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arXiv 2019年

作者： Gong, Helin Maday, Yvon Mula, Olga Taddei, Tommaso Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China Paris75005 France Institut Universitaire de France Paris75005 France Université Paris-Dauphine PSL Research University CNRS UMR 7534 CEREMADE Paris75016 France IMB UMR 5251 Univ. Bordeaux Talence33400 France Inria Bordeaux Sud-Ouest Team MEMPHIS Talence33400 France

We present an error analysis and further numerical investigations of the Parameterized-Background Data-Weak (PBDW) formulation to variational Data Assimilation (state estimation), proposed in [Y Maday, AT Patera, JD Penn, M Yano, Int J Numer Meth Eng, 102(5), 933-965]. The PBDW algorithm is a state estimation method involving reduced models. It aims at approximating an unknown function utrueliving in a highdimensional Hilbert space from M measurement observations given in the form ym= m(utrue), m = 1, ⋯, M, where mare linear functionals. The method approximates utruewith u = z + η. The background Z belongs to an N-dimensional linear space ZNbuilt from reduced modelling of a parameterized mathematical model, and the update η belongs to the space UMspanned by the Riesz representers of (1, ⋯, M). When the measurements are noisy - i.e., ym= m(utrue) + ϵmwith ϵmbeing a noise term - the classical PBDW formulation is not robust in the sense that, if N increases, the reconstruction accuracy degrades. In this paper, we propose to address this issue with an extension of the classical formulation, which consists in searching for the background z either on the whole ZNin the noise-free case, or on a well-chosen subset KN⊂ ZNin presence of noise. The restriction to KNmakes the reconstruction be nonlinear and is the key to make the algorithm significantly more robust against noise. We further present an a priori error and stability analysis, and we illustrate the efficiency of the approach on several numerical examples. Copyright © 2019, The Authors. All rights reserved.

关键词： Parameterization

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Enhanced Toughness and Ductility of T91 Steel after Exposure to Liquid Lbe Saturated by Oxygen at 350-500 °C

SSRN

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SSRN 2024年

作者： Zhou, Zhikun Tian, Chenwen Dong, Wenbo Du, Juan Liu, Yunpeng Wahab, Magd Abdel Chen, Ziguang Department of Engineering Mechanics School of Aerospace Engineering Huazhong University of Science and Technology Wuhan430074 China Laboratory Soete Faculty of Engineering and Architecture Ghent University Technologiepark Zwijnaarde 46 ZwijnaardeB-9052 Belgium Institute of Intelligent Manufacturing Jianghan University Wuhan430056 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China College of Engineering Yuan Ze University Taiwan Hubei Key Laboratory of Engineering Structural Analysis and Safety Assessment 1037 Luoyu Road Wuhan430074 China

The mechanical tensile properties of T91 steel after being oxidized in liquid LBE saturated by oxygen at 350-500 °C for up to 1,000 h are studied. Duplex oxide scales are found on T91 steels after the LBE exposure, and the thickness evolution is revealed. Oxidized T91 steels with surface oxide scale yield enhanced toughness and ductility, which is mainly attributed to the inner oxide layer. We show that the enhancing effect relies on the presence of the oxide scale, not its thickness. The possible enhancing effect of the oxide scale on the toughness of T91 steel by impeding the dislocation from emitting out of the steel surfaces is discussed and qualitatively verified by micro-scale elastoplastic simulations based on a newly proposed discrete dislocation dynamics and peridynamics superposition scheme. © 2024, The Authors. All rights reserved.

关键词： Ductility

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Cover Picture: Materials and Corrosion. 11/2024

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Materials and Corrosion 2024年第11期75卷 1399-1399页

作者： Wei Zhang Mingyang Zhou Huifang Yue Danmin Peng Xi Qiu Jijun Yang Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China

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The Power Control Method of Data Center Based on Cloud- Edge Collaboration

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Journal of Physics: Conference Series 2021年第1期1754卷

作者： Junjie Zhao Yucheng Hou Liu Liu Feng Xie Xiang Mao Pan Luo Jinxin Wang Zhiqiang Zhang Jiang Deng Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu 610213 China Key Laboratory of the Ministry of Education on Smart Power Grids (Tianjin University) Tianjin 300072 China

Data centers have the characteristics of huge energy consumption and strong power fluctuations. To solve the problem of unstable supply and demand such as frequent power fluctuations in the micro-grid of the data center using renewable energies, this paper establishes a controllable load model of server clusters based on the task migration mechanism by analyzing the various tasks and characteristics of large cloud data centers, as well as edge computing nodes. Through the collaborative optimization control of edge and cloud computing tasks, and dynamically adjusting and migrating the server cluster load, a new data center tie-line power control method is proposed. The results of calculation examples show that the method can achieve power smoothing of large-scale cloud data center tie lines through cloud-edge collaborative control.

