Optimization in the Energy Industry pp 149-165
Critical States of Nuclear Power Plant Reactors and Bilinear Modeling
Chapter
Summary
We present a new system methodology for modeling of nonlinear processes in nuclear power plant cores. This methodology makes use of a variety of different approaches from different mathematical fields. The problem of modeling critical states is reduced to a bilinear subproblem. A scheme which provides stable parameter identification and adaptive control for the nuclear nuclear power plant described by the bilinear differential equation is presented. Abnormal events are found via a system-theoretical approach. Transitions to critical states can be detected by bilinear analysis of observed characteristics and by optimization of sensory measurements. Latent conditions and critical parameters in the reactor core are estimated trough a bilinear modeling.
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References
- 1.V. Arnold. Singularities of smooth mappings. Uspekhi Mat. Nauk., 23(1):3–44, 1968.Google Scholar
- 2.D. Bell and S. Glesston. Theory of nuclear reactors. Moscow, Atomizdat, 1974.Google Scholar
- 3.T. Bose and M. Chen. Conjugate gradient method in adaptive bilinear filtering. IEEE Trans. Signal Process., 43:349–355, 1995.CrossRefGoogle Scholar
- 4.R. Brockett. System theory of group manifolds and coset spaces. SIAM J. Contr., 10:265–284, 1972.MathSciNetCrossRefMATHGoogle Scholar
- 5.K. Chitkara and J. Weisman. Equilibrium approach to optimal in-core fuel management for pressurized water reactors. Nucl. Technol., 24(1):33–49, 1974.Google Scholar
- 6.F. D'Auria, B. Gabaraev, S. Soloviev, O. Novoselsky, A. Moskalev, E. Uspuras, G. M. Galassi, C. Parisi, A. Petrov, V. Radkevich, L. Parafilo, and D. Kryuchkov. Deterministic accident next term analysis for RBMK. Nucl. Eng. Des., 238(4):975–1001, 2008.CrossRefGoogle Scholar
- 7.E. De Klerk, C. Roos, T. Terlaky, H. T. Illés, I. A. J. De Jong, J. Valkó, and J. E. Hoogenboom. Optimization of nuclear reactor reloading patterns. Ann. Oper. Res., 69(0):65–84, 1997.MathSciNetCrossRefMATHGoogle Scholar
- 8.F. Fnaiech, L. Ljung, and Fliess M. Hoogenboom. Recursive identifcation of bilinear systems. Int. J. Control, 45(2):453–470, 1987.CrossRefMATHGoogle Scholar
- 9.R. R. Fullwood and R. E. Hall. Probabilistic risk assessment in the nuclear power industry: fundamentals and applications. Butterworth-Heinemann, New York, 1988.Google Scholar
- 10.V. Goldin, G. Pestriakova, Y. Troishchev, and E. Aristova. Neutron and nuclear regime with self-organisation in reactor with the hard spectrum and carbide fuel. Math. Model., 14(1):27–39, 2002.Google Scholar
- 11.C. S. Gordelier. Nuclear energy risks and benefits in perspective. NEA News, 25(2):4–8, 2007.Google Scholar
- 12.Greenpeace. Subject: Calender of Nuclear Accidents and Events (Updated 21st March), 2007. http://archieve.greenpeace.org/comms/nukes/chernob/rep02.html.
- 13.L. Hunt, R. Su, and G. Meyer. Global transformations of nonlinear systems. IEEE Trans. Autom. Contr., 25(2):4–8, 2007.Google Scholar
- 14.International Atomic Energy Agency. Accident analysis for RBMKs. Safety Reports Series No. 43, IAEA, Vienna, 2005.Google Scholar
- 15.International Atomic Energy Agency. Annual Report 2006. IEA, Vienna, 2006.Google Scholar
- 16.International Energy Agency. IEA energy technology essentials: Nuclear power. IEA, Vienna, March 2007.Google Scholar
- 17.R. Kozma, S. Sato, M. Sakuma, M. Kitamura, and T. Sugiyama. Generalization of knowledge acquired by a reactor core monitoring system based on a neurofuzzy algorithm. Prog. Nucl. Energy, 29:203–214, 1995.CrossRefGoogle Scholar
- 18.J. Lo. Global bilinearizastion of systems with control appearing linearly. SIAM J. Control, 13:879–884, 1975.MathSciNetCrossRefMATHGoogle Scholar
- 19.A. Krener. Bilinear and nonlinear realizations of input-output maps. SIAM J. Control, 13(4):827–834, 1975.MathSciNetCrossRefMATHGoogle Scholar
- 20.Zhian Li, P. M. Pardalos, and S. H. Levine. Space-covering approach and modified Frank-Wolfe algorithm for optimal nuclear reactor reload design. Recent advances in global optimization. Princeton University Press, New Jersey, 1992.Google Scholar
- 21.G. Marchuk. Methods of nuclear reactors calculations. Samizdat, Moscow, 1961.Google Scholar
- 22.N. J. McCormick. Reliability and risk analysis: methods and nuclear power applications. Academic, New York, 1981.Google Scholar
- 23.M. F. Robbe, M. Lepareux, E. Treille, and Y. Cariouc. Numerical simulation of a hypothetical core disruptive accident in a small-scale model of a nuclear reactor. Nucl. Eng. Des., 223(2):159–196, 2003.CrossRefGoogle Scholar
- 24.A. Veinberg and E. Vigner. Physical theory of nuclear reactors [Russian translation]. IL, Moscow, 1961.Google Scholar
- 25.M. L. Wald. Approval is sought for reactors. The New York Times, pages C1–C11, September 25, 2007.Google Scholar
- 26.V. Yatsenko. An engineering design method for automatic control of transverse magnetic field in tokamaks. Proceedings of Conference on The 2nd All-Union Conference on the Engineering Problems of Thermonuclear Reactors, pages 272–273, 1981.Google Scholar
- 27.V. Yatsenko. Dynamic equivalent systems in the solution of some optimal control problems. Avtomatika, 4:59–65, 1984.MathSciNetGoogle Scholar
- 28.V. Yatsenko. Methods of risk analysis for energy objects. Proceedings of Conference on International Energy Conference, July 23–28, Las Vegas, Nevada, USA pages 272–273, 2000.Google Scholar
- 29.V. Yatsenko. Reliability forecasting of nuclear reactor in fuzzy environment. Proceedings of Conference on Problems of Decision Making Under Uncertainties, pages 54–57, 2003.Google Scholar
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