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Mesocarbon microbead densified matrix graphite A3-3 for fuel elements in molten salt reactors
Wang, Haoran,Xu, Liujun,Zhong, Yajuan,Li, Xiaoyun,Tang, Hui,Zhang, Feng,Yang, Xu,Lin, Jun,Zhu, Zhiyong,You, Yan,Lu, Junqiang,Zhu, Libing Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.5
This study aims to provide microstructural characterization for the matrix graphite which molten salt reactors (MSRs) use, and improve resistance to molten salt infiltration of the matrix graphite for fuel elements. Mesocarbon microbeads (MCMB) densified matrix graphite A3-3 (MDG) was prepared by a quasi-isostatic pressure process. After densification by MCMBs with average particle sizes of 2, 10, and 16 ㎛, the pore diameter of A3-3 decreased from 924 nm to 484 nm, 532 nm, and 778 nm, respectively. Through scanning electron microscopy, the cross-section energy spectrum and time-of-flight secondary ion mass spectrometry, resistance levels of the matrix graphite to molten salt infiltration were analyzed. The results demonstrate that adding a certain proportion of MCMB powders can improve the anti-infiltration ability of A3-3. Meanwhile, the closer the particle size of MCMB is to the pore diameter of A3-3, the smaller the average pore diameter of MDG and the greater the densification. As a matrix graphite of fuel elements in MSR was involved, the thermal and mechanical properties of matrix graphite MDG were also studied. When densified by the MCMB matrix graphite, MDGs can meet the molten salt anti-infiltration requirements for MSR operation.
A new method for exponential synchronization of memristive recurrent neural networks
Zhang, Ruimei,Park, Ju H.,Zeng, Deqiang,Liu, Yajuan,Zhong, Shouming Elsevier science 2018 Information sciences Vol.466 No.-
<P><B>Abstract</B></P> <P>This paper investigates the exponential synchronization problem of memristive recurrent neural networks (MRNNs). A novel approach, switching matrix approach, is considered to study synchronization of MRNNs for the first time. All the matrices in the constructed Lyapunov–Krasovskii functional (LKF) are switching according to different switching rules. Based on the switching matrix approach, a new synchronization criterion is established in the form of linear matrix inequalities (LMIs). Compared with some existing methods, the switching matrix approach is more flexible and can improve the synchronization performance with low control cost. Finally, numerical simulations are provided to show the effectiveness and advantages of the proposed results.</P>
Zhang, Ruimei,Zeng, Deqiang,Park, Ju H.,Liu, Yajuan,Zhong, Shouming IEEE 2018 IEEE transactions on neural networks and learning Vol.29 No.12
<P>This paper is concerned with the problem of synchronization for inertial neural networks (INNs) with heterogeneous time-varying delays (HTVDs) through quantized sampled-data control. The control scheme, which takes the communication limitations of quantization and variable sampling into account, is first employed for tackling the synchronization of INNs. A novel Lyapunov–Krasovskii functional (LKF) is constructed for synchronizing an error system. Compared with existing LKFs by the largest upper bound of all HTVDs, the proposed LKF is superior, since it can make full use of the information on the lower and upper bounds of each HTVD. Based on the LKF and a new integral inequality technique, less conservative synchronization criteria are derived. The desired quantized sampled-data controller is designed by solving a set of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and conservatism reduction of the proposed results.</P>
Zhang, Ruimei,Zeng, Deqiang,Park, Ju H.,Liu, Yajuan,Zhong, Shouming IEEE 2018 IEEE transactions on systems, man, and cybernetics Vol.48 No.12
<P>In this paper, the problem of nonfragile sampled-data synchronization of delayed complex dynamical networks with randomly occurring controller gain fluctuations (ROCGFs) is studied. First, more applicable nonfragile memory sampled-data controllers are designed, which involve the signal transmission delay and ROCGFs. The controller gain fluctuations appear in a random way, which obey certain Bernoulli distributed white noise sequences. Second, a modified piecewise Lyapunov–Krasovskii functional (LKF), which involves cubic sawtooth structure term, is constructed for the first time. Third, based on the LKF, less conservative synchronization criteria are established. In comparison with the existing results, the constraint condition of the positive definition of the LKF is less restrictive, since it does not need to be positive definite for all time, but is only required to be positive definite at sampling times. Finally, the effectiveness and advantages of the obtained results are illustrated by two numerical examples.</P>
Zhao He,Hongchao Zhao,Jinliang Song,Xiaohui Guo,Zhanjun Liu,Yajuan Zhong,T. James Marrow 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.4
Green pitch coke with an average particle size of 2 mm was adopted as densifier and added to the rawmaterials of conventional A3-3 matrix graphite (MG) to prepare modified A3-3 matrix graphite (MMG)by the quasi-isostatic molding method. The structure, mechanical and thermal properties were assessed. Compared with MG, MMG had a more compact structure, and exhibited improved properties of highermechanical strength, higher thermal conductivity and better molten salt barrier performance. Notably,under the same infiltration pressure of 5 atm, the fluoride salt occupation of MMG was only 0.26 wt%,whereas it was 15.82 wt% for MG. The densification effect of green pitch coke endowed MMG withimproved properties for potential use in the spherical fuel elements of molten salt reactor.
A community computational challenge to predict the activity of pairs of compounds
Bansal, Mukesh,Yang, Jichen,Karan, Charles,Menden, Michael P,Costello, James C,Tang, Hao,Xiao, Guanghua,Li, Yajuan,Allen, Jeffrey,Zhong, Rui,Chen, Beibei,Kim, Minsoo,Wang, Tao,Heiser, Laura M,Realubit Nature Publishing Group, a division of Macmillan P 2014 Nature biotechnology Vol.32 No.12
Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.