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Structural design and strength analysis of multi-ring packed flywheel with heavy metal alloy segments

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IOP Conference Series: Materials science and Engineering 2019年第1期657卷

作者： L Jiang W Zhang C W Wu L P Zhang Y X Zhang Z Y Liu National Key Laboratory of Science and Technology on Reactor System Design Technology Nuclear Power Institute of China Chengdu 610041 China State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian 116024 China

Flywheel, as a kinetic energy storage and conversion device, has promising applications due to its high efficiency, no pollution and long lifetime. In particular, with a three-layer structure packed with heavy metal alloy middle layer, a flywheel can achieve both a large rotational inertia and a high energy density. To guarantee structural strength safety of this type of multi-ring packed flywheel operating at high temperature, structural and thermal stress analysis for a flywheel with a tungsten alloy layer sandwiched between two stainless steel layers is carried out using finite element method (FEM). Based on plane stress assumption, flywheel stress characteristic along radius under assembly force, centrifugal force and thermal loading is demonstrated. The results show that, the rise of temperature causes inconsistent thermal expansion between neighbouring layers and results in a large thermal stress. Particularly, a high circumferential tensile stress occurs in the middle layer. It is also found that, the segments of the middle tungsten alloy layer can efficiently relieve the inconsistent thermal expansion and lower the thermal stress. Moreover, the number of segments significantly influences the efficiency of thermal stress releasing and the reserved gap between adjacent segments significantly improves the contact pressure between inner hub and tungsten alloy layer. This work may provide reference for structural design of the multi-ring packed flywheels under thermal loading.

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Optimization design of the reactor coolant pump flywheel comprised of multi-ring packing heavy metal alloy

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Journal of Physics: Conference Series 2021年第1期1777卷

作者： L Jiang C W Wu X J Shao Y Zhang M D Yu National Key Laboratory of Science and Technology on Reactor System Design Technology Nuclear Power Institute of China Chengdu 610041 China State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian 116024 China

To improve energy storage performance of the multi-ring RCP flywheel comprised of inner hub, tungsten alloy ring and outer retainer, optimization design process for the radial thicknesses of components and interference fit assembly is demonstrated. Radial thicknesses of these components and magnitude of interference fit are set as design parameters to construct parametric analysis model. design of experiments (DOE) technique is adopted to generate design matrix for sensitive analysis. Subsequently, radial basis function (RBF) approximation is employed to search for the optimal design considering structural integrity requirement. Finally, a proper range of the magnitude of interference fit is obtained which can not only prevent neither slippage nor separation between the inner hub and tungsten alloy ring but also ensure the safety of structural strength. In addition, it is found that to ensure a high moment of inertia and energy density, a reasonable large radial thickness of tungsten alloy ring and a reasonable small radial thickness of outer retainer are required.

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Scaling analysis and SE simulation of the tilted cylinder-interface capillary interaction

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IOP Conference Series: Materials science and Engineering 2018年第1期372卷

作者： S Q Gao X Y Zhang Y H Zhou National Key Laboratory of Science and Technology on Reactor System Design Technology Nuclear Power Institute of China Chengdu 610041 China Department of Mechanics and Engineering Sciences College of Civil Engineering and Mechanics Lanzhou University Lanzhou 730000 China

The capillary interaction induced by a tilted cylinder and interface is the basic configuration of many complex systems, such as micro-pillar arrays clustering, super-hydrophobicity of hairy surface, water-walking insects, and fiber aggregation. We systematically analyzed the scaling laws of tilt angle, contact angle, and cylinder radius on the contact line shape by SE simulation and experiment. The following in-depth analysis of the characteristic parameters (shift, stretch and distortion) of the deformed contact lines reveals the self-similar shape of contact line. Then a general capillary force scaling law is proposed to incredibly grasp all the simulated and experimental data by a quite straightforward ellipse approximation approach.

