Browse > Article
http://dx.doi.org/10.1016/j.net.2020.02.003

Overcoming the challenges of Monte Carlo depletion: Application to a material-testing reactor with the MCS code  

Dos, Vutheam (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Lee, Hyunsuk (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Jo, Yunki (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Lemaire, Matthieu (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Kim, Wonkyeong (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Choi, Sooyoung (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Zhang, Peng (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Lee, Deokjung (Department of Nuclear Engineering, Ulsan National Institute of Science and Technology)
Publication Information
Nuclear Engineering and Technology / v.52, no.9, 2020 , pp. 1881-1895 More about this Journal
Abstract
The theoretical aspects behind the reactor depletion capability of the Monte Carlo code MCS developed at the Ulsan National Institute of Science and Technology (UNIST) and practical results of this depletion feature for a Material-Testing Reactor (MTR) with plate-type fuel are described in this paper. A verification of MCS results is first performed against MCNP6 to confirm the suitability of MCS for the criticality and depletion analysis of the MTR. Then, the dependence of the effective neutron multiplication factor to the number of axial and radial depletion cells adopted in the fuel plates is performed with MCS in order to determine the minimum spatial segmentation of the fuel plates. Monte Carlo depletion results with 37,800 depletion cells are provided by MCS within acceptable calculation time and memory usage. The results show that at least 7 axial meshes per fuel plate are required to reach the same precision as the reference calculation whereas no significant differences are observed when modeling 1 or 10 radial meshes per fuel plate. This study demonstrates that MCS can address the need for Monte Carlo codes capable of providing reference solutions to complex reactor depletion problems with refined meshes for fuel management and research reactor applications.
Keywords
MCS; Monte Carlo depletion; MCNP6; Material-testing reactor;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 H. Lee, C. Kong, D. Lee, Status of Monte Carlo code development at UNIST, in: Proceedings of PHYSOR Conference, the Westin Miyako, Kyoto, Japan, September 28-October 3, 2014 ([USB]).
2 T.D.C. Nguyen, H. Lee, S. Choi, et al., Validation of UNIST Monte Carlo code MCS using VERA progression problems, Nucl. Eng. Tech. (2019), https://doi.org/10.1016/j.net.2019.10.023.
3 B. Ebiwonjumi, H. Lee, J. Choe, et al., MCS analysis of Westinghouse 3-loop PWR multi-cycle operation, in: Proceedings of KNS Autumn Meeting, Yeosu, Korea, October 25-26, 2018 ([USB]).
4 V. Dos, H. Lee, J. Choe, et al., Validation of Monte Carlo MCS code for OPR -1000 operation, in: Proceedings of NURER Conference, Ramada Plaza Jeju, Korea, September 30- October 3, 2018 ([USB]).
5 H. Lee, E. Jeong, H. Lee, et al., Verification of MCS VHTR modeling capability, in: Proceedings of RPHA17 Conference, Chengdu, China, August 24-25, 2017 ([USB]).
6 T.D.C. Nguyen, H. Lee, et al., LPPT analysis of APR1400 reactor core by UNIST Monte Carlo code MCS, in: Proceedings of RPHA17 Conference, Chengdu, China, August 24-25, 2017 ([USB]).
