An innovative approach to effective breeding blanket design for future fusion reactors

An effective breeding blanket is critical to support tritium self-sufficiency for future fusion reactors.The difficulty is to achieve tritium breeding ratio(TBR)target of 1.05 or more.This paper presents a new design approach to the blanket design process.It indicates that fusion blanket design is affected by universal functions based on iterations.Three aspects are worth more attention from fusion engineers in the future.The first factor is that the iterations on the material fractions affect not only structure scheme but also TBR variation.The second factor is the cooling condition affecting final TBR due to the change of the structure material proportion.The third factor is temperature field related to the tritium release.In particular,it is suggested that the statistical calculation of effective TBR must be under reasonable control of the blanket temperature field.This approach is novel for blanket engineering in development of a fusion reactor.

Preliminary electromagnetic analysis of the COOL blanket for CFETR

The supercritical CO_(2)cOoled Lithium-Lead(COOL)blanket has been designed as one advanced blanket candidate for the Chinese Fusion Engineering Test Reactor(CFETR).This work focuses on the electromagnetic(EM)loads(Maxwell force and Lorentz force)acting on the COOL blanket,which are important mechanical loads in further structural analysis of the COOL blanket.A 3D electromagnetic analysis is performed using the ANSYS finite element method to obtain EM loads on the COOL blanket in this study.At first,the magnetic scalar potential(MSP)method is used to obtain the magnetic field and the Maxwell force on the COOL blanket.Then,the magnetic vector potential(MVP)method is performed during a plasma disruption event to get the eddy current distribution.At last,a multi-step method is adopted for the calculation of the Lorentz force and the torque.The maximum Lorentz forces of inboard and outboard blanket structural components are 5624 kN and 2360 kN respectively.

A Constrained Local Neighborhood Approach for Efficient Markov Blanket Discovery in Undirected Independent Graphs

When learning the structure of a Bayesian network,the search space expands significantly as the network size and the number of nodes increase,leading to a noticeable decrease in algorithm efficiency.Traditional constraint-based methods typically rely on the results of conditional independence tests.However,excessive reliance on these test results can lead to a series of problems,including increased computational complexity and inaccurate results,especially when dealing with large-scale networks where performance bottlenecks are particularly evident.To overcome these challenges,we propose a Markov blanket discovery algorithm based on constrained local neighborhoods for constructing undirected independence graphs.This method uses the Markov blanket discovery algorithm to refine the constraints in the initial search space,sets an appropriate constraint radius,thereby reducing the initial computational cost of the algorithm and effectively narrowing the initial solution range.Specifically,the method first determines the local neighborhood space to limit the search range,thereby reducing the number of possible graph structures that need to be considered.This process not only improves the accuracy of the search space constraints but also significantly reduces the number of conditional independence tests.By performing conditional independence tests within the local neighborhood of each node,the method avoids comprehensive tests across the entire network,greatly reducing computational complexity.At the same time,the setting of the constraint radius further improves computational efficiency while ensuring accuracy.Compared to other algorithms,this method can quickly and efficiently construct undirected independence graphs while maintaining high accuracy.Experimental simulation results show that,this method has significant advantages in obtaining the structure of undirected independence graphs,not only maintaining an accuracy of over 96%but also reducing the number of conditional independence tests by at least 50%.This significant performance improvement is due to the effective constraint on the search space and the fine control of computational costs.

Neutronics analysis of a subcritical blanket system driven by a gas dynamic trap-based fusion neutron source for ^(99)Mo production

