E.B. Agyekum, M.N.S. Ansah, K.B. Afornu, Nuclear energy for sustainable development: SWOT analysis on Ghana’s nuclear agenda. Energy Rep. 6, 107-115(2020). doi: 10.1016/j.egyr.2019.11.163http://doi.org/10.1016/j.egyr.2019.11.163

X.P. Guo, X.D. Guo. Nuclear power development in China after the restart of new nuclear construction and approval: A system dynamics analysis. Renew. Sust. Energ. Rev. 57, 999-1007(2016). doi: 10.1016/j.rser.2015.12.190http://doi.org/10.1016/j.rser.2015.12.190

S.T. Ling, W.Q. Li, C.X. Li et al. Flow field fusion simulation method based on model features and its application in CRDM. Nucl. Sci. Tech. 33(3), 32 (2022). doi: 10.1007/s41365-022-01022-0http://doi.org/10.1007/s41365-022-01022-0

D. Fan, T. Peng, Y Tang et al. Periodicity and transversal pressure distribution in a Wire‐wrapped 19‐Pin fuel assembly. Int. J. Energy Res. 45(8), 11837-11850(2020). doi: 10.1002/er.5809http://doi.org/10.1002/er.5809

V.I. Skalozubov, I.L. Kozlov, Y.A. Komarov et al., Analysis of nuclear safety in diversification of Westinghouse fuel assemblies at WWER-1000. Ядерна фізика та енергетика. 20(2), 159-163(2019).

X. Wang, D. Wang, Q. Deng et al. Simulation of dynamic characteristics of NHR200-II fuel assembly. Nucl. Eng. Des. 379, 111255 (2020). doi: 10.1016/j.nucengdes.2021.111255http://doi.org/10.1016/j.nucengdes.2021.111255

NB/T 20057.3-2012. Reactor system design for pressurized water reactor nuclear power plants-core part 3: fuel assemblies(2012).

G. Yadigaroglu, M. Andreani, J. Dreier et al. Trends and needs in experimentation and numerical simulation for LWR safety. Nucl. Nucl. Eng. Des. 221, 205-223(2003). doi: 10.1016/S0029-5493(02)00339-4http://doi.org/10.1016/S0029-5493(02)00339-4

D. Mourtzis. Simulation in the design and operation of manufacturing systems: state of the art and new trends. Int. J. Prod. Res. 58(7), 1927-1949 (2020). doi: 10.1080/00207543.2019.1636321http://doi.org/10.1080/00207543.2019.1636321

M. Wang, Y. Wang, W. Tian et al., Recent progress of CFD applications in PWR thermal hydraulics study and future directions. Ann. Nucl. Energy. 150, 107836 (2021). doi: 10.1016/j.anucene.2020.107836http://doi.org/10.1016/j.anucene.2020.107836.

Y. Wang, M. Wang, H. Ju et al. CFD simulation of flow and heat transfer characteristics in a 5× 5 fuel rod bundles with spacer grids of advanced PWR. Nucl. Eng. Technol. 52, 1386-1395(2020). doi: 10.1016/j.net.2019.12.012http://doi.org/10.1016/j.net.2019.12.012

J. Zhang, M. Wang, C. Chen et al. CFD investigation of the cold wall effect on CHF in a 5×5 rod bundle for PWRs. Nucl. Eng. Des. 387, 111589(2022). doi: 10.1016/j.nucengdes.2021.111589http://doi.org/10.1016/j.nucengdes.2021.111589

H. Wang, Z. Pu, F. Zhu et al. Simulation and Analysis of New-Type Fuel Assembly Top Connection Structure. Nucl. Power Eng. 38(06), 163-166 (2017). doi: 10.13832/j.jnpe.2017.06.0163http://doi.org/10.13832/j.jnpe.2017.06.0163

S. Liu. Strength Analysis of Pipe Seat Transport and Hoisting Conditions on PWR Fuel Assembly. Southwest Petroleum University, 2019.

Y. Yoo, K. Kim, K. Eom et al. Finite element analysis of the mechanical behavior of a nuclear fuel assembly spacer grid. Nucl. Eng. Des. 352, 110179 (2019). doi: 10.1016/j.nucengdes.2019.110179http://doi.org/10.1016/j.nucengdes.2019.110179

M.H. Duan, M.F. Zhao. A Numerical Research of the Resistance Characteristics of the Bottom Nozzle in the Annular Fuel Assembly. International Conference on Nuclear Engineering. American Society of Mechanical Engineers. 51494, V06BT08A046(2018). doi: 10.1115/ICONE26-82259http://doi.org/10.1115/ICONE26-82259

