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MTR benchmark static calculations with MCNP5 code
Anis Bousbia-Salah
a,*
, Hocine Benkharfia
b
, Nateekoool Kriangchaiporn
c
Alessandro Petruzzi
a
, Francesco D’Auria
a
, Nidal Ghazi
d
a (^) Universita di Pisa, Dipartimento di Ingegneria Meccanica, Nucleare e della Produzione, Via Diotisalvi, 2, 56100 Pisa, Italy b (^) Nuclear research centre of Birine, BP 180 Ain Oussera 17200, Djelfa, Algeria c (^) Thailand Institute of Nuclear Technology, Bangkok, Thailand d (^) Nuclear Engineering Department, Atomic Energy Commission, Damascus, P.O. Box 6091, Syria
Received 16 April 2007; accepted 14 September 2007 Available online 14 November 2007
Abstract
With the sustained development in computer technology, the use of more powerful computational tools becomes mandatory. The
challenge today is to revisit safety features of the existing nuclear research reactors using new generation of computer tools. The objective
is to verify that the safety requirements still met and when necessary to introduce some amendments coming from the new attainments. In
the current paper the IAEA safety-related nuclear research reactors (RR) benchmark problem is reconsidered. The idea consists in per-
forming static calculations of the benchmark using the last version of the MCNP5 code. This later offers updated code models and cross-
section library. The results are afterwards compared with previous calculations and discussed.
Ó 2007 Elsevier Ltd. All rights reserved.
- Introduction
In general, nuclear research reactors are commonly
devoted for neutrons generation for different scientific
and industrial purposes. Actually, high power densities
are involved in the core and consequently specific features are necessary to ensure their safe utilisation. Furthermore
safety evaluations are carried out whenever core reloading,
planned power up-rating or other events are made. In addi-
tion, the content of the safety report has to be updated
whenever a new type or design of fuel is to be used in the
reactor core. As the existing plants have well established
licensing procedures, including well founded analysis meth-
ods, the application of new innovative analysis methods
have to be thoroughly evaluated, with specific emphasis
to the capabilities of producing results that in general terms
might be beneficial to the RR design, operation, and licens-
ing (D’Auria and Bousbia-Salah, 2006).
Nowadays, an established international expertise in rela- tion to computational tools, procedures for their applica- tion, including best-estimate methods supported by uncertainty evaluation, and comprehensive experimental database exists within the safety technology of NPP (Bous- bia-Salah and D’Auria, 2007). The importance of transfer- ring NPP safety technology tools and methods to RR safety technology has been noted in recent IAEA activities (Hamidouche et al., 2004). The ranges of parameters of interest to RR are different from those for NPP due to the wide variety of research reactors, including fuel compo- sition and design, system pressure, adopted materials, and overall system configuration. In the eighties, a safety-related benchmark problem for an idealized generic 10 MW MTR light-water pool-type reactor has been defined (IAEA-TECDOC, 1980). The benchmark was specified under the program of research reactor core conversions from highly enriched uranium (HEU) to low enriched uranium (LEU) cores. It covers large steady state neutron kinetics and thermal-hydraulic calculations and wide range of hypothetical dynamic accidental scenarios. In the current framework, a three
0306-4549/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.anucene.2007.09.
www.elsevier.com/locate/anucene
Available online at www.sciencedirect.com
Annals of Nuclear Energy 35 (2008) 845–
annals of
NUCLEAR ENERGY
dimensional (3D) Monte Carlo calculations are performed
and compared with previous simplified diffusion as well as
Monte Carlo calculations. For this purpose the latest ver-
sion of MCNP5 code (Jeremy, 2003), offering update
cross-section library in ENDF/B-VI data format, is used.
The WIMSD4 code was also considered for the burnup cal-
culations. The MCNP5 results are discussed and compared
with those obtained by other organizations as outlined in
the Appendix F of IAEA-TECDOC (1980).
- Problem modeling
2.1. Brief code description
The general Monte Carlo N-Particle Transport Code (MCNP), developed by Los Alamos National Laboratory
(LANL), has been used to perform the calculations for sev-
eral Benchmark cases. In general, the MCNP code is widely
used to perform numerical simulations for a variety of
cases including complex three-dimensional geometry. In
addition, MCNP uses the continuous nuclear energy and
atomic data libraries ranging from 10^11 to 20 MeV. It also
provides the capability to calculate keff eigenvalues for fis-
sile systems and tally option for the desired information.
MCNP code is considered as a powerful tool for perform-
ing fuel management optimization and HEU to LEU con-
version of the reactor core (Damm and Nabbi, 2002; Pond
et al., 1998).
2.2. Core description
In the current framework both the 10 MW HEU and LEU cores are considered. The core configuration consists of 6 · 5 grid containing 21 MTR fuel and four control ele- ments as reported in Fig. 1. The core is reflected by graph- ite on two opposite sides and surrounded by light water. Axially, all fuel and graphite elements are reflected in their edges by a 15.0 cm Al–H 2 O reflector containing 20% Al
Fig. 1. MTR benchmark core cross section.
Unit:cm
Fig. 2. Standard (23 plates/element) and Control (17 plates/element) fuel element.