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Determining impact parameters of heavy-ion collisions at low-intermediate incident energies using deep learning with convolutional neural networks

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Physical Review C 2022年第3期105卷 034611-034611页

作者： X. Zhang (张鑫) X. Liu (刘星泉) Y. Huang (黄宇) W. Lin (林炜平) H. Zheng (郑华) R. Wada A. Bonasera Z. Chen (陈志强) L. Chen (陈蕾) J. Han (韩纪锋) R. Han (韩瑞) M. Huang (黄美容) Q. Hu (胡强) Q. Leng (冷强钟) C. W. Ma (马春旺) G. Qu (曲国峰) P. Ren (任培培) G. Tian (田国玉) Z. Xu (徐子虚) Z. Yang (杨振雷) L. Zhang (张丽娜) Key Laboratory of Radiation Physics and Technology of the Ministry of Education Sichuan University Chengdu 610064 China School of Physics and Information Technology Shaanxi Normal University Xi'an 710119 China Cyclotron Institute Texas A&M University College Station Texas 77843 USA Laboratori Nazionali del Sud INFN via Santa Sofia 62 95123 Catania Italy Institute of Modern Physics Chinese Academy of Sciences Lanzhou 730000 China College of Physics and Electronics information Inner Mongolia University for Nationalities Tongliao 028000 China School of Physics Henan Normal University Xinxiang 453007 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu 610213 China School of Information Sciences and Engineering Lanzhou University Lanzhou 730000 China

A deep learning based method with the convolutional neural network (CNN) algorithm for determining the impact parameters is developed by using constrained molecular-dynamics model simulations, focusing on the heavy-ion collisions at the low-intermediate incident energies from several tens to one hundred MeV/nucleon in which the emissions of heavy fragments with the charge numbers larger than three become crucial. To make the CNN applicable in the task of the impact-parameter determination at the present energy range, specific improvements are made in the input selection, the CNN construction, and the CNN training. It is demonstrated from the comparisons of the deep CNN method and the conventional methods with the impact-parameter-sensitive observables that the deep CNN method shows better performance for determining the impact parameters, especially leading to the capability of providing better recognition of the central collision events. With a proper consideration of the experimental filter effect in both training and testing processes to keep consistency with the actual experiments, the good performance of the deep CNN method holds and performs significantly better in terms of predicting the impact parameters and recognizing the central collision events compared with conventional methods, demonstrating the superiority of the present deep CNN method. The deep CNN method with the consideration of the filter effect is applied in the deduction of nuclear stopping power. Higher accuracy for the stopping power deduction is achieved benefitting from the better impact-parameter determination using the deep CNN method, compared with using conventional methods. This result reveals the importance of selecting a reliable impact-parameter-determination method in the experimental deduction of the nuclear stopping power as well as other observables.

关键词： Low & intermediate energy heavy-ion reactions Convolutional neural networks Machine learning Nuclear data analysis & compilation

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Determining impact parameters of heavy-ion collisions at low-intermediate incident energies using deep learning with convolutional neural network

arXiv

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arXiv 2021年

作者： Zhang, X. Huang, Y. Lin, W. Liu, Xingquan Zheng, H. Wada, R. Bonasera, A. Chen, Z. Chen, L. Han, J. Han, R. Huang, M. Hu, Q. Leng, Q. Ma, C.W. Qu, G. Ren, P. Tian, G. Xu, Z. Yang, Z. Zhang, L. Key Laboratory of Radiation Physics and Technology The Ministry of Education Sichuan University Chengdu610064 China School of Physics and Information Technology Shaanxi Normal University Xi’an710119 China Cyclotron Institute Texas A&M University College StationTX77843 United States Laboratori Nazionali del Sud INFN via Santa Sofia 62 Catania95123 Italy Institute of Modern Physics Chinese Academy of Sciences Lanzhou730000 China College of Physics and Electronics information Inner Mongolia University for Nationalities Tongliao028000 China School of Physics Henan Normal University Xinxiang453007 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China School of Information Sciences and Engineering Lanzhou University Lanzhou730000 China

