Application of information technologies (genetic algorithms, neural networks, parallel calculations) in safety analysis of Nuclear Power Plants
https://doi.org/10.15514/ISPRAS-2014-26(2)-6
Abstract
This paper investigates important issues in three types of safety assessment methodologies commonly applied for Nuclear Power Plants (NPP). These methodologies are i) dynamic probabilistic safety assessment (DPSA) where application of genetic algorithm (GA) is shown to improve the efficiency of the analysis, ii) deterministic safety assessment (DSA) with meta model representation of the system using pre-performed computational fluid dynamics (CFD) code and iii) vulnerability search (e.g. identification of accident scenarios in an NPP) with application of neural network (NN). The use of advanced computational tools and methods such as genetic algorithms, neural networks and parallel computations improve the efficiency of safety analysis. To achieve the best effect, these advanced technologies are to be integrated with existing classical methods of safety analysis of the NPP.
About the Authors
Yu. B. Vorobyev
SRU «MPEI», Moscow
Russian Federation
Russian Federation
P. Kudinov
Royal Institute of Technology, Stockholm
Sweden
Sweden
M. Jeltsov
Royal Institute of Technology, Stockholm
Sweden
Sweden
K. Kööp
Royal Institute of Technology, Stockholm
Sweden
Sweden
T. V. Nhat
SRU «MPEI», Moscow
Russian Federation
Russian Federation
References
1. Belhadj M, Hassan M, Aldemir T, On the need for dynamic methodologies in risk and reliability studies, Reliability Engineering and System Safety, 1992, V38, 219-236
2. Coppit D, Sullivan K J, Dugan J B. Formal semantics of models for computational engineering- a case study on dynamic fault trees, Software Reliability Engineering,11th International Symposium, San Jose, CA. USA, 8 –11 Oct. 2000, 270-282
3. Marseguerra M, Zio E, Devooght J, Labeau P E. A concept paper on dynamic reliability via Monte Carlo simulation, Mathematics and Computers in Simulation, 1998,V47 , 371-382
4. Hakobyan A P. Severe Accident Analysis using Dynamic Accident Progression Event Trees, PhD Thesis, Ohio State University, 2006, 225
5. Mitchell Melanie , An Introduction to Genetic Algorithms, A Bradford Book The MIT Press, Cambridge, Massachusetts, London, England, Fifth printing, 1999, 158
6. Vorob'ev YU.B., Kuznetsov V.D. , Ispol'zovanie sovremennykh integral'nykh kodov dlya upravleniya bezopasnost'yu АEHS [ The use of modern best estimate codes for controlling of the NPP safety ], Vestnik MEHI [ Herald of MPEI ], 2001, №5, pp 31-37 (in Russian).
7. Bajbakov V.D., Vorob'ev YU.B., Kuznetsov V.D. , Kody dlya raschetov yadernykh reaktorov [ Calculation codes for nuclear reactors ], , Izdatel'stvo MEHI [ MPEI Publ. ], М., 2003, 162 p (in Russian).
8. Mansuri Masud, Аnaliz neopredelennostej parametrov pri modelirovanii dinamicheskikh protsessov v konturakh АEHS s VVEHR [ Uncertainty analysis of parameters by modeling of dynamic processes for NPP with VVER ], dis. k.t.n. [ Phd thesis ], MEHI [ MPEI ], 2005, 166 p (in Russian).
9. Vorobyev Y, Kudinov P. Development and Application of a Genetic Algorithm Based Dynamic PRA Methodology to Plant Vulnerability Search, proceedings ANS PSA 2011 International Topical Meeting on Probabilistic Safety Assessment and Analysis, Wilmington, NC, on CD-ROM, American Nuclear Society, LaGrange Park, IL, on CD-ROM, March 13-17, 2011, 15
10. David W. Scott , Stephan R. Sain, Multi-dimensional Density Estimation, Handbook of Statistics, 2005, V24, 229 - 261
11. D.L. Aumiller, E.T. Tomlinson, R. C. Bauer, A Coupled RELAP5-3D/CFD Methodology with a Proof-of-Principle Calculation, Nuclear Engineering and Design, 2001,V205, 83-90
12. M. Jeltsov, K. Kööp, W. Villanueva, P. Kudinov, Development of multi-scale simulation methodology for analysis of heavy liquid metal thermal hydraulics with coupled STH and CFD codes, Proceedings of The 9th International Topical Meeting on Nuclear Thermal-Hydraulics, Operation and Safety (NUTHOS-9) N9P0298 Kaohsiung, Taiwan, September 9-13, on CD-ROM, 2012, 18
13. S. E. Yakush, N. T. Lubchenko and P. Kudinov, SURROGATE MODELS FOR DEBRIS BED DRYOUT, The 15th International Topical Meeting on Nuclear Reactor Thermal - Hydraulics, NURETH-15, Pisa, Italy, May 12-17, on CD-ROM, 2013, 16
Review
For citations:
Vorobyev Yu.B., Kudinov P., Jeltsov M., Kööp K., Nhat T.V. Application of information technologies (genetic algorithms, neural networks, parallel calculations) in safety analysis of Nuclear Power Plants. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2014;26(2):137-158. (In Russ.) https://doi.org/10.15514/ISPRAS-2014-26(2)-6
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