public release; distribution unlimited.

Peruvian Navy author.