VALIDATION OF PWR-FUEL CODE FOR STATIC PARAMETERS IN THE LWR CORE BENCHMARK

Authors

  • Iman Kuntoro Center for Nuclear Reactor Technology and Safety, BATAN
  • Surian Pinem Center for Nuclear Reactor Technology and Safety, BATAN
  • Tagor Malem Sembiring Center for Nuclear Energy System Assesment, BATAN

DOI:

https://doi.org/10.17146/tdm.2018.20.3.4650

Keywords:

Validation, PWR-FUEL code, static parameter

Abstract

The PWR-FUEL code is a multi dimensional, multi group diffusion code with nodal and finite difference methods. The code will be used to calculate the fuel management of PWR reactor core. The result depends on the accuracy of the codes in producing the core effective multiplication factor and power density distribution. The objective of this research is to validate the PWR-FUEL code for those cases. The validation are carried out by benchmarking cores of IAEA-2D, KOERBERG-2D and BIBLIS-2D. The all three cases have different characteristics, thus it will result in a good accuracy benchmarking. The calculation results of effective multiplication factor have a maximum difference of 0.014 %, which is greater than the reference values. For the power peaking factor, the maximum deviation is 1.75 % as compared to the reference values. Those results show that the accuracy of PWR-FUEL in calculating the static parameter of PWR reactor benchmarks are very satisfactory.

 

References

Pinem S., Surbakti T. Analysis on Neutronic Parameters of The Ap1000 Reactor Core. in: Prosiding Seminar Nasional Teknologi Energi Nuklir 2016. 2016. pp. 569-75.

Pinem S., Sembiring T.M., Tukiran, Deswandri, Sunaryo G.R. Reactivity Coefficient Calculation for AP1000 Reactor Using the NODAL3 Code. J. Phys. Conf. Ser. 2018. 962(1):1-8.

https://doi.org/10.1088/1742-6596/962/1/012057

Kuntoro I., Pinem S., Sembiring T.M. Analysis of Reactivity Coefficient Change Due To Burn Up in Ap1000 Reactor Core Using Nodal3. Tri Dasa Mega. 2017. 19(3):131.

https://doi.org/10.17146/tdm.2017.19.3.3668

Susilo J., Pane J.S. Fuel burn-up distribution and transuranic nuclide contents produced at the first cycle operation of ap1000. Tri Dasa Mega. 2016. 18(2):101-11.

https://doi.org/10.17146/tdm.2016.18.2.2665

Liem P.H., Pinem S., Sembiring T.M., Tran H. Status on development and verification of reactivity initiated accident analysis code for PWR (NODAL3). Nucl. Sci. Technol. 2016. 6(1):1-13.

https://doi.org/10.53747/jnst.v6i1.139

Pinem S., Sembiring T.M., Liem P.H. The verification of coupled neutronics thermal hydraulics code NODAL3 in the PWR rod ejection benchmark. Sci. Technol. Nucl. Install. 2014. 2014:1-9.

https://doi.org/10.1155/2014/845832

Isnaini M.D., Widodo S., Subekti M. The thermal-hydraulics analysis on radial and axial power fluctuation for ap1000 reactor. Tri Dasa Mega. 2018. 2015:79-86.

https://doi.org/10.17146/tdm.2015.17.2.2290

Ekariansyah A.S. Analisis kondisi teras reaktor daya maju AP1000 pada kecelakaan small break loca. Tri Dasa Mega. 2015. 17(2):87-98.

https://doi.org/10.17146/tdm.2015.17.2.2291

Andi Sofrany Ekariansyah, Surip Widodo, Susyadi, D.T. Sony Tjahyani H.T. Verifikasi Kecelakaan Hilangnya Aliran Air Umpan Pada Reaktor Daya PWR Maju. Tri Dasa Mega. 2012. 14(2):76-90.

Moghaddam N.M., Fadaei A.H., Zahedi E. Evaluating the effect of using different sets of enrichment for FAs on fuel management optimization using CA. Ann. Nucl. Energy. 2011. 38(4):835-45.

https://doi.org/10.1016/j.anucene.2010.11.026

Hill N.J., Parks G.T. Pressurized water reactor in-core nuclear fuel management by tabu search. Ann. Nucl. Energy. 2015. 75:64-71.

https://doi.org/10.1016/j.anucene.2014.07.051

Aghaie M., Nazari T., Zolfaghari A., Minuchehr A., Shirani A. Investigation of PWR core optimization using harmony search algorithms. Ann. Nucl. Energy. 2013. 57:1-15.

https://doi.org/10.1016/j.anucene.2013.01.046

Mahmoudi S.M., Aghaie M., Bahonar M., Poursalehi N. A novel optimization method, Gravitational Search Algorithm (GSA), for PWR core optimization. Ann. Nucl. Energy. 2016. 95:23-34.

https://doi.org/10.1016/j.anucene.2016.04.035

PWR-FUEL PWR In-Core Fuel Management Code. User Guide. 2012.(August)

Sembiring T.M., Pinem S. The validation of the NODAL3 code for static cases of the PWR benchmark core. J. Nucl. Sci. Technol. Ganendra. 2012. 15(2):82-92.

https://doi.org/10.17146/gnd.2012.15.2.18

Pinem S., Sembiring T.M., Liem P.H. NODAL3 Sensitivity Analysis for NEACRP 3D LWR Core Transient Benchmark (PWR). Sci. Technol. Nucl. Install. 2016. 2016:1-11.

https://doi.org/10.1155/2016/7538681

Pinem S., Sembiring T.M., Tukiran Verifikasi Program PWR-FUEL Dalam Manajemen Bahan Bakar PWR. J. Sains dan Teknol. Nukl. Indonesia. 2015. 16(1)

https://doi.org/10.17146/jstni.2015.16.1.2357

E.Z. Muller Z.J.W. Benchmarking with the multigroup diffusion high-order response matrix method. Ann. Nucl. Energy. 1991. 18(9):535-44.

https://doi.org/10.1016/0306-4549(91)90098-I

Guessous N., Akhmouch M. Higher order analytical nodal methods in response-matrix formulation for the multigroup neutron diffusion equations. Ann. Nucl. Energy. 2002. 29:1765-78.

https://doi.org/10.1016/S0306-4549(02)00015-4

Meneses A.A. de M., Araujo L.M., Nast F.N., da Silva P.V., Schirru R. Application of metaheuristics to Loading Pattern Optimization problems based on the IAEA-3D and BIBLIS-2D data. Ann. Nucl. Energy. 2018. 111:329-39.

https://doi.org/10.1016/j.anucene.2017.09.008

Yadav R.D.S., Gupta H.P. Optimization Studies of Fuel Lading Pattern for a Typical Pressurized Water Reactor (PWR) Using Particle Swarm Method. Ann. Nucl. Energy. 2011. 38(9):2086-95

https://doi.org/10.1016/j.anucene.2011.05.019

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Published

2018-10-30

How to Cite

Kuntoro, I., Pinem, S., & Sembiring, T. M. (2018). VALIDATION OF PWR-FUEL CODE FOR STATIC PARAMETERS IN THE LWR CORE BENCHMARK. Jurnal Teknologi Reaktor Nuklir Tri Dasa Mega, 20(3), 111–122. https://doi.org/10.17146/tdm.2018.20.3.4650