Browse > Article

Sensitivity Analysis of Fabrication Parameters for Dry Process Fuel Performance Using Monte Carlo Simulations  

Park Chang Je (Korea Atomic Energy Research Institute)
Song Kee Chan (Korea Atomic Energy Research Institute)
Yang Myung Seung (Korea Atomic Energy Research Institute)
Publication Information
Nuclear Engineering and Technology / v.36, no.4, 2004 , pp. 338-345 More about this Journal
Abstract
This study examines the sensitivity of several fabrication parameters for dry process fuel, using a random sampling technique. The in-pile performance of dry process fuel with irradiation was calculated by a modified ELESTRES code, which is the CANDU fuel performance code system. The performance of the fuel rod was then analyzed using a Monte Carlo simulation to obtain the uncertainty of the major outputs, such as the fuel centerline temperature, the fission gas pressure, and the plastic strain. It was proved by statistical analysis that for both the dry process fuel and the $UO_2$ fuel, pellet density is one of the most sensitive parameters, but as for the fission gas pressure, the density of the $UO_2$ fuel exhibits insensitive behavior compared to that of the dry process fuel. The grain size of the dry process fuel is insensitive to the fission gas pressure, while the grain size of the $UO_2$ fuel is correlative to the fission gas pressure. From the calculation with a typical CANDU reactor power envelop, the centerline temperature, fission gas pressure, and plastic strain of the dry process fuel are higher than those of the $UO_2$ fuel.
Keywords
dry process fuel; ELESTRES; monte marlo simulation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 D.R. Olander, Fundamental Aspects of Nuclear Reactor Fuel Elements, Technical Information Center, U.S. Department Energy. (1976)
2 H.C. Suk, et.al., ELESTRES.M11K Program Users' Manual and Description, KAERI/TR-320/92, Korea Atomic Energy Research Institute, (1992)
3 K.S. Sim, et.al., Modification of ELESTRES Code with New Database of Flux Depression across the Pellet Radius, KAERI/TR-485/94, Korea Atomic Energy Research Institute, (1994)
4 D. Vose, Quantitative Risk Analysis: A Guide Monte Carlo Simulation Method, John Wiley & Sons, New York, (1996)
5 I.E. Oldaker and M. Gacesa, Fuel Design Manual for CANDU 6 Reactor, DM-XX-37000-001, AECL, Canada (1989)
6 K.H. Kang, et al., 'The Thermal Conductivity of Simulated DUPIC Fuel,' J. Nucl. Sci. Tech., Suppl, 3, 776 (2002)
7 M.S. Yang, et al., 'Characteristics of DUPIC Fabrication Technology,' Proc. Int. Conf. Future Nuclear Systems: Challenge towards Second Nuclear Era with Advanced Fuel Cycles. Gobal' 97, p.535, 1997,Yokohama, Japan
8 C.J. Park, et al., 'Development of an Optimization Method for Fuel Design Parameters Using Sampling Techniques,' Proc. Korean Nuclear Society, Kyung-ju, Korea (2003).(CD-Rom)
9 K.C. Song, et al., Irradiation Tests and Performance Evaluation of DUPIC Fuel, KAERI/RR- 2236/2001, MOST, Korea (2001)
10 A. Saltelli, et.al., Sensitivity Analysis, John Wiley & Sons Ltd., (2000)
11 H.S. Park, et al.,' The DUPIC Fuel Cycle Alternatives: Status & Perspective,' Proceedings of the 10th PBNC, 1996, Kobe, Japan
12 Generation 4 Roadmap - Report of the Fuel Cycle Crosscut Group, DOE, FCCG Summary Rpt FR02-00, November 1, (2001)