Pressure-induced Diels-Alder reactions in CH - CF cocrystal towards graphane structure

Wang, Y.*; Dong, X.*; Tang, X.*; Zheng, H.*; Li, K.*; Lin, X.*; Fang, L.*; Sun, G.*; Chen, X.*; Xie, L.*; et al.

Angewandte Chemie; International Edition, 58(5), p.1468 - 1473, 2019/01

https://doi.org/10.1002/anie.201813120

芳香族の圧力誘起重合反応(PIP)は、sp炭素骨格を構築するための新しい方法であり、ベンゼンとその誘導体を圧縮することによってダイヤモンド様構造を有するナノスレッドを合成した。ここで、ベンゼン-ヘキサフルオロベンゼン共結晶(CHCF)を圧縮することにより、PIP生成物中に層状構造を有するH-F置換グラフェンを同定した。その場中性子回折から決定された結晶構造およびガスクロマトグラフィー質量スペクトルによって同定された中間生成物に基づいて、20GPaでは、CHCFがベンゼンおよびヘキサフルオロベンゼンを交互に積み重ねた傾斜カラムを形成し、それらが[4+2]重合体に転化し、次いで、短距離秩序を持つ水素化フッ素化グラフェンに変化する。反応プロセスは[4+2]ディールス-アルダー, レトロディールス-アルダー、および1-1'カップリング反応を含み、前者はPIPの重要な反応である。われわれの研究は、CHCFの素反応を初めて確認した。これは、芳香族化合物のPIPについての新しい見方を提供する。

Severe accident scenario uncertainty analysis using the dynamic event tree method

Zheng, X.; 玉置 等史; 石川 淳; 杉山 智之; 丸山 結

Proceedings of 14th International Conference on Probabilistic Safety Assessment and Management (PSAM-14) (USB Flash Drive), 10 Pages, 2018/09

Several types of uncertainties exist during the simulation of a severe accident. These may result from incomplete knowledge about the plant systems, accident progression and oversimplified numerical models. Among them, parameter uncertainty can be treated via Monte-Carlo-sampling-based methods. To tackle the severe accident scenario uncertainty, we must resort to advanced dynamic probabilistic risk assessment (PRA) methods. In this paper, authors reviewed the previous dynamic PRA methods and tools, and then performed a preliminary scenario uncertainty analysis, by using an integrated SA code (THALES2) and a scenario generator (RAPID, risk assessment with plant interactive dynamics), both being developed at JAEA. THALES2 is a fast-running severe accident code for the simulation of severe accident progression and source term in light water reactors. Typical scenarios of station-blackout (SBO)-initiated accidents in boiling water reactors are generated and simulated. The dynamic event tree (DET) method is applied to consider the stochastic uncertainties during the scenario progression. Major groups of SBO sequences with the similar accident characteristics can be found. To provide a reference value for risk, a conditional core damage frequency is calculated accordingly. This is a preliminary analysis for severe accident scenario uncertainty quantification at JAEA, and further DPRA researches are in progress.

Bayesian optimization analysis of containment-venting operation in a Boiling Water Reactor severe accident

Zheng, X.; 石川 淳; 杉山 智之; 丸山 結

Nuclear Engineering and Technology, 49(2), p.434 - 441, 2017/03

https://doi.org/10.1016/j.net.2016.12.011

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.

Bayesian optimization analysis of containment venting operation in a BWR severe accident

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.

An Integrated approach to source term uncertainty and sensitivity analysis for nuclear reactor severe accidents

Zheng, X.; 伊藤 裕人; 玉置 等史; 丸山 結

Journal of Nuclear Science and Technology, 53(3), p.333 - 344, 2016/03

AA2014-0796.pdf:0.84MB

https://doi.org/10.1080/00223131.2015.1044262

Large-scale computer programs simulate severe accident phenomena and often have a moderate-to-large number of models and input variables. Analytical solutions to uncertainty distributions of interested source terms are impractical, and influential inputs on outputs are hard to discover. Additionally, runs of such computer programs, or integral codes, are time-consuming and hence expensive. This article presents an integrated approach to the uncertainty and sensitivity analysis for nuclear reactor severe accident source terms, with an example which simulates an accident sequence similar to that occurred at Unit 2 of the Fukushima Daiichi Nuclear Power Plant using an integral code, MELCOR. Monte Carlo based uncertainty analysis has been elaborated to investigate released fractions of representative radionuclides, Cs and CsI. In order to estimate sensitivity of inputs, which have a substantial influence on the core melt progression and the transportation process of radionuclides, a variance decomposition method is applied. Stochastic process, specifically a Dirichlet process, is applied to construct a surrogate model in sensitivity analysis as a substitute of the code. The surrogate model is cross-validated by comparing with corresponding results of MELCOR. The analysis with the simpler model avoids laborious computational cost so that importance measures for input factors are obtained successfully.

Source term uncertainty analysis; Probabilistic approaches and applications to a BWR severe accident

Zheng, X.; 伊藤 裕人; 玉置 等史; 丸山 結

Mechanical Engineering Journal (Internet), 2(5), p.15-00032_1 - 15-00032_14, 2015/10

http://doi.org/10.1299/mej.15-00032

A suite of methods has been established to quantitatively estimate uncertainties in source term analysis during a nuclear reactor severe accident. The accident sequence occurred at Unit 2 of the Fukushima Daiichi Nuclear Power Plant is taken as an example. The approach mainly consists of four steps: screening analysis, random sampling, numerical computation and verification of uncertainty distributions. First, by using an individually randomized one-factor-at-a-time screening method, a group of variables are preliminarily determined as uncertain inputs. Second, appropriate probability distributions are assigned to input variables. Random samples are generated using Latin Hypercube sampling with the consideration of rank correlation. Third, random samples of variables are inputted into MELCOR 1.8.5. Numerical simulation with multiple code runs is implemented. Finally, uncertainty distributions for representative source terms are obtained and verified. The technique of Bayesian nonparametric density estimation is applied to obtain probability density functions of source terms. The difference of probability density functions is evaluated through the comparison based on the Kullback-Leibler (KL) divergence. With the subjective judgment of small enough KL divergence, after a certain number of numerical computations, the uncertainty distributions of representative source terms are considered as stable enough as reliable results.

