Semantic Scholar Open Access 2024 10 sitasi

The Reactor Monte Carlo code RMC: The state-of-the-art technologies, advancements, applications, and next

Kan Wang Zhaoyuan Liu Nan An Hao Luo Conglong Jia +16 lainnya

Abstrak

Based on academic research and industrial applications over more than 20 years, the Reactor Monte Carlo code (RMC) developed by the REAL (Reactor Engineering Analysis Laboratory) team at Tsinghua University since 2000 has become a powerful, innovative, and versatile simulation platform for nuclear reactor analysis, shielding simulations, criticality safety calculations, fusion neutronics analysis and beyond. Utilizing collaborative and agile development technology, advanced methods and the most cutting-edge algorithms can be tested and implemented in RMC quickly and efficiently. RMC has been deployed on many world-class supercomputers in China and played an irreplaceable role in the design and analysis of commercial nuclear power plants and newly designed types of advanced nuclear reactors. This paper reviews the state-of-the-art technologies developed in RMC in recent years, such as stochastic and continuous-varying media modeling, advanced transient simulation capability, more accurate energy deposition model, etc. Parallel acceleration on heterogeneous architecture supercomputers and machine learning algorithms would be incorporated in ongoing research and future development plans.

Penulis (21)

K

Kan Wang

Z

Zhaoyuan Liu

N

Nan An

H

Hao Luo

C

Conglong Jia

P

Pengfei Shen

S

Shihang Jiang

Y

Yingzhe Hu

Y

Yuanhao Gou

W

Wu Wang

Z

Zhiyuan Feng

G

Guodong Liu

X

Xingyu Zhao

K

Kok Yue Chan

Z

Zili Su

Z

Z. Tan

G

Guanyang Liu

Z

Ze-Guang Li

G

Ganglin Yu

J

Jiyang Yu

S

Shanfang Huang

Format Sitasi

Wang, K., Liu, Z., An, N., Luo, H., Jia, C., Shen, P. et al. (2024). The Reactor Monte Carlo code RMC: The state-of-the-art technologies, advancements, applications, and next. https://doi.org/10.1051/epjn/2024021

Akses Cepat

Lihat di Sumber doi.org/10.1051/epjn/2024021
Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Total Sitasi
10×
Sumber Database
Semantic Scholar
DOI
10.1051/epjn/2024021
Akses
Open Access ✓