Prediction of major transient scenarios for severe accidents of nuclear power plants

IEEE Transactions on Nuclear Science

Volumn 51, Issue 2, 2004, Pages 313-321

  Na, Man Gyun ^a   Shin, Sun Ho ^a   Lee, Sun Mi ^a   Jung, Dong Won ^a   Kim, Soong Pyung ^a   Jeong, Ji Hwan ^b   Lee, Byung Chul ^c  

^a Chosun University   (South Korea)

^b Cheonan College of Foreign Studies   (South Korea)

^c Future and Challenges Inc   (South Korea)

Author keywords

Event classification; Neural network; Scenario identification; Severe accident

Indexed keywords

ACCIDENT PREVENTION; APPROXIMATION THEORY; COMPUTER SIMULATION; COOLANTS; NEURAL NETWORKS; NUCLEAR REACTOR ACCIDENTS; TRANSIENTS;

EVENT CLASSIFICATION; SCENARIO IDENTIFICATION; SEVERE ACCIDENTS; STEAM GENERATOR TUBE RUPTURE (SGTR);

NUCLEAR POWER PLANTS;

EID: 2442696716     PISSN: 00189499     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNS.2004.825090     Document Type: Article

References (22)

1. C. H. Roh, H. S. Chang, H. G. Kim, and S. H. Chang, "Identification of reactor vessel failures using spatiotemporal neural networks," IEEE Trans. Nucl. Sci., vol. 43, pp. 3223-3229, Dec. 1996.
2. J. W. Hines, D. J. Wrest, and R. E. Uhrig, "Signal validation using an adaptive neural fuzzy inference system," Nucl. Technol., vol. 119, no. 2, pp. 181-193, Aug. 1997.
3. P. Fantoni, S. Figedy, and A. Racz, "A neuro-fuzzy model applied full range signal validation of PWR nuclear power plant data," in Proc. Int. Conf. Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS'98), Belgium, 1998.
4. M. G. Na, Y. R. Sim, K. H. Park, S. M. Lee, D. W. Jung, S. H. Shin, B. R. Upadhyaya, K. Zhao, and B. Lu, "Sensor monitoring using a fuzzy neural network with an automatic structure constructor," IEEE Trans. Nucl. Sci., vol. 50, pp. 241-250, Apr. 2003.
5. E. B. Bartlett and R. E. Uhrig, "Nuclear power plant diagnostics using an artificial neural network," Nucl. Technol., vol. 97, pp. 272-281, Mar. 1992.
6. M. Marseguerra and E. Zio, "Fault diagnosis via neural networks: The Boltzmann machine," Nucl. Sci. Eng., vol. 117, no. 3, pp. 194-200, July 1994.
7. H. G. Kim, S. H. Chang, and B. H. Lee, "Optimal fuel loading pattern design using an artificial neural network and a fuzzy rule-based system," Nucl. Sci. Eng, vol. 115, no. 2, pp. 152-163, Oct. 1993.
8. J. H. Lee, H. J. Sim, C. S. Jang, and C. H. Kim, "Incorporation of neural networks into simulated annealing algorithm for fuel assembly loading pattern optimization in a PWR," in Proc. Int. Conf. Physics of Nuclear Science and Technology-American Nuclear Society, vol. 1, Long Island, NY, Oct. 5-8, 1998, p. 75.
9. M. G. Na, "Design of a genetic fuzzy controller for the nuclear steam generator water level control," IEEE Trans. Nucl. Sci., vol. 45, pp. 2261-2271, Aug. 1998.
10. S. W. Cheon and S. H. Chang, "Application of neural networks to a connectionist expert system for transient identification in nuclear power plants," Nucl. Technol., vol. 102, no. 2, pp. 177-191, May 1993.
11. Y. Bartal, J. Lin, and R. E. Uhrig, "Nuclear power plant transient diagnostics using artificial neural networks that allow "don't-know" classifications," Nucl. Technol., vol. 110, no. 3, pp. 436-449, June 1995.
12. User's Manual, vol. vol. 1, 2, 3,4, Fauske and Associates, Inc., 1990.
13. Korea Hydro & Nuclear Power Company (in APR 1400 SSAR), June 2002.
14. D. F. Specht, "Probabilistic neural networks," Neural Networks, vol. 3, no. 1, pp. 109-118, 1990.
15. R. E. Shaffer, S. L. Rose-Pehrsson, and R. A. McGill, "A comparison study of chemical sensor array pattern recognition algorithms," Analytica Chimica Acta, vol. 384, no. 3, pp. 305-317, Apr. 1999.
16. J.-S. R. Jang, "ANFIS: Adaptive-network-based fuzzy inference systems," IEEE Trans. Syst., Man, Cybern., vol. 23, pp. 665-685, May 1993.
17. E. H. Mamdani and S. Assilian, "An experiment in linguistic synthesis with a fuzzy logic controller," Int. J. Man-Machine Studies, vol. 7, pp. 1-13, 1975.
18. T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. Syst., Man, Cybern., vol. SMC-1, pp. 116-132, Jan./Feb. 1985.
19. T. Eklov, P. Martensson, and I. Lundstorm, "Selection of variables for interpreting multivariate gas sensor data," Analytica Chimica Acta, vol. 381, pp. 221-232, Feb. 1999.
20. B. K. Lavine, A. Moores, and L. K. Helfend, "A genetic algorithm for pattern recognition analysis of pyrolysis gas Chromatographic data," J. Anal. Appl. Pyrolysis, vol. 50, pp. 47-62, Apr. 1999.
21. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
22. M. Mitchell, An Introduction to Genetic Algorithms. Cambridge, MA: MIT Press, 1996.