7 T.D.C. Nguyen, J. Choe, B. Ebiwonjumi, et al., Core design of long-cycle small modular lead-cooled fast reactor, Int. J. Energy Res. 43 (2019) 254-273, https://doi.org/10.1002/er.4258.   DOI
8 P. Zhang, H. Lee, D. Lee, On the transfer matrix of the modified power method, Comput. Phys. Commun. 222 (2018) 102-112, https://doi.org/10.1016/j.cpc.2017.09.022.   DOI
9 H. Lee, S. Choi, D. Lee, A hybrid Monte Carlo/Method-of-Characteristics method for efficient neutron transport analysis, Nucl. Sci. Eng. 180 (2015) 69-85, https://doi.org/10.13182/NSE13-102.   DOI
10 P.K. Romano, B. Forget, Parallel fission bank algorithms in Monte Carlo criticality calculations, Nucl. Sci. Eng. 170 (2017) 125-135, https://doi.org/10.13182/NSE10-98.   DOI
11 M. Pusa, J. Leppanen, Computing the matrix exponential in burnup calculations, Nucl. Sci. Eng. 164 (2017) 140-150, https://doi.org/10.13182/NSE09-14.   DOI
12 A.E. Isotalo, P.A. Aarnio, Comparison of depletion algorithms for large systems of nuclides, Ann. Nucl. Energy 38 (2011) 261-268, https://doi.org/10.1016/j.anucene.2010.10.019.   DOI
13 J. Park, A. Khassenov, W. Kim, et al., Comparative analysis of VERA depletion benchmark through consistent code-to-code comparison, Ann. Nucl. Energy 124 (2019) 385-398, https://doi.org/10.1016/j.anucene.2018.10.024.   DOI
14 W. Kim, H. Lee, S. Choi, et al., Hybrid depletion method for the light water reactor analysis wonkyeong, in: Proceeding of M&C 2017 Conference, Jeju, Korea, April 16-20, 2017 ([USB]).
15 K.O. Kim, B.J. Jun, B. Lee, et al., Comparison of first criticality prediction and experiment of the Jordan research and training reactor (JRTR), Nucl. Eng. Tech. (2019) 6-10, https://doi.org/10.1016/j.net.2019.06.027.   DOI
16 H. Lee, Development of a New Monte Carlo Code for High-Fidelity Power Reactor Analysis Thesis (Doctoral), Ulsan National Institute of Science and Technology, 2019 ([USB]).
17 B.T. Mervin, Monte Carlo and Depletion Reactor Analysis for High-Performance Computing Applications, Doctoral Dissertation University of Tennessee - Knoxville, 2013. https://trace.tennessee.edu/utk_graddiss/2601.
18 V. Dos, H. Lee, Y. Jo, et al., Verification of MCS Monte Carlo code for the JRTR research reactor, in: Proceedings of the PHYSOR Conference, Cancun: American Nuclear Society, Apr 22-26, 2018 ([USB]).
19 A.H. Fadaei, S. Setayeshi, Control rod worth calculation for VVER-1000 nuclear reactor using WIMS and CITATION codes, Prog. Nucl. Energy 51 (2009) 184-191, https://doi.org/10.1016/j.pnucene.2008.03.003.   DOI
20 I.F. Farouki, Full-core burn-up calculations using MCNP6 code for the Jordan research and training reactor, in: Proceeding of Research Reactor Fuel Management Conference, Amman, Jordan, March, 2019.
21 Y. Qiu, Z. Wang, K. Li, et al., Calculation of adjoint-weighted kinetic parameters with the reactor Monte Carlo code RMC, Prog. Nucl. Energy 101 (2017) 424-434, https://doi.org/10.1016/j.pnucene.2017.03.023.   DOI
22 M.H. Rabir, M.R.M. Zin, M.D, et al., Neutron flux and power in RTP core-15, in: Proceeding of AIP Conference, vol. 1704, 2016, https://doi.org/10.1063/1.4940114,050018-1-050018-11.
23 M.L. Fensin, M.R. James, J.S. Hendricks, et al., The new MCNP6 depletion capability, in: Proceedings of ICAPP Conference, Chicago, USA, June 244-28, 2012.
24 I.J. Bratton, Modeling and Validation of the Fuel Depletion and Burnup of the OSU Research Reactor Using MCNPX/CINDER'90, Thesis (Master), The Ohio State University, 2012.
25 C. Gonnier, J. Estrade, G. Bignan, et al., Experimental devices in Jules Horowitz reactor and first orientations for the experimental programs, in: Proceedings of IGORR 18th Meeting, Sydney, Australia, December, 2017.
26 J.S. Hendricks, G.W. Mckinney, M.L. Fensin, et al., MCNPX 2.6.0 Extensions, LAUR-08-2216, April 11, 2008.
27 U.S. Hidayat, A. Agung, M. Lemaire, et al., MCS cycle depletion analysis and validation of excess reactivity and shutdown margin for the Kartini triga Mark II research reactor, in: Proceedings of ICAPP Conference, Juan-Les-Pins, France, May 12-15, 2019.
