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Kubo, Kotaro; Zheng, X.; Tanaka, Yoichi; Tamaki, Hitoshi; Sugiyama, Tomoyuki; Jang, S.*; Takata, Takashi*; Yamaguchi, Akira*
Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.308 - 315, 2020/10
Dynamic probabilistic risk assessment (PRA) is a method for improving the realism and completeness of conventional PRA. However, enormous calculation costs are incurred by these improvements. One solution is to select an appropriate sampling method. In this paper, we applied the Monte Carlo, Latin hypercube, grid-point, and quasi-Monte Carlo sampling methods to the dynamic PRA of a simplified accident sequence and compared the results for each method. Quasi-Monte Carlo sampling was found to be the most effective method in this case.
Takigami, Machiko; Arai, Hidehiko*; Hirota, Koichi; Taguchi, Mitsumasa; Hakoda, Teruyuki; Kojima, Takuji
Kankyo Kagaku, 14(1), p.13 - 23, 2004/03
The Japan Atomic Energy Research Institute undertook a pilot scale electron beam decompostion of dioxins in the flue gases from the municipal solid waste incinerator at the Takahama Clean Center. The conventional method, following the Japan Industrial Standards (JIS) method, takes 2 weeks at least to extract and purify dioxins from the flue gases for analysis by GC/MS. However, using a carbon adsorbent, the time required for the extraction of dioxins was shortened from 16 to 2.5 hours. Further improvements in the clean up process enabled the overall time to be reduced to less than a half of that rquired by the JIS method. Using this simplified method allows analysts, who are not practiced in the pretreatment of flue gases, to prepare samples for dioxin analysis by GC/MS. The sampling and pretreatment of the flue gases can, with this process, be completed within 4 days with accuracy comparable to JIS method.
