Complementary layer thickness effects of Q235 and SUS304 layers of multilayered steels for improving of tensile strength and plasticity simultaneously

Lin, Z. M.*; Liu, B. X.*; Ming, K. S.*; 徐 平光; Yin, F. X.*; Zheng, S. J.*

Scripta Materialia, 263, p.116692_1 - 116692_7, 2025/07

https://doi.org/10.1016/j.scriptamat.2025.116692

Complementary layer thickness effects on strength and plasticity in Q235 and SUS304 steels provide a novel strategy to realize high strength and high plasticity of heterogeneous Q235/SUS304 multilayered steel. In this work, the tensile deformation behaviors and fracture characteristics of vacuum hot-rolled Q235/SUS304 multilayered steel with various layer thicknesses ranging from 223 m to 5 m were deeply investigated. The tensile strength improved with the reduction of layer thickness, and the uniform elongation were first increasing and then decreasing with the decrease of layer thickness, and the peak value appeared at the layer thickness of 20 m. Interestingly, the fracture elongation forms a high plateau value within the 1020 m range. Further analysis reveals that the severe strain localization in the brittle SUS304 thin layers is delayed by the ductile Q235 layers, which is mainly attributed to the different texture evolution and dislocation configuration characteristics during tensile deformation.

確率論的リスク評価手法へのAI技術活用の最前線,3; 機械学習を活用した動的PRAと不確かさ評価手法の高度化

Zheng, X.; 玉置 等史; 柴本 泰照; 丸山 結

日本原子力学会誌ATOMO, 66(11), p.565 - 569, 2024/11

https://doi.org/10.3327/jaesjb.66.11_565

原子力安全の継続的な改善のためにはリスク情報と不確かさ情報を活用した合理的な意思決定が重要であり、近年ではこれを効率的に実施するために人工知能/機械学習(AI/ML)を活用することが期待されている。本報では、原子力分野におけるAI/MLの活用例を調査し、日本原子力研究開発機構が行うAI/MLを活用した動的確率論的リスク評価(PRA)と不確かさ評価・感度解析の研究状況を紹介する。具体的には、決定論的解析コードと機械学習による代替評価モデルを柔軟に共用できる多忠実シミュレーション手法を構築することで、ランダムサンプリングを用いた動的PRAとソースターム不確かさ評価・グローバル感度解析の効率的な実施を可能とした。

Development of an Fe complex exhibiting intermolecular proton shifting coupled spin transition

Ji, T.*; Su, S.*; Wu, S.*; 堀 優太*; 重田 育照*; Huang, Y.*; Zheng, W.*; Xu, W.*; Zhang, X.*; 鬼柳 亮嗣; et al.

Angewandte Chemie; International Edition, 63(25), p.e202404843_1 - e202404843_6, 2024/04

https://doi.org/10.1002/anie.202404843

In this study, we investigated reversible intermolecular proton shifting (IPS) coupled with spin transition (ST) in a novel Fe complex. The host Fe complex and the guest carboxylic acid anion were connected by intermolecular hydrogen bonds (IHBs). We extended the intramolecular proton transfer coupled ST phenomenon to the intermolecular system. The dynamic phenomenon was confirmed by variable-temperature single-crystal X-ray diffraction, neutron crystallography, and infrared spectroscopy.

Composite with a glassy nonporous coordination polymer enhances gas adsorption selectivity

Zheng, X.*; 加藤 優*; 上村 洋平*; 松村 大樹; 八木 一三*; 高橋 仁徳*; 野呂 真一郎*; 中村 貴義*

Inorganic Chemistry, 62(3), p.1257 - 1263, 2023/01

https://doi.org/10.1021/acs.inorgchem.2c04068

A glass-crystal composite (g-NCP/PCP), comprising a glassy nonporous coordination polymer (g-NCP) and a crystalline porous coordination polymer (PCP)/metal-organic framework, was synthesized by using a melt-quenched method. Compared to that of the PCP itself, g-NCP/PCP has an enhanced gas adsorption selectivity. The results should stimulate further studies of the chemistry of g-NCP/PCP glass-crystal composites.

