Development of multi-group Monte-Carlo transport and depletion coupling calculation method and verification with metal-fueled fast reactor

The accurate modeling of depletion,intricately tied to the solution of the neutron transport equation,is crucial for the design,analysis,and licensing of nuclear reactors and their fuel cycles.This paper introduces a novel multi-group Monte-Carlo depletion calculation approach.Multi-group cross-sections(MGXS)are derived from both 3D whole-core model and 2D fuel subassembly model using the continuous-energy Monte-Carlo method.Core calculations employ the multi-group Monte-Carlo method,accommodating both homogeneous and specific local heterogeneous geometries.The proposed method has been validated against the MET-1000 metal-fueled fast reactors,using both the OECD/NEA benchmark and a new refueling benchmark introduced in this paper.Our findings suggest that microscopic MGXS,produced via the Monte-Carlo method,are viable for fast reactor depletion analyses.Furthermore,the locally heterogeneous model with angular-dependent MGXS offers robust predictions for core reactivity,control rod value,sodium void value,Doppler constants,power distribution,and concentration levels.

GLOBAL STABILITY OF EXTENDED MULTI-GROUP SIR EPIDEMIC MODELS WITH PATCHES THROUGH MIGRATION AND CROSS PATCH INFECTION

In this article, we establish the global stability of an endemic equilibrium of multi-group SIR epidemic models, which have not only an exchange of individuals between patches through migration but also cross patch infection between different groups. As a result, we partially generalize the recent result in the article [16].

A modified multi-group model of angular and momentum distribution of cosmic ray muons for thickness measurement and material discrimination of slabs

Muon tomography is a capable imaging technique to measure the geometry of high-Z objects. However,most existed algorithms used in muon tomography have obscured the effects of angular distribution and momentum spectra of cosmic ray muons and reduced the spatial resolution. We present a modified multi-group model that takes into account these effects and calibrates the model by the material of lead. Performance tests establish that the model is capable of measuring the thickness of a Pb slab and identifying the material of an unknown slab on a reasonable exposure timescale, in both cases of complete and incomplete angular data. Results show that the modified multi-group model is helpful for improvements in image resolution in real applications.

Global dynamics of a novel multi-group model for computer worms

In this paper, we study worm dynamics in computer networks composed of many autonomous systems. A novel multigroup SIQR （susceptible-infected-quarantined-removed） model is proposed for computer worms by explicitly considering anti-virus measures and the network infrastructure. Then, the basic reproduction number of worm R0 is derived and the global dynamics of the model are established. It is shown that if R0 is less than or equal to 1, the disease-free equilibrium is globally asymptotically stable and the worm dies out eventually, whereas, if R0 is greater than 1, one unique endemic equilibrium exists and it is globally asymptotically stable, thus the worm persists in the network. Finally, numerical simulations are given to illustrate the theoretical results.

Multi-group ant colony algorithm based on simulated annealing method

To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the trail information on the current best route. The trail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed.

DYNAMIC FOR A STOCHASTIC MULTI-GROUP AIDS MODEL WITH SATURATED INCIDENCE RATE

In this paper,a stochastic multi-group AIDS model with saturated incidence rate is studied.We prove that the system is persistent in the mean under some parametric restrictions.We also obtain the sufficient condition for the existence of the ergodic stationary distribution of the system by constructing a suitable Lyapunov function.Our results indicate that the existence of ergodic stationary distribution does not rely on the interior equilibrium of the corresponding deterministic system,which greatly improves upon previous results.

Estimates of the Fast and Termal Flux in Blanket of Critical Reactors by Using Multi-Group Methods

In this study, based differential equations methods are used to solve equations because these methods are dependent on boundary value data more than other mathematical equations. We have calculated neutron flux, criticality and geometrical eigenvalue by using multi-group method and solving the neutron diffusion equation for finite and infinite cylindrical and spherical reactors in this study. For the calculation of the total neutron flux cross sections, we need the neutron diffusion equation. Thus, we have established the relationship between neuron flow and cross-section of neuron depending on neutron energy. Critical calculations have been made by comparing the results with MNCP (montecarlo n-partical) simulation methods. For necessary computer calculations, the programme, Wolfram-Matematica-7 has been used.

Multi-group pin power reconstruction method based on colorset form functions

A multi-group pin power reconstruction method that fully exploits nodal information obtained from global coarse mesh solution has been developed.It expands the intra-nodal flux distributions into nonseparable semi-analytic basis functions,and a colorset based form function generating method is proposed,which can accurately model the spectral interaction occurring at assembly interface.To demonstrate its accuracy and applicability to realistic problems, the new method is tested against two benchmark problems,including a mixed-oxide fuel problem.The results show that the new method is comparable in accuracy to fine-mesh methods.