C.Y. Wu, M.T. Kao, C.C. Chieng et al., CFD analysis of PWR core top region: Top fuel assembly and top nozzle regions. International Conference on Nuclear Engineering. ICONE18-29463, 557-564(2010). doi: 10.1115/ICONE18-29463http://doi.org/10.1115/ICONE18-29463

M. Su, P. Chen, L. Kuang et al. Mechanical property Study of CF3 fuel assembly Bottom Nozzle. Nucl. Power Eng. 39(S1), 62-65(2018). doi: 10.13832/j.jnpe.2018.S1.0062http://doi.org/10.13832/j.jnpe.2018.S1.0062

Z. Wei, S. Du, X. Wang et al. Numerical Simulation Study on Resistance Characteristics of Top Nozzle in Fuel Assembly Based on CFD. Nucl. Power Eng. 38(S2), 29-33(2017). doi: 10.13832/j.jnpe.2017.S2.0029http://doi.org/10.13832/j.jnpe.2017.S2.0029

Š Dyk, V. Zeman. Impact vibrations of guide thimbles in nuclear fuel assembly. Aech. Appl. Mech. 87(2), 231-244(2017). doi: 10.1007/s00419-016-1189-6http://doi.org/10.1007/s00419-016-1189-6

Y. Xu, M. Conner, K. Yuan et al. Study of impact of the AP1000® reactor vessel upper internals design on fuel performance. Nucl. Eng. Des. 252, 128-134(2012). doi: 10.1016/j.nucengdes.2012.06.036http://doi.org/10.1016/j.nucengdes.2012.06.036

J. Zhao, S. Xu, W. Pan et al. A Detailed Model to Predict Mechanical Characteristics of Fuel Assembly. International Conference on Nuclear Engineering. American Society of Mechanical Engineers 86366: V002T02A043(2022). doi: 10.1115/ICONE29-91931http://doi.org/10.1115/ICONE29-91931

ASME. Section 3 Division 1-Subsection NG, Core support structures, 2003.

D. Meng, Y. Li, C. He et al. Multidisciplinary design for structural integrity using a collaborative optimization method based on adaptive approximation modelling. Mater. Des. 206, 109789(2021). doi: 10.1016/j.matdes.2021.109789http://doi.org/10.1016/j.matdes.2021.109789

S. Ling, W. Li, T. Yu et al. Analysis and optimization research on latch life of control rod drive mechanism based on approximate model. Nucl. Eng. Technol. 53(12), 4166-4178(2021). doi: 10.1016/j.net.2021.06.012http://doi.org/10.1016/j.net.2021.06.012

R. Jin, W. Chen, T.W. Simpson. Comparative studies of metamodelling techniques under multiple modelling criteria. Struct. Multidisc. Optim. 23(1), 1-13(2001). doi: 10.1007/s00158-001-0160-4http://doi.org/10.1007/s00158-001-0160-4

T. Chai, R. R. Draxle. Root mean square error (RMSE) or mean absolute error (MAE)?–Arguments against avoiding RMSE in the literature. Geosci. Model Dev. 7(3), 1247-1250(2014). doi: 10.5194/gmd-7-1247-2014http://doi.org/10.5194/gmd-7-1247-2014

R. Y. Rubinstein, B. Melamed. Modern simulation and modeling. New York: Wiley, 1998.

Q. Pan, D. Dias. An efficient reliability method combining adaptive support vector machine and Monte Carlo simulation. Struct. Safety. 67, 85-95(2017). doi: 10.1016/j.strusafe.2017.04.006http://doi.org/10.1016/j.strusafe.2017.04.006

Z. Wang, M. Broccardo, J. Song. Hamiltonian Monte Carlo methods for subset simulation in reliability analysis. Struct. Safety. 76, 51-67(2019). doi: 10.1016/j.strusafe.2018.05.005http://doi.org/10.1016/j.strusafe.2018.05.005

D.V. Dao, H. Adeli, H.B. Ly et al. A sensitivity and robustness analysis of GPR and ANN for high-performance concrete compressive strength prediction using a Monte Carlo simulation. Sustainability. 12(3), 830 (2020). doi: 10.3390/su12030830http://doi.org/10.3390/su12030830

B.T. Pham, M.D. Nguyen, D.V. Dao et al. Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis. Sci. Total Environ. 679, 172-184(2019). doi: 10.1016/j.scitotenv.2019.05.061http://doi.org/10.1016/j.scitotenv.2019.05.061

S. Mordechai. Applications of Monte Carlo method in science and engineering. InTech, 2011.

S.A. Olatubosun, Z. Zhang. Dependency consideration of passive system reliability by coupled stress-strength interference/functional relations of parameters approach. Reliab. Eng. Syst. Safe. 188, 549-560(2019). doi: 10.1016/j.ress.2019.04.009http://doi.org/10.1016/j.ress.2019.04.009