Open Access
Issue |
EPJ Web Conf.
Volume 302, 2024
Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC 2024)
|
|
---|---|---|
Article Number | 17001 | |
Number of page(s) | 10 | |
Section | Artificial Intelligence & Digital in Nuclear Applications - Quantum Computing | |
DOI | https://doi.org/10.1051/epjconf/202430217001 | |
Published online | 15 October 2024 |
- B. Boyack, R. Duffey, P. Griffith, G. Lellouche, S. Levy, U. Rohatgi, G. Wilson, W. Wulff, N. Zuber, Quantifying Reactor Safety Margins: Application of Code Scaling, Applicability, and Uncertainty Evaluation Methodology to a Large-Break Loss-of- Coolant Accident, NUREG/CR-5249 (1989) [Google Scholar]
- The RELAP5 Code Development Team, RELAP5/MOD3 Code Manual, NUREG/CR- 5535 (1995) [Google Scholar]
- K. Mitarai, M. Negori, M. Kitagawa, K. Fujii, Quantum circuit learning, PHYSICAL REVIEW A 98, 032309 (2018) [CrossRef] [Google Scholar]
- I. Kinoshita, M. Murase, RELAP5 Code Analysis of LSTF Small Break LOCA Tests with Steam Generator Intentional Depressurization and Its Uncertainty Quantification by Monte-Carlo Method and Wilks’ Formula Approach, Proceedings of the ASME 2016 International Mechanical Engineering Congress & Exposition (IMECE2016), IMECE2016-66638, Phoenix, AZ, November 11-17, (2016) [Google Scholar]
- H. Asaka, Y. Anoda, Y. Kukita, I. Ohtsu, Secondary-Side Depressurization during PWR Cold-Leg Small Break LOCAs Based on ROSA-V/LSTF Experiments and Analyses, Journal of Nuclear Science and Technology, 35 (12), pp. 905–915 (1998) [CrossRef] [Google Scholar]
- I. Kinoshita, Application of Surrogate Model for Uncertainty Quantification of RELAP5 Code Analysis of LSTF Small Break LOCA Tests, Proceedings of 27th International Conference on Nuclear Engineering (ICONE27), ICONE27-2428, Ibaraki, Japan, May 19-24 (2019) [Google Scholar]
- S.S. Wilks, Statistical prediction with special reference to the problem of tolerance limit, Annals of Mathematical Statistics, 13, pp. 400–409 (1942) [CrossRef] [Google Scholar]
- A. Guba, M. Makai, P. Lenard, Statistical aspects of best estimate method-I, Reliability Engineering and System Safety, 80, pp. 217–232 (2003) [CrossRef] [Google Scholar]
- Y. Suzuki, et al., Qulacs: a fast and versatile quantum circuit simulator for research purpose, arXiv:2011.13524v4 (2021) [Google Scholar]
- M.J. Griffiths, J.P. Schlegel, T. Hibiki, M. Ishii, I. Kinoshita, Y. Yoshida, Phenomena identification and ranking table for thermal-hydraulic phenomena during a small-break LOCA with loss of high pressure injection, Progress of Nuclear Energy, 73, pp. 51–63 (2014) [CrossRef] [Google Scholar]
- QunaSys Inc., Welcome to Quantum Native Dojo!, https://dojo.qulacs.org/ja/latest/index.html (2024) (in Japanese) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.