Dynamic probabilistic risk assessment of nuclear power plants using multi-fidelity simulations

Zheng, X.; 玉置 等史; 杉山 智之; 丸山 結

Reliability Engineering & System Safety, 223, p.108503_1 - 108503_12, 2022/07

AA2021-0588.pdf:1.29MB

https://doi.org/10.1016/j.ress.2022.108503

Dynamic probabilistic risk assessment (PRA) more explicitly treats timing issues and stochastic elements of risk models. It extensively resorts to iterative simulations of accident progressions for the quantification of risk triplets including accident scenarios, probabilities and consequences. Dynamic PRA leverages the level of detail for risk modeling while intricately increases computational complexities, which result in heavy computational cost. This paper proposes to apply multi-fidelity simulations for a cost- effective dynamic PRA. It applies and improves the multi-fidelity importance sampling (MFIS) algorithm to generate cost-effective samples of nuclear reactor accident sequences. Sampled accident sequences are paralleled simulated by using mechanistic codes, which is treated as a high-fidelity model. Adaptively trained by using the high-fidelity data, low-fidelity model is used to predicting simulation results. Interested predictions with reactor core damages are sorted out to build the density function of the biased distribution for importance sampling. After when collect enough number of high-fidelity data, risk triplets can be estimated. By solving a demonstration problem and a practical PRA problem by using MELCOR 2.2, the approach has been proven to be effective for risk assessment. Comparing with previous studies, the proposed multi-fidelity approach provides comparative estimation of risk triplets, while significantly reduces computational cost.

General synthesis of single-atom catalysts for hydrogen evolution reactions and room-temperature Na-S batteries

Lai, W.-H.*; Wang, H.*; Zheng, L.*; Jiang, Q.*; Yan, Z.-C.*; Wang, L.*; 吉川 浩史*; 松村 大樹; Sun, Q.*; Wang, Y.-X.*; et al.

Angewandte Chemie; International Edition, 59(49), p.22171 - 22178, 2020/12

https://doi.org/10.1002/anie.202009400

Herein, we report a comprehensive strategy to synthesize a full range of single-atom metals on carbon matrix, including V, Mn, Fe, Co, Ni, Cu, Ge, Mo, Ru, Rh, Pd, Ag, In, Sn, W, Ir, Pt, Pb, and Bi. The extensive applications of various single-atom catalysts (SACs) are manifested via their ability to electro-catalyze typical hydrogen evolution reactions (HER) and conversion reactions in novel room-temperature sodium sulfur batteries (RT-Na-S). The enhanced performances for these electrochemical reactions arisen from the ability of different single active atoms on local structures to tune their electronic configuration. Significantly, the electrocatalytic behaviors of diverse SACs, assisted by density functional theory calculations, are systematically revealed by in situ synchrotron X-ray diffraction and in situ transmission electronic microscopy, providing a strategic library for the general synthesis and extensive applications of SACs in energy conversion and storage.

Simulation-based Level 2 multi-unit PRA using RAVEN and a simplified thermal-hydraulic code

Zheng, X.; Mandelli, D.*; Alfonsi, A.*; Smith, C.*; 杉山 智之

Proceedings of 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL 2020 and PSAM-15) (Internet), p.2176 - 2183, 2020/11

