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BackgroundFast neutron pulsed reactors are sensitive to wall scattering neutrons, and their waveforms are changed by reflected neutrons. In addition, their operation may be adversely affected when there are too many reflected neutrons.PurposeThis study aims to solve the problem of fast neutron pulse reactor wall reflection neutron.MethodThe point reactor kinetic method containing the reflection effect, Monte Carlo method, and ANSYS were combined to analyze the Godiva-I transient process in fast neutron pulsed reactor with wall-reflected neutron effect. Firstly, the quench coefficient of the fast neutron pulsed reactor was calculated. Then, the point reactor kinetic method containing the reflection effect was established. Finally, the thermal power obtained from the neutronics calculation was combined with the ANSYS thermal-mechanical module to establish the thermal-mechanical calculation method for fast neutron pulsed reactor, and the effect of wall-reflected neutrons was analyzed and calculated.ResultsThe results show that the reflected neutrons increased the rear edge of the pulse. The reactivity decreases when the flat is washed whilst the core displacement and stress are improved.ConclusionsThe method established in this study can reasonably explain the phenomenon of reduction in attenuation and the increase in power after pulse.

Aimed at the problems in continuous crowd sensing,such as the increased privacy requirements,the unreliable perception data collected and the low enthusiasm of users to participate,this paper proposes an incentive mechanism based on symmetric encryption and double-layer truth discovery(SDIM).First,the symmetric encryption algorithm is used to protect the privacy of the perceived data.When the privacy requirements are high and the number of perceptions is large,the computing overhead and the time of data encryption and reward computing will be greatly reduced.Second,based on a double-layer truth discovery model,an incentive mechanism supporting data reliability evaluation is proposed.The purpose is to simultaneously realize the real time reward of continuous crowd sensing,and improve the fairness of reward when the participants have malicious behavior.Finally,the dual privacy analysis of the proposed method is illustrated.The simulation results show that the proposed method can effectively calculate the true value and the reward according to the data reliability.Notably,it is obviously superior to the comparative model in the time of data encryption and reward computing,and can calculate the reward more fairly when the participants have malicious behavior.

BackgroundRadiation shielding design is an important part of reactor design, and the development of new nuclear power technology for various kinds of reactors has put forward new demands on radiation shielding optimization design methods.PurposeThis study aims to overcome the shortcomings of the traditional multi-objective optimization methods for shielding structures in dealing with the optimization problem of 3D shielding structures, such as slow optimization speed, difficulty in convergence, and poor globalization.MethodsBased on the non-dominated sorting genetic algorithm Ⅲ (NSGA-Ⅲ), the many-objective optimization method for 3D shielding structure design for nuclear reactor was proposed. The Monte Carlo N-Particle Transport Code (MCNP) was employed to analyze comparative performance of the NSGA-III optimization method on the basis of the 3D shielding structure model of nuclear reactors, and shield weight, volume and radiation dose rate in specific regions were taken as the optimization targets.Results & ConclusionsThe numerical simulation results show that the NSGA-III based optimization method for 3D shielding structure design can search for the Pareto-optimal front more efficiently and stably, providing a new idea for the optimization of radiation shielding design.

BackgroundThe mass of a space nuclear power system is a critical parameter due to limitation of loading and high cost of transportation. The radiation shielding system is one of the main contributions of the self-weight of the space nuclear power system.PurposeThis study aims at the shielding optimization problem for the mass minimization of space nuclear power system.MethodsFirstly, the calculation model for the Topaz-II space stack was established and the shielding material was selected. Secondly, a masked multi-objective optimization model was built on the base of Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to obtain an optimization scheme. Then, an intelligent decision support system for the shielding scheme to improve the optimization efficiency was established by coupling the BP neural network algorithm. Finally, the adjustment plan was obtained according to the intelligent decision support system, and verified by using Topaz-II space reactor model.ResultsVerification results show that the intelligent decision support system can be used to set up a basic theoretical model according to the actual needs of the project, and finally provide a space stack shielding scheme that meets the engineering needs.ConclusionsThe validity and feasibility of the method in this paper are proved, providing theoretical and technical support for the optimization of radiation shielding of space reactors.

