Monte Carlo Simülasyon Sonuçlarının Nükleer Reaktör Kalp Modelleme Yaklaşımlarına Duyarlılığının Araştırılması

Yıl 2022, , 110 - 115, 31.08.2022

Mohammad Allaf , Senem Şentürk Lüle , Üner Çolak

https://doi.org/10.31590/ejosat.1065944

Öz

Monte Carlo benzetimleri, modelleme uygun şekilde yapılırsa söz konusu sistemin nötronik tepkisinin tahmininde doğru sonuçlar verir. Yakıt elemanlarında geometri ve bölünebilir malzeme bileşimlerinin dağılımının modellenmesinde kullanılabilecek yaklaşımlarının duyarlılığı İTÜ TRIGA Mark II Araştırma Reaktörü kullanılarak araştırılmıştır. Dairesel veya altıgen kafes kullanarak kalpteki yakıt elemanı konumlarını belirleme yöntemi bir durum, yakıt elemanlarındaki malzeme bileşimlerinin grup olarak toplanması için üç farklı yöntem diğer bir durum olarak değerlendirilmiştir. Böylece, sıklıkla bu yaklaşımları kullanan deterministik kodların da duyarlılığı araştırılmıştır. Doğrulama çalışması, hem MCNP hem de Serpent Monte Carlo kodlarının sonuçlarının deneysel verilere iyi bir uyum sağladığını göstermiştir. Yakıt bileşiminin farklı şekillerde ele alınmasının sonuçları önemli ölçüde etkilemediği (reaktivitede maksimum 11,1 cent) gözlenmiştir. Ancak yakıt elemanı konum modelleme yaklaşımının etkisi daha belirgindir (reaktivitede maksimum 1 $). Sonuçlardaki bu sapmalar, küçük kapatma marjlarına sahip reaktörlerin nükleer güvenlik değerlendirmelerini etkileyebilir. Deterministik kodların kullanıcılarının, kalpteki geometri ve yakıt bileşimindeki basitleştirmelerin sonuçlarda önemli ölçüde sapmaya neden olacağı gerçeğinin farkında olması gerektiği sonucuna varılmıştır.

Anahtar Kelimeler

Kritiklik, Monte Carlo, Nötronik Analiz, TRIGA Mark II, Serpent, MCNP, Geometrik Modelleme, Yakıt Bileşimi Modellemesi.

The Investigation of the Sensitivity of Monte Carlo Simulation Results to Modelling Approaches for Nuclear Reactor Cores

Öz

Monte Carlo simulations provide accurate results for the neutronic response of the system under consideration if modeling is performed appropriately since it has great influence on the results. Sensitivity analysis of modeling approaches for geometry and fissile material composition distributions in the reactor core was performed by taking ITU TRIGA Mark II Research Reactor into consideration. The method of defining fuel element positions in the core by using circular or hexagonal lattice was considered as one case and three different methods of lumping material compositions in the fuel elements was considered as another case since these approaches are used by deterministic codes hence the accuracy of deterministic codes were also investigated. The validation study showed that both MCNP and Serpent Monte Carlo codes resulted in good agreement with the experimental data. It was observed that the handling of fuel composition in different ways did not influence the results significantly (up to 11.1 cents in reactivity). However, the influence of fuel arrangement is more pronounced (deviation in reactivity calculations is around 1$). These deviations at the results may affect the nuclear safety conclusion of reactors having small shutdown margins. It was also concluded that users of the deterministic codes should be aware of the fact that the simplifications in geometry and fuel composition in the core will result in significant deviation from the reality.

Anahtar Kelimeler

Criticality, Monte Carlo, Neutronic Analysis, TRIGA Mark II, Serpent, MCNP, Geometrical Modeling, Fuel Composition Modeling.

