Calculation of the power peaking factor in a nuclear reactor using support vector regression models

Annals of Nuclear Energy

Volumn 35, Issue 12, 2008, Pages 2200-2205

  Bae, In Ho ^a   Na, Man Gyun ^a   Lee, Yoon Joon ^b   Park, Goon Cherl ^c  

^a Chosun University   (South Korea)

^b Jeju National University   (South Korea)

^c Seoul National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

COOLING; ELECTRIC POWER PLANTS; ERRORS; LINEAR PROGRAMMING; NUCLEAR ENERGY; NUCLEAR FUEL ELEMENTS; NUCLEAR FUEL REPROCESSING; NUCLEAR FUELS; NUCLEAR INDUSTRY; NUCLEAR POWER PLANTS; NUCLEAR PROPULSION; NUCLEAR REACTORS; OPTICAL PROJECTORS; POWER PLANTS; REGRESSION ANALYSIS; STATISTICAL TESTS; VECTORS; VEGETATION; WATER DISTRIBUTION SYSTEMS;

ARTIFICIAL NEURAL NETWORKS; AVERAGE POWERS; CORE NEUTRONS; FLUX SENSORS; FUEL CYCLES; KERNEL FUNCTIONS; LINEAR CONSTRAINTS; LOCAL POWER DENSITIES; MEASURED SIGNALS; NETWORK WEIGHTS; NUCLEAR FUEL RODS; POWER PEAKING FACTORS; QUADRATIC PROGRAMMING PROBLEMS; REACTOR COOLING SYSTEMS; ROOT MEAN SQUARE ERRORS; SUPPORT VECTOR REGRESSION MODELS; SUPPORT VECTOR REGRESSIONS; TEST DATUMS; TRAINING DATA SETS;

NEURAL NETWORKS;

EID: 55949095851     PISSN: 03064549     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.anucene.2008.09.004     Document Type: Article

References (15)

1. ABB Combustion Engineering Inc., 1986. Overview Description of the Core Operation Limit Supervisory System (COLSS). CEN-312-P, Revision 01-P.
2. Chiu S.L. Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems 2 (1994) 267-278
3. Cho, B.O., et al. 1999. MASTER-2.0: Multi-purpose analyzer for static and transient effects of reactors. KAERI, KAERI/TR-1211/99.
4. Gunn, S.R., 1998. Support Vector Machines for Classification and Regression. Technical Report, University of Southampton.
5. Han S., Kim U.S., and Seong P.H. A methodology for benefit assessment of using in-core neutron detector signals in core protection calculator system (CPCS) for Korea standard nuclear power plants (KSNPP). Annals of Nuclear Energy 26 (1999) 471-488
6. In W.K., Hwang D.H., Yoo Y.J., and Zee S.Q. Assessment of core protection and monitoring systems for an advanced reactor SMART. Annals of Nuclear Energy 29 (2002) 609-621
7. Kecman V. Learning and Soft Computing (2001), MIT Press
8. Kim H.C., and Chang S.H. Development of a back propagation network for one-step transient DNBR calculations. Annals of Nuclear Energy 24 (1997) 1437-1446
9. Lee G.C., Baek W.P., and Chang S.H. Improved methodology for generation of axial flux shapes in digital core protection systems. Annals of Nuclear Energy 29 (2002) 805-819
10. Lee J.K., and Han B.S. Modeling of core protection and monitoring system for PWR nuclear power plant simulator. Annals of Nuclear Energy 25 (1998) 409-420
11. Na M.G. Application of a genetic neuro-fuzzy logic to departure from nucleate boiling protection limit estimation. Nuclear Technology 128 (1999) 327-340
12. Na M.G. DNB limit estimation using an adaptive fuzzy inference system. IEEE Transactions on Nuclear Science 47 (2000) 1948-1953
13. Na M.G., Jung D.W., Shin S.H., Lee K.B., and Lee Y.J. Estimation of the nuclear power peaking factor using in-core sensor signals. Nuclear Engineering and Technology 36 (2004) 420-429
14. Na M.G., Hwang I.J., and Lee Y.J. Inferential sensing and monitoring for feedwater flowrate in pressurized water reactors. IEEE Transactions on Nuclear Science 53 (2006) 2335-2342
15. Vapnik V.N. Statistical Learning Theory (1998), John Wiley & Sons