28 K.N. Choo, M.S. Cho, S.W. Yang, et al., Contribution of Hanaro irradiation technologies to national nuclear R&D, Nucl. Eng. Technol. 46 (2014) 501-512, https://doi.org/10.5516/NET.07.2014.006.   DOI
29 S.A. El-mongy, Overview of Research Reactors (RR) Worldwide and Their Applications, 2018.
30 Saclay CEA, OSIRIS Nuclear Reactors and Services Department, 2008.
31 A. Peron, F. Malouch, C.M. Diop, Improvement of nuclear heating evaluation inside the core of the OSIRIS material testing reactor, in: Proceedings of EPJ Web of Conferences, vol. 106, 2016, https://doi.org/10.1051/epjconf/201610605006, 05006.
32 C.J. Stanley, F.M. Marshall, Advanced test reactore A national scientific user facility, in: Proceedings of ICONE 16th Conference, Orlando, Florida, USA, May 11-15, 2008, https://doi.org/10.1115/icone16-48426.
33 N. Xoubi, Jordan Research and Training Reactor (JRTR) Utilization Facilities, 2010. IAEA-TM-38728.
34 E. Privas, C. Bouret, S. Nicolas, et al., Monte-carlo coupled depletion codes efficiency for research reactor design, in: Proceedings of IGORR 18th Meeting, Sydney, Australia, December, 2017.
35 D. Parrat, G. Bignan, B. Maugard, et al., The future Jules Horowitz material testing reactor: an opportunity for developing international collaborations on a major European irradiation infrastructure, in: Proceedings of International Conference on WWER Fuel Performance, Modelling and Experimental Support, Vama, Bulgaria, September 26- October 3, 2015.
36 F. Jeury, J. Politello, C. D'Aletto, et al., HORUS3D/N neutron calculation tool, a deterministic scheme dedicated to JHR design and safety studies, Nucl. Sci. Eng. 189 (2018) 188-198, https://doi.org/10.1080/00295639.2017.1381505.   DOI
37 J. Yu, H. Lee, M. Lemaire, et al., MCS based neutronics/thermal-hydraulics/fuelperformance coupling with CTF and FRAPCON, Comput. Phys. Commun. 238 (2019) 1-18, https://doi.org/10.1016/j.cpc.2019.01.001.   DOI
38 W. Haeck, B. Cochet, L. Aguiar, Monte Carlo depletion calculations using VESTA 2.1 new features and perspectives, in: Proceedings of PHYSOR Conference, Knoxville, Tennessee, USA, April 15-20, 2012.
39 D.B. Pelowitz, J.T. Goorley, M.R. James, et al., MCNP6 USER'S MANUAL Version 1.0, LA-CP-13-00634, Rev. 0, 2013.
40 H. Lee, W. Kim, P. Zhang, et al., MCS - a Monte Carlo particle transport code for large-scale power reactor analysis, Ann. Nucl. Energy (2019). https://doi.org/10.1016/j.anucene.2019.107276.
41 M.K. Jaradat, V. Radulovic, C.J. Park, et al., Verification of MCNP6 model of the Jordan Research and Training Reactor (JRTR) for calculations of neutronic parameters, Ann. Nucl. Energy 96 (2016) 96-103, https://doi.org/10.1016/j.anucene.2016.06.003.   DOI
42 K.O. Kim, B.J. Jun, B. Lee, et al., Neutronics experiment results in commissioning stage B of JRTR, in: Proceedings of RRFM Conference, Munich, Germany, March 11-15, 2018.
43 J. Jang, W. Kim, S. Jeong, et al., Validation of UNIST Monte Carlo code MCS for criticality safety analysis of PWR spent fuel pool and storage cask, Ann. Nucl. Energy 114 (2018) 495-509, https://doi.org/10.1016/j.anucene.2017.12.054.   DOI
44 J. Yu, H. Lee, H. Kim, et al., Preliminary coupling of the Thermal/Hydraulic solvers in the Monte Carlo code MCS for practical LWR analysis, Ann. Nucl. Energy 118 (2018) 317-335, https://doi.org/10.1016/j.anucene.2018.03.043.   DOI