[1. Oak Ridge National Laboratory. (2011). SCALE: A comprehensive modeling and simulation suite for nuclear safety analysis and design. Version 6.1. Oak Ridge, TN, USA: ORNL. (ORNL/TM-2005/39).]Search in Google Scholar
[2. US Nuclear Regulatory Commission. (2013). SCALE/ TRITON Primer: A primer for light water reactor lattice physics calculations using SNAP. U.S. NCR.]Search in Google Scholar
[3. MIT Computational Reactor Physics Group. (2013). BEAVRS – benchmark for evaluation and validation of reactor simulations. Rev. 1.1.1. Cambridge, UK: MIT CRPG.]Search in Google Scholar
[4. MIT Computational Reactor Physics Group. (2017). BEAVRS – benchmark for evaluation and validation of reactor simulations. Rev. 2.0.1. Cambridge, UK: MIT CRPG.]Search in Google Scholar
[5. Horelik, N., Herman, B. R., Forget, B., & Smith, K. (2013). Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS). In International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, May 5–9, 2013, Sun Valley, ID, USA (Vol., 4, pp. 2986–2999). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[6. Park, H. J., Lee, H. C., Shim, H. J., & Cho, J. Y. (2016). Real variance analysis of Monte Carlo eigenvalue calculation by McCARD for BEAVRS benchmark. Ann. Nucl. Energy, 90, 205–211. doi: 10.1016/j.anucene.2015.12.009.10.1016/j.anucene.2015.12.009]Open DOISearch in Google Scholar
[7. Liu, S., Liang, J., Wu, Q., Guo, J., Huang, S., Tang, X., Li, Z., & Wang, K. (2017). BEAVRS full core burnup calculation in hot full power condition by RMC code. Ann. Nucl. Energy, 101, 434–446. doi: 10.1016/j.anucene.2016.11.033.10.1016/j.anucene.2016.11.033]Open DOISearch in Google Scholar
[8. Wan, C., Cao, L., Wu, H., & Shen, W. (2017). Uncertainty analysis for the assembly and core simulation of BEAVRS at the HZP conditions. Nucl. Eng. Des., 315, 11–19. doi: 10.1016/j.nucengdes.2017.02.020.10.1016/j.nucengdes.2017.02.020]Search in Google Scholar
[9. Electric Power Research Institute. (2015). PWR fuel reactivity depletion uncertainty quantification – methods validation using BEAVRS Flux Map Data. EPRI.]Search in Google Scholar
[10. Leppänen, J., Mattila, R., & Pusa, M. (2014). Validation of the Serpent-ARES code sequence using the MIT BEAVRS benchmark – initial core at HZP conditions. Ann. Nucl. Energy, 69, 212–225. doi: 10.1016/j.anucene.2014.02.014.10.1016/j.anucene.2014.02.014]Search in Google Scholar
[11. Gang, L., Dunfu, S., Baoyin, Z., Rui, L., Zehua, H., & Yuanguang, F. (2016). The application of JMCT to HZP of BEAVRS. In Physics of Reactors 2016 – PHYSOR 2016 – Unifying Theory and Experiments in the 21st Century, May 1–5, 2016, Sun Valley, ID, USA (pp. 4131–4138). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[12. Bykov, V. (2016). Solution of the BEAVRS benchmark using CASMO-5/SIMULATE-5 Code sequence. In Physics of Reactors 2016 – PHYSOR 2016 – Unifying Theory and Experiments in the 21st Century, May 1–5, 2016, Sun Valley, ID, USA (pp. 0–3). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[13. Taforeau, J., & Salino, V. (2016). Analysis of the MIT BEAVRS Benchmark using the DRAGON-5/PARCS code sequence. In Physics of Reactors 2016 – PHYSOR 2016 – Unifying Theory and Experiments in the 21st Century, May 1–5, 2016, Sun Valley, ID, USA (pp. 2940–2949). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[14. Li, Z., Wu, H., Cao, L., Tian, C., & Chen, D. (2016). On-line monitoring analysis of BEAVRS benchmark using NECP-ONION. In Physics of Reactors 2016 – PHYSOR 2016 – Unifying Theory and Experiments in the 21st Century, May 1–5, 2016, Sun Valley, ID, USA (pp. 3637–3648). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[15. Harrison, R. D., & Wheeler, A. F. (2016). Validation of WIMS/PANTHER PWR fuel reactivity depletion using the BEAVRS Benchmark flux map data. In Physics of Reactors 2016 – PHYSOR 2016 – Unifying Theory and Experiments in the 21st Century, May 1–5, 2016, Sun Valley, ID, USA (pp. 2833–2846). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[16. Wang, K., Liu, S., Li, Z., Wang, G., Liang, J., Yang, F., Chen, Z., Guo, X., Qiu, Y., Wu, O., Guo, J. J., & Tang, X. (2017). Analysis of BEAVRS two-cycle benchmark using RMC based on full core detailed model. Prog. Nucl. Energy, 98, 1–12. doi: 10.1016/j.pnucene.2017.04.009.10.1016/j.pnucene.2017.04.009]Open DOISearch in Google Scholar