Fig. 4. Axial tally cells.
Fig. 3. Radial tally cells.
Fluxes in the middle plane for HEU and LEU at both
BOL and EOL stages are plotted along the x-axis in Figs.
9 and 10.
The distributions of the axial flux in the water trap for
HEU and LEU in two stages of burnup are plotted in Figs.
11 and 12.
As expected for all studied cases, the maximum of ther-
mal flux occurs at the central flux trap and drops exponen-
tially moving away from the core. The thermal flux slightly increases at the interface of fuel/water and fuel/graphite, also in the water gaps between two sets of aluminum plates of control element. On the other hand, the fast flux behaves in opposite way of the thermal flux. Table 6 presents the
Fig. 5. Unit cell used in WIMSD4.
Table 2 Atom densities in 93% enriched fuel meat with 235U burnup Atom densities (Cm^3 · 10E+24)
Burnup (%) Al 235 U 236 U 238 U 239 Pu
0 5.70110E 02 1.61790E 03 0.0 1.20200E 04 0. 5 5.70110E 02 1.53702E 03 1.36535E 05 1.19754E 04 4.14728E 07 10 5.70110E 02 1.45612E 03 2.72623E 05 1.19282E 04 8.03823E 07 25 5.70110E 02 1.21342E 03 6.74525E 05 1.17757E 04 1.75804E 06 30 5.70110E 02 1.13253E 03 8.05315E 05 1.17251E 04 1.97171E 06 45 5.70110E 02 8.89840E 04 1.18999E 04 1.15574E 04 2.44499E 06 50 5.70110E 02 8.08948E 04 1.31486E 04 1.15010E 04 2.50090E 06
(^240) Pu 241 Pu 242 Pu 135 Xe 149 Sm
0 0.0 0.0 0.0 0.0 0. 5 7.82785E 09 3.27177E-10 2.80917E-12 1.62895E 08 1.39595E 07 10 3.04524E 08 2.59777E 09 4.65412E-11 1.56175E 08 1.41498E 07 25 1.68320E 07 3.69683E 08 1.93776E 09 1.31289E 08 1.39448E 07 30 2.30601E 07 5.91755E 08 4.03381E 09 1.24824E 08 1.35540E 07 45 4.38939E 07 1.67028E 07 2.05802E 08 9.90483E 09 1.24911E 07 50 5.12951E 07 2.08922E 07 3.14891E 08 9.17715E 09 1.17549E 07
Table 3 Atom densities in 20% enriched fuel meat with 235 U burnup Atom densities (Cm^3 · 10E+24)
Burnup (%) Al 235 U 236 U 238 U 239 Pu
0 3.81710E 02 2.25360E 03 0.0 8.90050E 04 0. 5 3.81710E 02 2.14092E 03 1.97571E 05 8.88776E 03 1.13074E 05 10 3.81710E 02 2.02824E 03 3.94491E 05 8.87415E 03 2.19337E 05 25 3.81710E 02 1.69018E 03 9.74379E 05 8.82938E 03 4.81672E 05 30 3.81710E 02 1.57752E 03 1.16255E 04 8.81378E 03 5.45263E 05 45 3.81710E 02 1.23949E 03 1.71363E 04 8.76100E 03 6.91062E 05 50 3.81710E 02 1.12688E 03 1.89175E 04 8.74231E 03 7.16456E 05
(^240) Pu 241 Pu 242 Pu 135 Xe 149 Sm
0 0.0 0.0 0.0 0.0 0. 5 2.31749E 07 1.20192E 08 1.07041E-10 2.21224E 08 2.01798E 07 10 8.92882E 07 9.52209E 08 1.77301E 09 2.15200E 08 2.08996E 07 25 4.79108E 06 1.32323E 06 7.22806E 08 1.87846E 08 2.15206E 07 30 6.52398E 06 2.09234E 06 1.48896E 07 1.81255E 08 2.11683E 07 45 1.22646E 05 5.75006E 06 7.36416E 07 1.50798E 08 2.01752E 07 50 1.43552E 05 7.10893E 06 1.11510E 06 1.42346E 08 1.91742E 07
Table 4 WIMSD4 K 1 infinite according to the 235 U burnup for HEU and LEU Burnup (%)
HEU (93%) LEU (20%)
Current calculation WIMSD
ANL
EPRI-
CELL
Current calculation WIMSD
ANL
EPRI-
CELL
BOL
-40 -30 -20 -10 10 20 30 40
X (cm)
0.00E+
5.00E+
1.00E+
1.50E+
2.00E+
2.50E+14 (^) Thermal
Epithermal Fast
0
Flux (n/cm
².s)
Fig. 9a. Neutron fluxes along the X-axis in BOL core of 93% w/o.
EOL
-40 -30 -20 -10 0 10 20 30 40 X (cm)
0.00E+
5.00E+
1.00E+
1.50E+
2.00E+
2.50E+14 (^) Thermal
Fast Epithermal
Flux (n/cm
².s)
Fig. 9b. Neutron fluxes along the X-axis in EOL core of 93% w/o.