Kaynakça

• Argonne National Laboratory. (2003). MCNP - Version 5, Vol. I: Overview and Theory. Ed., LA-UR-03-1987. https://mcnp.lanl.gov/pdf_files/la-ur-03-1987.pdf
• Asuku, A., Ahmed, Y. A., & Agbo, S. A. (2015). Application of positive period method in the calibration and determination of İntegral Worth of MNSR Control Rod. Nuclear Energy Science and Technology, 9, 319-332. https://doi.org/10.1504/ijnest.2015.075485
• Ćalić, D., Žerovnik, G., Trkov, A., & Snoj, L. (2015). Validation of the Serpent 2 code on TRIGA Mark II benchmark experiments. Applied Radiation and Isotopes, 107, 165-170. https://doi.org/10.1016/j.apradiso.2015.10.022
• Dall’Osso, A. (2002). A transverse buckling based method in core neutronics models equivalence. Annals of Nuclear Energy, 29, 659–671. https://doi.org/10.1016/S0306-4549(01)00068-8
• General Atomics. (1979). Safety Analysis Report of ITU TRIGA Mark II Research Reactor. General Atomics.
• Hartanto, D., Kim, C., & Kim, Y. (2016). An optimization study on the excess reactivity in a linear breed-and-burn fast reactor (B&BR). Annals of Nuclear Energy, 94, 62-71. https://doi.org/10.1016/j.anucene.2016.02.017
• Henry, R., Tiselj, I., & Snoj, L. (2015). Analysis of JSI TRIGA MARK II reactor physical parameters calculated with TRIPOLI and MCNP. Applied Radiation and Isotopes, 97, 140-148. https://doi.org/10.1016/j.apradiso.2014.12.017
• Huda, M. Q., Rahman, M., Sarker, M.M., & Bhuiyan, S. I. (2004). Benchmark analysis of the TRIGA MARK II research reactor using Monte Carlo techniques. Annals of Nuclear Energy, 31, 1299-1313. https://doi.org/10.1016/j.anucene.2004.02.005
• Ivanov, V., & Bousquet, J. (2016). Assessing reactor physics codes capabilities to simulate fast reactors on the example of the BN-600 Benchmark. Kerntechnik, 81, 512-519. https://doi.org/10.3139/124.110730
• Ju, H., Ishiwatari, Y., & Oka, Y. (2015). Fuel rod behavior under normal operating conditions in Super Fast Reactor with high power density. Nuclear Engineering and Design, 289, 166-174. https://doi.org/10.1016/j.nucengdes.2015.04.037
• Khan, R., Stummer, T., Böck, H., & Villa, M. (2011). Neutronics analysis of the initial core of the TRIGA Mark II reactor. Nuclear Engineering and Design, 241, 1463-1468. https://doi.org/10.1016/j.net.2017.11.003
• Lamarsh, J. R., & Baratta, A. J. (2001). Introduction to Nuclear Engineering. Prentice-Hall Inc.
• Leppänen, J., Pusa, M., Viitanen, T., Valtavirta, V., & Kaltiaisenaho, T. (2015). The Serpent Monte Carlo code: status, development and applications in 2013. Annals of Nuclear Energy, 82, 142–150. https://doi.org/10.1016/j.anucene.2014.08.024
• Li, Y., Zhang, B., Wu, H., & Shen, W. (2017). Heterogeneous neutron-leakage model for PWR pin-by-pin calculation. Annals of Nuclear Energy, 110, 443-452. https://doi.org/10.1016/j.anucene.2017.07.002
• Rehman H., & Ahmad, S.-u.-I. (2018). Neutronics analysis of TRIGA Mark II research reactor. Nuclear Engineering and Technology, 50, 35-42. https://doi.org/10.1016/j.net.2017.11.003 Suetomi, E., Nakano, S., Takezawa, H., & Takaki, N. (2017). Core geometry for recriticality prevention against CDA in sodium-cooled fast reactor. Energy Procedia, 131, 45-52. https://doi.org/10.1016/j.egypro.2017.09.444
• Sohrabpour, M., & Ezzati, A. (2009). Monte Carlo simulation and benchmarking of pulsed neutron experiments in variable buckling Beo systems. Annals of Nuclear Energy, 36, 547-549. https://doi.org/10.1016/j.anucene.2009.01.014
• Tetsuo, M., & Nobuhiro, H. (2000). Benchmark Analysis of TRIGA Mark II Reactivity Experiment Using a Continuous Energy Monte Carlo Code MCNP. Journal of Nuclear Science and Technology, 37, 1082-1087. https://doi.org/10.1080/18811248.2000.9714995
• Türkmen, M., & Çolak, Ü. (2014). Analysis of ITU TRIGA Mark II research reactor using Monte Carlo method. Progress in Nuclear Energy, 77, 152-159. https://doi.org/10.1016/j.pnucene.2014.06.015
• Wang, M.-J., Peir, J.-J., Sheu, R.-J., & Liang, J.-H. (2014). Effects of geometry homogenization on the HTR-10 criticality calculations. Nuclear Engineering and Design, 271, 365-360. https://doi.org/10.1016/j.nucengdes.2013.11.062
• Yamamoto, T. (2012). Monte Carlo algorithm for buckling search and neutron leakage-corrected calculations. Annals of Nuclear Energy, 47, 14-20. https://doi.org/10.1016/j.anucene.2012.04.017
• Yamamoto T., & Sakamoto, T. (2018). Monte Carlo method for solving a B1 equation with complex-valued buckling in asymmetric geometries and generation of directional diffusion coefficients. Annals of Nuclear Energy, 122, 37-46. https://doi.org/10.1016/j.anucene.2018.08.025