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涌井 隆; 高岸 洋一*; 二川 正敏
Materials, 16(17), p.5830_1 - 5830_16, 2023/09
被引用回数：0 パーセンタイル：0(Chemistry, Physical)水銀ターゲット容器は、陽子ビームの入射に伴い、キャビテーション損傷を受けるため、キャビテーションバブルの位置や衝撃圧力分布の不確実さを考慮して、モンテカルロ・シミュレーションを用いたキャビテーション損傷を予測する手法を提案した。本手法では、個々のキャビテーション気泡の崩壊に起因する衝撃圧力の分布はガウス分布とし、衝撃圧力の最大値の確率密度分布は3種類の分布: デルタ関数、ガウス分布、ワイブル分布と仮定した。衝撃圧力の分布を記述する方程式の2つのパラメータについて、実験から得られたキャビテーション損傷の分布とシミュレーションから得られた累積塑性ひずみの分布を比較し、ベイズ最適化を使用して推定することができた。また、ワイブル分布を用いて得られた結果が、他の結果に比べて、実際のキャビテーションエロージョン現象を再現することが分かった。
涌井 隆; 高岸 洋一*; 二川 正敏; 田邉 誠*
実験力学, 23(2), p.168 - 174, 2023/06
核破砕中性子源の水銀ターゲット容器において、陽子ビームが水銀に入射することにより、容器内面にキャビテーション損傷が生じる。気泡核の位置や衝撃圧力分布のばらつきを考慮して、モンテカルロ・シミュレーションを用いたキャビテーション損傷の予測方法を提案した。実験より得られたキャビテーション損傷の分布とシミュレーションより得られた積算ひずみの分布を比較し、ベイズ最適化を用いた逆解析により、衝撃圧力の分布を評価した。ガウス分布を仮定した最大衝撃圧力の平均値及び広がりはそれぞれ3.1GPa及び1.2
mであった。シミュレーション結果は実験結果を再現しており、本評価手法が有効であると言える。
Zheng, X.; 石川 淳; 杉山 智之; 丸山 結
Nuclear Engineering and Technology, 49(2), p.434 - 441, 2017/03
被引用回数：4 パーセンタイル：36.71(Nuclear Science & Technology)Containment venting is one of essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach, from a simulation-based perspective, to the venting operations by using an integrated severe accident code, THALES2/KICHE. The effectiveness of containment venting strategies needs to be verified via numerical simulations based on various settings of venting conditions. The number of iterations, however, needs to be controlled for cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using Gaussian process regression, a surrogate model of the "black-box" code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. The number of code queries is largely reduced for the optimum finding, compared with pure random searches. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.
Zheng, X.; 石川 淳; 杉山 智之; 丸山 結
Proceedings of 13th Probabilistic Safety Assessment and Management Conference (PSAM-13) (USB Flash Drive), 10 Pages, 2016/10
Containment venting is one of essential measures to protect the integrity of the final barrier of a nuclear reactor, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to the planning of containment-venting operations by using THALES2/KICHE. Factors that control the activation of the venting system, for example, containment pressure, amount of fission products within the containment and pH value in the suppression chamber water pool, will affect radiological consequences. The effectiveness of containment venting strategies needs to be confirmed through numerical simulations. The number of iterations, however, needs to be controlled for cumbersome computational burden of severe accident codes. Bayesian optimization is a computationally efficient global optimization approach to find desired solutions. With the use of Gaussian process regression, a surrogate model of the "black-box" code is constructed. According to the predictions through the surrogate model, the upcoming location of the most probable optimum can be revealed. The number of code queries is largely reduced for the optimum finding, compared with simpler methods such as pure random search. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies under BWR severe accident conditions.