Overview of recent methods for the modeling of the uncertainties on the calculations of consequences of a nuclear power plant severe accident

Chevalier-Jabet, K.*; Zheng, X.; Mabrouk, A.*; 丸山 結; Baccou, J.*

Proceedings of 2015 International Congress on Advances in Nuclear Power Plants (ICAPP 2015) (CD-ROM), 13 Pages, 2015/05

Severe accident phenomenology in light water nuclear power plants is complex. For the past decades, extensive experimental programs have been conducted to gain knowledge and computational tools have been built to predict accident progressions and consequences. Nevertheless remained uncertainties directly affect the predictability of severe accidents consequences. Monte-Carlo techniques are widely used in previous uncertainty analysis and the shortcomings are addressed by JAEA and IRSN. The first part of the article deals with uncertainty propagation. Possibilist formalisms are presented with an example. In the second part, JAEA has developed a method for source term assessment using a Dirichlet process. The implementation of the method is described from the Bayesian nonparametric model to the cross-validation process. As results, corresponding computational cost and importance measure of inputs are addressed. The third part describes the current research at IRSN. The combination of Bayesian formalism and graph theory is applied to modeling severe accident uncertainties. The method allows the information to propagate in any direction of the graph, making inference easy to perform. Bayesian networks allow the representation of a complex model in an integrated environment.

Estimation of source term uncertainty in a severe accident with correlated variables

Zheng, X.; 伊藤 裕人; 玉置 等史; 丸山 結

Proceedings of 22nd International Conference on Nuclear Engineering (ICONE-22) (DVD-ROM), 10 Pages, 2014/07

https://doi.org/10.1115/ICONE22-30011

BWRのシビアアクシデント時におけるソースタームの評価を目的として、福島第一原子力発電所2号機の事故を例にとり、シビアアクシデント総合解析コードMELCOR (Ver.1.8.5)を用いた不確かさ解析を実施した。最初のステップとして、炉内溶融進展挙動及び放射性物質移行挙動モデルに係わる主要なパラメータを抽出し、Morris法によりパラメータの絞り込みを行なった。得られた各パラメータの不確かさ分布及びパラメータ間の相関を設定した後、Iman-Conover法による順位相関を考慮したラテン超方格サンプリング(LHS)法を用いて入力データセット作成し、Cs, CsI等の格納容器外放出量について不確かさを評価した。合わせて、相関係数に基づいてソースタームに大きく寄与するパラメータを検討し、炉心コンポーネントや構造物の破損、エアロゾルのプールスクラビングに係わるモデル等がソースタームの不確かさに大きな影響を及ぼすことを明らかにした。

Literature review on experiments and models associated with degradation and oxidation of boron carbide control material during severe accidents

Zheng, X.; 石川 淳; 伊藤 裕人; 玉置 等史; 丸山 結

JAEA-Review 2014-016, 32 Pages, 2014/06

JAEA-Review-2014-016.pdf:1.98MB

炭化ホウ素(BC)は軽水炉における制御材の一つであり、福島第一原子力発電所では全号機において用いられている。BC制御棒/ブレードの損傷は、原子炉容器内における早期の炉心溶融に影響する。また、BCの水蒸気酸化による二酸化炭素(CO)を含む炭素化合物やホウ素化合物の発生は、放射性物質のソースタームに影響を及ぼす可能性がある。本報告書では、原子力機構において整備しているシビアアクシデント総合解析コードTHALES-2の高度化を視野に入れて、BCの損傷及び酸化に係わる既往の実験及びモデル化について文献調査を行なった。制御棒/ブレードの溶融温度はBCとステンレス鋼やジルカロイとの共晶反応により低下する。既存の共晶モデルを検討し、NagaseらのモデルをTHALES-2に組み込むモデルの一つとして選定した。また、BCと水蒸気との酸化反応により大量の熱が放出されるとともに、COやホウ酸,酸化ホウ素が生成され、それらが溶解することにより、ソースタームに影響を与える水相のpH値が変化し得る。BCの水蒸気酸化については、フランス放射線防護原子力安全研究所(IRSN)が開発した酸化反応速度モデルをTHALES-2に導入するモデルの候補として選定した。

High-j proton alignments in Pd

Zhou, H. B.*; Zhou, X. H.*; Zhang, Y. H.*; Zheng, Y.*; Liu, M. L.*; Zhang, N. T.*; Chen, L.*; Wang, S. T.*; Li, G. S.*; Wang, H. X.*; et al.

European Physical Journal A, 47(9), p.107_1 - 107_7, 2011/09

https://doi.org/10.1140/epja/i2011-11107-3

Pd原子核の高スピン状態を、タンデム加速器及び多重線検出装置GEMINI-IIを用いて、インビーム線核分光法で調べた。既知のバンド, 1/2[550]バンドをより高スピン状態まで拡張した。発見されたバンド交差は陽子の整列によるものであると解釈した。Pdの回転バンドの性質を周辺の核、及びcranked shell modelと比較・議論した。