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Wakui, Takashi; Takagishi, Yoichi*; Futakawa, Masatoshi
Materials, 16(17), p.5830_1 - 5830_16, 2023/09
Times Cited Count：0 Percentile：0(Chemistry, Physical)Cavitation damage on the mercury target vessel is induced by proton beam injection in mercury. The prediction method of the cavitation damage using Monte Carlo simulations was proposed taking into account of the uncertainties of the position of cavitation bubbles and impact pressure distributions. The distribution of impact pressure attributed to individual cavitation bubble collapsing was assumed to be the Gaussian distribution, and the probability distribution of the maximum value of impact pressures was assumed to be three kinds of distributions; the delta function, the Gaussian and Weibull distributions. Two parameters were estimated using Bayesian optimization by comparing the distribution of the cavitation damage obtained from experiment with that of accumulated plastic strain obtained from the simulation. It was found that the results obtained using the Weibull distribution reproduced the actual cavitation erosion phenomenon better than the other results.
Wakui, Takashi; Takagishi, Yoichi*; Futakawa, Masatoshi; Tanabe, Makoto*
Jikken Rikigaku, 23(2), p.168 - 174, 2023/06
Cavitation damage on the inner surface of the mercury target for the spallation neutron source occurs by proton bombarding in mercury. The prediction method of the cavitation damage using Monte Carlo simulations was suggested taking variability of the bubble core position and impact pressure distribution into account. The impact pressure distribution was estimated using the inverse analysis with Bayesian optimization was conducted with comparison between cavitation damage distribution obtained from experiment and the cumulative plastic strain distribution obtained from simulation. The average value and spread of maximum impact pressure estimated assuming the Gaussian distribution were 3.1 GPa and 1.2 
m, respectively. Simulation results reproduced experimental results and it can be said that this evaluation method is useful.
Zheng, X.; Ishikawa, Jun; Sugiyama, Tomoyuki; Maruyama, Yu
Nuclear Engineering and Technology, 49(2), p.434 - 441, 2017/03
Times Cited Count：4 Percentile：37.06(Nuclear Science & Technology)Zheng, X.; Ishikawa, Jun; Sugiyama, Tomoyuki; Maruyama, Yu
Proceedings of 13th Probabilistic Safety Assessment and Management Conference (PSAM-13) (USB Flash Drive), 10 Pages, 2016/10