A deep learning based method with the convolutional neural network (CNN) algorithm for determining the impact parameters is developed using the constrained molecular dynamics model simulations, focusing on the heavy-ion collisions at the low-intermediate incident energies from several ten to one hundred MeV/nucleon in which the emissions of heavy fragments with the charge numbers larger than 3 become crucial. To make the CNN applicable in the task of the impact parameter determination at the present energy range, specific improvements are made in the input selection, the CNN construction and the CNN training. It is demonstrated from the comparisons of the deep CNN method and the conventional methods with the impact parameter-sensitive observables, that the deep CNN method shows better performance for determining the impact parameters, especially leading to the capability of providing better recognition of the central collision events. With a proper consideration of the experimental filter effect in both training and testing processes to keep consistency with the actual experiments, the good performance of the deep CNN method holds, and shows significantly better in terms of predicting the impact parameters and recognizing the central collision events, compared to that of the conventional methods, demonstrating the superiority of the present deep CNN method. The deep CNN method with the consideration of the filter effect is applied in the deduction of nuclear stopping power. Higher accuracy for the stopping power deduction is achieved benefitting from the better impact parameter determination using the deep CNN method, compared to using the the conventional methods. This result reveals the importance to select a reliable impact parameter determination method in the experimental deduction of the nuclear stopping power as well as other observables. © 2021, CC BY.

关键词： Molecular dynamics

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Experimental investigation of abnormal transverse flow enhancement of α particles in heavy-ion collisions

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Physical Review C 2021年第4期104卷 044611-044611页

作者： Y. Huang W. Lin H. Zheng R. Wada A. Bonasera Z. Chen J. Han R. Han M. Huang K. Hagel T. Keutgen X. Liu Y. G. Ma C. W. Ma Z. Majka G. Qu L. Qin P. Ren G. Tian J. Wang Z. Yang J. B. Natowitz Key Laboratory of Radiation Physics and Technology of the Ministry of Education Sichuan University Chengdu 610064 China School of Physics and Information Technology Shaanxi Normal University Xi'an 710119 China Cyclotron Institute Texas A&M University College Station Texas 77843 USA School of Physics Henan Normal University Xinxiang 453007 China Laboratori Nazionali del Sud INFNvia Santa Sofia 62 95123 Catania Italy Institute of Modern Physics Chinese Academy of Sciences Lanzhou 730000 China College of Physics and Electronics Information Inner Mongolia University for Nationalities Tongliao 028000 China FNRS and IPN Université Catholique de Louvain B-1348 Louvain-Neuve Belgium Key Laboratory of Nuclear Physics and Ion-Beam Application (MOE) Institute of Modern Physics Fudan University Shanghai 200433 China Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai 201800 China Jagiellonian University Krakow Poland School of Science Huzhou University Huzhou 313000 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu 610213 China

The mass dependence of the transverse flow for Z=1–5 fragments from the collisions of Ar40+Al27, Ar40+Ti48, and Ar40+Ni58 at 47 MeV/nucleon is investigated experimentally in this article. The transverse flow values are determined using the in-plane components of the fragment transverse momenta, where three conventional methods, i.e., the kinetic flow tensor method, the transverse momentum analysis method, and the azimuthal correlation method, are applied to reconstruct the reaction plane in an event-by-event basis. It is demonstrated from the comparison of the present experimental mass dependent flow measurements and the model simulations using an improved antisymmetrized molecular dynamics model that the experimentally observed abnormal α transverse flow enhancement is closely related to the reaction plane reconstruction procedure in the flow extraction. We further investigate the physical existence of the abnormal α flow behavior using a two-particle azimuthal correlation method, which allows us to provide the relative flow magnitude information with an identification of fragment charge number without the knowledge of the reaction plane differing from the three conventional methods. It is found that the relative flow magnitudes deduced from the two-particle azimuthal correlation functions with an identification of Z, with the correction for the recoil effect imposed by the momentum conservation, show a monotonically increasing trend as a function of fragment charge number, with no exception of the α flow enhancement. These results, in addition to those from the improved antisymmetrized molecular dynamics model simulations, definitely provide experimental evidences for the inexistence of the abnormal α flow behavior in the heavy-ion collisions at the present incident energy region in nature.

关键词： Collective flow Low & intermediate energy heavy-ion reactions Nuclear reaction analysis

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