https://www.rpsonline.com.sg/proceedings/esrel2020/html/3762.xml

The paper introduces a simulation-based Level 2 probabilistic risk assessment (PRA) of a multi-unit nuclear power plant. We propose the methodology by quantifying risk for a station-blackout accident scenario, initialized by a loss-of-offsite-power event. Contrary to classical PRA that applies static models such as event-tree/fault-tree, the analysis is seamlessly integrated with mechanistic simulation and PRA models, including: (1) a simplified thermal-hydraulic code for simulating system behaviors; (2) a Markovian model for the failure mechanism of decay-heat-removal systems, to investigate the interaction between mechanistic simulation and reliability analysis; and (3) classical containment event trees for evaluating containment performances and hydrogen-explosion risk under severe accident conditions. All dynamic and static models, including plant dependencies, are unified within the RAVEN computational framework, applying RAVEN components, External Model, Ensemble Model, and PRA Plugins. The study demonstrates an integrated assessment of risks by considering accident progression and inter-unit system interactions, both time dependent. Statistical data analysis is used to quantifying risk metrics, including core damage frequencies, large early release frequencies and plant damage status. The methodology pertains to modern risk-analysis methodologies such as risk-informed safety margin characterization (RISMC) and dynamic PRA.

Case study on sampling techniques using machine learning and simplified physical model for simulation-based dynamic probabilistic risk assessment

久保 光太郎; Zheng, X.; 石川 淳; 杉山 智之; Jang, S.*; 高田 孝*; 山口 彰*

Proceedings of Asian Symposium on Risk Assessment and Management 2020 (ASRAM 2020) (Internet), 11 Pages, 2020/11

動的確率論的リスク評価(PRA)は、従来のPRAよりも現実的で詳細な解析を可能とする。しかし、これらの改善とトレードオフの関係にあるのは、多数の熱水力解析を行うことに伴う膨大な計算コストである。本研究では、機械学習に基づいて、熱水力解析を省略することでこの計算コストを削減することを目指した。機械学習には、サポートベクターマシンを選択し、その構築には高忠実度・高コストの詳細モデルと、低忠実度・低コストの簡易モデルを用いた。その結果、今回仮定した条件においては、精度を大幅に低下させることなく計算コストを約80%削減することができた。

A Comparative study of sampling techniques for dynamic probabilistic risk assessment of nuclear power plants

久保 光太郎; Zheng, X.; 田中 洋一; 玉置 等史; 杉山 智之; Jang, S.*; 高田 孝*; 山口 彰*

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.308 - 315, 2020/10

動的確率論的リスク評価(PRA)PRAは従来のPRA手法の現実性と網羅性を向上させる手法の一つである、しかしながら、それらの向上と引き換えに膨大な計算コストが発生する。本稿では、複数のサンプリング手法を簡易的な事故シーケンスに対する動的PRAに対して適用した。具体的には、モンテカルロ法,ラテン超方格法,格子点サンプリング及び準モンテカルロ法を比較した。その結果、今回の検討の範囲においては、準モンテカルロ法が最も効率的であった。

Evaluation of chemical speciation of iodine and cesium considering fission product chemistry in reactor coolant system

石川 淳; Zheng, X.; 塩津 弘之; 杉山 智之; 丸山 結

Proceedings of Asian Symposium on Risk Assessment and Management 2018 (ASRAM 2018) (USB Flash Drive), 6 Pages, 2018/10

Japan Atomic Energy Agency is pursuing the development and application of the methodologies on fission product (FP) chemistry for source term analysis by using integrated severe accident analysis code THALES2/KICHE. Generally, specific chemical forms of iodine and cesium such as cesium iodide (CsI) and cesium hydroxide (CsOH) were assumed in the source term analysis for light water reactors using an integrated severe accident analysis code. The accident at the Fukushima Dai-ichi Nuclear Power Station leads possible chemical effects of BC control materials and atmosphere on chemical speciation of iodine and cesium such as cesium metaborate (CsBO) and hydrogen iodide (HI). The difference of chemical speciation affects not only the FP behavior in the reactor coolant system (RCS) and transport to containment but also pH value of the suppression pool water in the containment. The pH value is one of the influential factors on the release of gaseous iodine (I and organic iodine) from containment liquid phase. In the present study, the improvement of the THALES2/KICHE code in terms of FP chemistry in RCS was performed and applied to source term analysis for severe accidents at a boil water reactor with Mark-I containment vessel. This paper discusses the chemical speciation of iodine and cesium, and FP behavior and transport to containment.