基于生态安全格局的云南世居民族所在地生态韧性评价研究

云南世居民族所在地是基于传统生态智慧世代延续,以自然系统与社会系统相互嵌套为特点的自然–文化遗产,而现代性和社会经济的快速发展使得世居民族所在地不断被蚕食和消解.研究基于韧性理念,利用多源数据,从稳定性、适宜性、冗余度、多样性4个层面构建云南世居民族所在地生态安全格局和生态韧性耦合框架,对藏、彝、傣族所在地2000—2020年生态韧性进行评价研究.结果表明,近20 a来,世居民族所在地总体生态韧性水平为中等,呈现逐年降低的趋势.高水平韧性区多分布于林地,存在连续但细碎化的分布特征.低水平生态韧性多分布于道路缓冲区2 km以内,路网的社会扰动内涵很大程度上影响生态韧性强度.20 a来平均生态韧性指数傣族所在地(0.6420)>彝族所在地(0.5602)>藏族所在地(0.5344).影响各世居民族所在地生态韧性的原因存在差异,地质灾害防护格局和水生环境安全格局是影响生态韧性的主要因素.

基于GRA-GCRITIC和改进加权双向投影的区间Fermatean模糊多属性群决策方法

针对司法案件决策环境的复杂性及评价信息的模糊性,提出一种基于GRA-GCRITIC(grey relational analysis-group criteria importance through intercriteria correlation)和改进加权双向投影的区间Fermatean模糊Hamacher-TODIM多属性群决策方法。首先考虑到各位专家对各评价方案下各指标评价信息的差异性,提出一种GRA-GCRITIC方法,该方法将灰色关联融入到CRITIC中,以确定指标综合权重比单一获取的指标权重更加客观可靠;其次,结合信任关系对加权双向投影法进行改进,兼顾主客观关系,利用专家个体与群体评价信息的隶属度及非隶属度矩阵间的相似度得到专家权重;最后,考虑到决策者的损失规避心理,将融合了Hamacher算子的TODIM方法拓展至区间Fermatean模糊环境中,通过具体算例可得到其综合优势度及排序,验证了所提方法的可行性及灵活性。

岗课赛证融通的模块化课程体系研究实践——以物联网应用技术专业群为例

岗课赛证融通是职业教育类型化的一个核心特征,是“三教”改革的一种全新育人模式。文章分析了岗课赛证的融通机制及融通模式下的物联网专业群课程体系新要求,提出了基于“基础共享、中层分立、高层拓展”课程体系设计思想的“1+X+Y”专业群模块化课程体系架构,并以物联网应用技术专业群为例,分析了物联网应用技术专业群与产业链的逻辑关系,构建了岗课赛证融通的“1+X+Y”专业群模块化课程体系,课程体系具有“对接产业要素、满足核心岗位需求、达成应用能力培养”的三型递进关系;并从多师协作的教学团队构建、课程资源开发、网络课程教学平台搭建及教学组织实施四个方面来阐述专业群模块化教学实施途径。

基于联合GLMB滤波器的可分辨群目标跟踪

针对联合广义标签多伯努利(joint generalized labeled multi-Bernoulli, J-GLMB)滤波算法中群目标之间距离较近、容易关联错误的问题,结合超图匹配(hypergraph matching, HGM)提出一种基于HGM-J-GLMB滤波器的可分辨群目标跟踪算法。首先,采用J-GLMB滤波器估计群内各目标的状态、数目及轨迹信息,并利用HGM结果提升量测与预测状态之间的关联性能。其次,通过图理论计算邻接矩阵,获取群结构信息和子群数目。随后,利用群结构信息估计协作噪声,进而校正目标的预测状态。最后,通过平滑算法改善滤波效果,并设置轨迹长度阈值,使其在平滑状态达到消除短轨迹的目的。仿真实验表明,所提算法在线性系统下能有效提升群目标跟踪性能。

基于多种群混沌遗传算法的GEO目标服务任务规划

面向地球同步轨道(geosynchronous Earth orbit,GEO)空间目标碎片清除、燃料加注等不同在轨服务需求,研究了“固定储油站+往返航天器”相结合的航天器任务规划问题。首先,建立了多任务混合的燃料最优双层任务规划模型,外层为目标服务序列规划,内层为轨道机动规划。随后,针对该连续-离散混合变量组合优化问题,提出了一种多种群混沌遗传算法(multi-group chaotic genetic algorithm,MGCGA),采用混合编码表征决策变量,引入立方混沌映射算子提高初始种群质量,多种群及精英保留策略使得算法在求解过程中能更为显著地逼近全局最优解。最后,参考实际GEO目标构建了典型算例,规划结果表明所提算法具有全局收敛性好、收敛速度快的优点。