BOL
-40 -30 -20 -10 10 20 30 40 X (cm)
0.00E+
4.00E+
8.00E+
1.20E+
1.60E+
2.00E+14 (^) Thermal
Fast Epithermal
Flux (n/cm
².s)
0
Fig. 10a. Neutron fluxes along the X-axis in BOL core of 20% w/o.
EOL
-40 -30 -20 -10 10 20 30 40 X (cm)
0.00E+
5.00E+
1.00E+
1.50E+
2.00E+14 (^) Thermal
Fast Epithermal
Flux (n/cm
².s)
0
Fig. 10b. Neutron fluxes along the X-axis in EOL cores of 20% w/o.
BOL EOL
1.0E+13 1.0E+14 1.0E+ Flux ( n/cm².s )
0
10
20
30
40
Z ( cm )
Epithermal
Thermal
Fast
1.0E+13 1.0E+14 1.0E+
0
10
20
30
40
Z ( cm )
Epithermal
Thermal
Fast
Flux ( n/cm².s )
Fig. 11. Axial neutron fluxes along the Z-axis in BOL and EOL cores of 93% w/o.
BOL EOL
1.0E+13 1.0E+14 1.0E+
0
10
20
30
40
Epithermal
Thermal
Fast
1.0E+13 1.0E+14 1.0E+
0
10
20
30
40
Z ( cm )
Epithermal
Thermal
Fast
Z ( cm )
Flux ( n/cm².s ) Flux ( n/cm².s )
Fig. 12. Axial neutron fluxes along the Z-axis in BOL and EOL cores of 20% w/o.
as well as the value of the recoverable energy released per
fission used by each code. In the current case a value of
193.75 MeV is used.
4.3. Power distributions
The relative radial power distributions for each fuel ele-
ment are illustrated in Figs. 13–16 for both BOL and EOL
stages for HEU and LEU, respectively. As expected, the
maximum power occurs in the trap channel localized in
the centre of the core. These results could be useful for per-
forming realistic steady state or initial conditions for a
thermal-hydraulic system code that considers individually
all the heated channels of the core (Bousbia-Salah et al.,
2006).
- Conclusions
The current work was motivated by the fact that the spread of computational methods and procedures within the scientific community working in research reactor tech- nology is limited. The specific purpose of the present paper is to provide a short overview of a typical application of a best estimate computational tool, with emphasis given to the capabilities of this later. For this purpose, the MTR-type reactor for HEU (93 wt.%) and LEU (20 wt.%) at fresh, BOL and EOL stages were modeled using MCNP5. The results were compared with the previous calculations performed by other organizations in the early 80’s. The calculated eigen- values are in good agreement with the ANL (VIM) results. The flux distributions in three energy groups, thermal, epi-
Fig. 15. Power fractions (%) distributions in each fuel element in BOL 20% core.
Fig. 16. Power fractions (%) distributions in each fuel element in EOL 20% core.
thermal, and fast, were collected with defined tally cells. The
flux and power distributions agree well with the physics of
the benchmark problems. The results of this study could be
benefic for a standalone thermal hydraulic system code that
considers all the core channels individually. It is also useful
for the assessment of a coupling process between a ther-
mal-hydraulic system code and 3D neutron kinetics code.
Acknowledgements
The authors would like to thank Mr. Hakim Mazrou for
his assistance.
References
Bousbia-Salah, A., Jirapongmed, A., D’Auria, F., White, J.R., Hami- douche, T., 2006. Assessment of RELAP5 model for the University of Massachusetts Lowell research reactor. Nuclear Technology and Radiation Protection Journal XXI (1), 3–12.
Bousbia-Salah, A., D’Auria, F., 2007. Use of coupled code technique for best estimate safety analysis of nuclear power plants. Progress in Nuclear Energy 49, 1–13. Damm, G., Nabbi, R., 2002. Status of HEU-LEU Conversion of FRJ-2. International Meeting on Reduced Enrichment for Research and Test Reactors RERTR-2002, Bariloche, Argentina, 3–8 November. D’Auria, F., Bousbia-Salah, A., 2006. Accident analysis in research reactors. 15th Pacific Basin Nuclear Conference at the Sydney, Australia, 15–20 October. Hamidouche, T., Bousbia-Salah, A., Adorni, M., D’Auria, F., 2004. Dynamic calculations of the IAEA safety MTR research reactor benchmark problem using RELAP5/3.2 code. Annals of Nuclear Energy 31, 1385–1402. IAEA 1980. IAEA Research Reactor Core Conversion from the Use of High-Enriched Uranium to the Use of Low Enriched Uranium Fuels Guidebook. IAEA-TECDOC-233. Jeremy, E., 2003. MCNP5 – A General Monte Carlo N-Particle Transport Code, Version 5. LA-UR-03-1987, LANL, Los Alamos, NM. MTR_PC (IAEA 1336). Pond, R.B., Hanan, N.A., Matos, J.E., Maraczy, C., 1998. A neutronic feasibility study for LEU conversion of the Budapest research reactor. International Meeting on Reduced Enrichment for Research and Test Reactors, Sao Paulo, Brazil, 18–23 October.