[17. Collins, B., & Godfrey, A. (2015). Analysis of the BEAVRS Benchmark using VERA-Cs. In ANS MC2015 – Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method, April 19–23, 2015, Nashville, TN, USA. LaGrange Park, IL, USA: American Nuclear Society. (CD Edition) (11 pp.). Available from https://www.casl.gov/sites/default/files/docs/CASL-U-2015-0183-000.pdf.]Search in Google Scholar
[18. Park, H. J., Lee, H. C., Cho, J. Y., Shim, H. J., & Kim, C. H. (2015). Real variance estimation of BEAVRS benchmark in McCARD Monte Carlo eigenvalue calculations. In ANS MC2015 – Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method, April 19–23, 2015, Nashville, TN, USA (pp. 110–121). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[19. Ryu, M., Jung, Y. S., Cho, H. H., & Joo, H. G. (2015). Solution of the BEAVRS benchmark using the nTRACER direct whole core calculation code. J. Nucl. Sci. Technol., 52, 961–969. doi: 10.1080/00223131.2015.1038664.10.1080/00223131.2015.1038664]Open DOISearch in Google Scholar
[20. Kelly, D. J., Aviles, B. N., Romano, P. K., Herman, B. R., Horelik, N. E., & Forget, B. (2014). Analysis of Select BEAVRS PWR benchmark Cycle 1 results using MC21 and OPENMC. In PHYSOR 2014 – The Role of Reactor Physics towards a Sustainable Future, 28 September – 3 October 2014, Kyoto, Japan (pp. 1–15).]Search in Google Scholar
[21. Suzuki, M., & Nauchi, Y. (2015). Analysis of BEAVRS benchmark problem by using enhanced Monte Carlo Code MVP with Jendl-4.0. In ANS MC2015 – Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method, April 19–23, 2015, Nashville, TN, USA (pp. 1–11). LaGrange Park, IL, USA: American Nuclear Society. (CD edition).]Search in Google Scholar
[22. Wang, Z., Wu, B., Hao, L., Liu, H., & Song, J. (2018). Validation of SuperMC with BEAVRS benchmark at hot zero power condition. Ann. Nucl. Energy, 111, 709–714. doi: 10.1016/j.anucene.2017.09.045.10.1016/j.anucene.2017.09.045]Open DOISearch in Google Scholar
[23. O’Grady, D., Kozlowski, T., & Hudson, N. (2018). Analysis of the BEAVRS benchmark using the TRITON/PARCS/PATHS two-step sequence. In PHYSOR 2018 – Reactors Physics Paving the Way Towards More Efficient Systems, April 22–26, 2018, Cancun, Mexico (pp. 1–11).]Search in Google Scholar
[24. Leppänen, J., & Mattila, R. (2016). Validation of the Serpent-ARES code sequence using the MIT BEAVRS benchmark HFP – conditions and fuel Cycle 1 simulations. Ann. Nucl. Energy, 96, 324–331. doi: 10.1016/j.anucene.2016.06.014.10.1016/j.anucene.2016.06.014]Open DOISearch in Google Scholar
[25. US Nuclear Regulatory Commission. (2012). SCALE/ TRITON Primer: A Primer for Light Water Reactor Lattice Physics Calculations – with SNAP. (NUREG/ CR-7041, ORNL/TM-2011/21). Available from https://www.nrc.gov/docs/ML1233/ML12338A215.pdf.]Search in Google Scholar
[26. MIT Computational Reactor Physics Group. (2018, April). BEAVRS – Benchmark for evaluation and validation of reactor simulations.. Release rev. 2.0.2. Available from https://crpg.mit.edu/sites/default/files/css_injector_images_image/BEAVRS_2.0.2_spec.pdf.]Search in Google Scholar
[27. Oak Ridge National Laboratory. (2011). SCALE/ TRITON Primer: A primer for Light Water Reactor lattice physics calculations – NO SNAP. (NUREG/ CR-7041, ORNL/TM-2011/21).]Search in Google Scholar
[28. US Nuclear Regulation Commission. (2013). Cross section generation guidelines for TRACE-PARCS. (NUREG/CR-7164, ORNL/TM-2012/518). Available from https://www.nrc.gov/docs/ML1320/ML13204A296.pdf.]Search in Google Scholar
[29. Darnowski, P., Ignaczak, P., Obrębski, P., Stępień, M., & Niewiński, G. (2018). Simulations of the AP1000-based reactor core with SERPENT computer code. Arch. Mech. Eng., LXV, 295–325. doi: 10.24425/124484.10.24425/124484]Open DOISearch in Google Scholar
[30. New York Power Authority. (2000, January 18). New York Power, Indian Point 3 Nuclear Power Plant – Cycle 11 Physics Test Report. Available from https://www.nrc.gov/docs/ML0036/ML003679481.pdf.]Search in Google Scholar