Time synchronization is the basis and prerequisite for precise information perception in intelligent mines. Many characteristics of underground space in coal mines, such as narrow and long terrain and uneven surface of the roadway, can cause large cumulative effect of synchronization error and poor reliability of signal transmission, which brings great challenges to the research of time synchronization technology among wireless nodes. Two basic time synchronization methods, hierarchical time synchronization and distributed time synchronization method, are introduced in this paper. The special requirements of time synchronization methods for underground coal mine IoTs are analyzed. In addition to the convergence and synchronization precision, the energy efficiency, the topology robustness and the scalability of the synchronization algorithm need to be considered as well. The method should have less communication volume, longer synchronization period and certain topology robustness. Moreover, the method should be able to reduce the cumulative effect of synchronization error caused by large network diameter, and adapt to impact of network scale changes. The current research status of time synchronization of underground coal mine IoTs perception layer is analyzed, and it is concluded that the current research results mainly focus on network structure, synchronization precision and synchronization energy consumption. The research direction of time synchronization technology for underground coal mine IOTs perception layer is prospected, and it is pointed out that the focuses of future research is to design a time synchronization method with certain robustness to topology and time delay in the context of the particularity of underground communication environment and space environment in coal mine: ① It is suggested to improve the robustness of time synchronization method to topology from the perspective of topology dynamic maintenance. ② It is advised to improve the convergence speed of consistent time synchronization method from the perspective of communication topology virtual construction. ③ It is proposed to improve the robustness of time synchronization method to transmission delay from the perspective of timestamp processing and matrix completion.

In order to meet the requirements of high accuracy and low energy consumption of time synchronization among massive nodes of coal mine underground network, a distributed accurate time synchronization algorithm is proposed based on the time-sensitive network (TSN) of coal mine with non-uniform clustering structure of multiple Sink nodes. The underground coal mine TSN is divided into 3 layers, including the TSN convergence layer containing all Sink nodes, the main network consisting of Sink nodes and all cluster head nodes within their respective communication radius, and the secondary network consisting of cluster head nodes and common nodes in the cluster. The TSN convergence layer uses the gPTP algorithm to achieve nanosecond time synchronization among Sink nodes. The main network uses an optimized algorithm based on Kalman filter to predict and compensate for frequency offset, phase offset and noise errors so as to improve the network time synchronization accuracy. The secondary network uses the broadcast-based single and two way hybrid synchronization algorithm to reduce the number of synchronization message packets. The simulation results show that the proposed algorithm can improve the accuracy and stability of network time synchronization effectively and reduce the energy consumption of network time synchronization.

Immune thrombocytopenia (ITP) is an autoimmune-mediated hemorrhagic disease. Emerging evidence indicates that FOXO1 SNPs are related to the immune dysregulation of several autoimmune diseases suggesting that FOXO1 may be involved in inflammation and pathologic activities in patients with ITP. This study aimed to evaluate whether FOXO1 gene single-nucleotide polymorphisms (SNPs) are associated with susceptibility to ITP and clinical priorities of concern include bleeding severity and sensitivity of glucocorticoid treatment. This study recruited 327 newly diagnosed ITP and 220 healthy controls. Four SNPs (rs17446593, rs17446614, rs2721068, and rs2721068) of the FOXO1 gene were detected using the Sequenom MassArray system. Bleeding severity were classified into the mild and severe groups based on the bleeding scores. ITP patients were classified as sensitive and insensitive to glucocorticoid treatment according to the practice guideline for ITP (2019 version). The frequencies of the four SNPs did not show any significant differences between the ITP and healthy control groups. Patients with AA genotype at rs17446593 (p = 0.009) and GG genotype at rs17446614 (p = 0.009) suffered more severe bleeding than patients without them. Carriers of haplotype Grs17446593Ars17446614Crs2721068Trs2755213 were protective to severe bleeding (p = 0.002). The AA genotype at rs17446593 was significantly higher in ITP patients sensitive to glucocorticoid treatment than in those insensitive to glucocorticoid treatment (p = 0.03). Haplotype Grs17446593Grs17446614Trs2721068Trs2755213 increases the risk of glucocorticoid resistance (p = 0.007). Although FOXO1 gene polymorphisms were not associated with susceptibility to ITP, the AA genotype at rs17446593 and GG genotype at rs17446614 were associated with bleeding severity. Haplotype GACT have a protective effect against severe bleeding. Patients with AA genotype at rs17446593 may tend to have good responds to glucocorticoid treatment. However, the FOXO1 gene haplotype GGTT increases the risk of glucocorticoid-resistant. Trial registration: ChiCTR1900022419. [ABSTRACT FROM AUTHOR]