基于溶液实验的堆芯物理多群常数库临界基准检验方法

堆芯物理多群常数库为反应堆计算程序的中子学计算提供多群截面数据以及燃耗数据,是反应堆物理计算的重要前提。目前国际上对多群数据库的验证通常将待验证的多群数据库耦合组件计算程序通过对临界基准实验进行模拟计算的方式来进行,各组件计算程序由于几何处理方法的局限无法对球形装置进行建模,因此尚未有基于球形临界基准实验对多群常数库进行基准检验的方法。本文提出了一种裸球形实验装置的模型建立方法,大幅增加临界基准检验使用的基准实验选择范围,同时基于国际核临界安全手册(ICSBEP2006)挑选了不同能谱指标下的49个铀、钚溶液实验对中国核数据中心研制的堆芯物理多群常数库进行临界基准检验,并给出了不同能谱指标下基准实验的参考结果范围。本文结果可扩大堆芯物理多群常数库基准检验规模和覆盖范围,有助于高保真堆芯物理计算程序准确性的进一步提升。

多视图专家组区域建议预测的视觉跟踪

为解决大多数最新的目标跟踪器都面临着判别特征表示缺乏多样性、目标定位过于模糊以及正样本的数量要求问题,提出一种基于多视图的顶层特征的区域建议网络的跟踪预测学习算法。融合多种视图的特征表示方式,利用丰富多样的语义信息,有效解决判别特征过于单一的问题。在扩展的边界框上构建多个支持向量机模型并加入区域建议网络模块,精确优化边界框,预测最优的目标位置,缓解目标定位过于模糊和正样本的数量有限的问题。通过大量视频基准序列对方法的综合评价,其结果表明,提出方法融合了轻量化的深度学习模型和多视图专家组的优点,使跟踪性能有了显著提升。

族群经济对多元族群社区治理的影响:理论依据与机制分析

多元族群社区治理是当前最具前沿性、挑战性和国际意义的社区治理研究内容,是社会治理创新的突破口。以往研究主要聚焦社区治理对族群经济的影响,鲜少研究族群经济对社区治理的影响。文章以义乌阿拉伯族群为研究对象,基于群际接触理论,将族群经济作为解析与洞察社区组织结构、社区治理模式、社区文化融合以及社区政策环境的独特变量。研究发现,义乌族群经济的发展为群际接触创造了平等地位、共同目标、群际合作以及权威支持四大条件,激发了多元族群社区管理的创新改革,形成了“多元共治、以外治外、文化互嵌、制度保障”的多元族群社区治理体系。义乌多元族群社区治理为优化我国移民政策、管理外籍商业活动和治理多元族群社区提供了借鉴和参考。

Global Dynamics of a Multi-group SEIR Epidemic Model with Infection Age

Consider the heterogeneity(e.g.,heterogeneous social behaviour,heterogeneity due to different geography,contrasting contact patterns and different numbers of sexual partners etc.)of host population,in this paper,the authors propose an infection age multigroup SEIR epidemic model.The model system also incorporates the feedback variables,where the infectivity of infected individuals may depend on the infection age.In the direction of mathematical analysis of model,the basic reproduction number R_0 has been computed.The global stability of disease-free equilibrium and endemic equilibrium have been established in the term of R_(0).More precisely,for R_(0)≤1,the disease-free equilibrium is globally asymptotically stable and for R_(0)>1,they establish global stability of endemic equilibrium using some graph theoretic techniques to Lyapunov function method.By considering a numerical example,they investigate the effects of infection age and feedback on the prevalence of the disease.Their result shows that feedback parameters have different and even opposite effects on different groups.However,by choosing an appropriate value of feedback parameters,the disease could be eradicated or maintained at endemic level.Besides,the infection age of infected individuals may also change the behaviour of the disease,global stable to damped oscillations or damped oscillations to global stable.

CT Reconstruction with Priori MRI Images Through Multi-Group Datasets Expansion

Computed tomography(CT) reconstruction with a well-registered priori magnetic resonance imaging(MRI) image can improve reconstruction results with low-dose CT, because well-registered CT and MRI images have similar structures. However, in clinical settings, the CT image of patients does not always match the priori MRI image because of breathing and movement of patients during CT scanning. To improve the image quality in this case, multi-group datasets expansion is proposed in this paper. In our method, multi-group CT-MRI datasets are formed by expanding CT-MRI datasets. These expanded datasets can also be used by most existing CT-MRI algorithms and improve the reconstructed image quality when the CT image of a patient is not registered with the priori MRI image. In the experiments, we evaluate the performance of the algorithm by using multi-group CT-MRI datasets in several unregistered situations. Experiments show that when the CT and priori MRI images are not registered, the reconstruction results of using multi-group dataset expansion are better than those obtained without using the expansion.

多阶段群组综合评价变权方法的研究

现有多阶段群组综合评价研究中,普遍缺乏对不同阶段间评价活动关系的思考,一定程度上影响了阶段权重的确定。基于此,本文根据评价阶段之间的评价活动是否存在关联将其归纳为独立型多阶段群组综合评价和非独立型多阶段群组综合评价。同时对独立型多阶段群组综合评价情形下的阶段变权方法进行了研究:论证了阶段变权的理论依据,提出了基于阶段评价信息偏离度的变权思想;设计了基于ANOVA法和SNK检验的评分信息偏差度测算方法;提出了考虑阶段变权的群组综合评价流程。最后,根据实证算例和比较分析验证了方法的有效性和可用性。