Gamma-emitting radionuclide ^(99m)Tc is globally used for the diagnosis of various pathological conditions owing to its ideal single-photon emission computed tomography (SPECT) characteristics.However,the short half-life of ^(99m)Tc (T_(1/2)=6 h)makes it difficult to store or transport.Thus,the production of ^(99m)Tc is tied to its parent radionuclide ^(99)Mo (T_(1/2)=66 h).The major production paths are based on accelerators and research reactors.The reactor process presents the potential for nuclear proliferation owing to its use of highly enriched uranium (HEU).Accelerator-based methods tend to use deuterium–tritium(D–T) neutron sources but are hindered by the high cost of tritium and its challenging operation.In this study,a new ^(99)Mo production design was developed based on a deuterium–deuterium (D–D) gas dynamic trap fusion neutron source (GDT-FNS) and a subcritical blanket system (SBS) assembly with a low-enriched uranium (LEU) solution.GDT-FNS can provide a relatively high-neutron intensity,which is one of the advantages of ^(99)Mo production.We provide a Monte Carlo-based neutronics analysis covering the calculation of the subcritical multiplication factor (k_(s)) of the SBS,optimization design for the reflector,shielding layer,and ^(99)Mo production capacity.Other calculations,including the neutron flux and nuclear heating distributions,are also provided for an overall evaluation of the production system.The results demonstrated that the SBS meets the nuclear critical safety design requirement (k_(s)<0.97) and maintained a high ^(99)Mo production capacity.The proposed system can generate approximately 157 Ci ^(99)Mo for a stable 24 h operation with a neutron intensity of 1×10^(14) n/s,which can meet 50%of China’s demand in 2025.

Joint target assignment and power allocation in the netted C-MIMO radar when tracking multi-targets in the presence of self-defense blanket jamming

The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.

Feasibility to Convert the NuScale SMR from UO2 to a Mixed (U, Th)O2 Core: A Parametric Study of Fuel Element—Seed-Blanket Concept

Delays in the construction of nuclear reactors due to licensing issues have been a problem across the world, affecting projects in Finland, France, and the United States. Small Modular Reactors (SMRs) emerge as a transition between Generations III+ and IV in order to make nuclear energy more competitive with other energy sources, including renewables. In this study, the SMR NuScale, one of the most promising projects today, is investigated for its conversion into a U-233-producing reactor through the Radkowsky seed-blanket fuel element concept, applied in the Shippingport reactor, in a parametric study. Initially, a validation of the reference reactor (NuScale) was carried out with data from technical documents and papers, thus demonstrating the agreement of the computational model carried out with the SERPENT code. Then, a parametric study is carried out to define the area of the seed and blanket region, proportions of enrichment and pitch length. Finally, a comparison is made between the production of U-233, TRU reduction, burn-up extension and neutronic and thermohydraulic safety parameters. This study demonstrates an improvement in the conversion factor and a considerable reduction in the production of TRU, in addition to the production of U-233 with a low proportion of other uranium isotopes that can lead to the beginning of the thorium cycle with already consolidated technologies.

鄱阳湖圩堤管涌险情分析与防治措施

为了进一步防治管涌险情,以鄱阳湖防洪圩堤为研究对象,建立了管涌预测的理论模型,运用GeoStudio2018软件对防洪圩堤进行模拟分析,设置了降雨强度、降雨类型和降雨时刻三个关键因素和四种工况,分别用Seep/W模块和Sigma/W模块对防洪圩堤进行破坏计算。结果表明,只有在固定库水位下不同降雨会出现管涌现象,管涌出现破坏的有固定库水位23 m+降雨时刻20~30 d+降雨强度0.06 m/d,管涌点位于下游坡坡脚0.2 m处;提出了反滤铺盖方案,并建立了相应的数值模拟模型。经验证,该方案符合相关规范要求。

保温毯应用于开腹肝癌根治术的护理探究

目的探究开腹肝癌根治术应用保温毯护理价值。方法选取2021年1月—2022年12月我院临床接诊80例患者参与分析,以计算机表法随机分组,对照组盖被保温,研究组保温毯保温,每组患者40例,分析体温情况、凝血指标、满意度、低体温症发生率、并发症发生率、患者的术后情况。结果研究组围手术期体温比较对照组围手术期体温更高,P<0.05。研究组凝血指标比较对照组凝血指标更低,P<0.05。研究组满意度(97.50%)比较对照组满意度(80.00%)更高,P<0.05。研究组低体温症发生率(5.00%)低于对照组(25.00%);研究组的并发症发生率和对照组比较更低,P<0.05;患者的术后情况分析,研究组的苏醒时间、排气时间均短于对照组,P<0.05。结论以保温毯保温护理对开腹肝癌根治术患者应用价值更高,能减少不良事件发生率,改善术后凝血功能。

挤压铸造工艺参数的案例推理设计方法

挤压铸造工艺参数是挤压铸造的关键,目前主要通过实验和经验来确定,效率低。结合数据驱动制造的趋势,提出基于案例推理的挤压铸造工艺参数设计方法。将收集的工艺数据视为案例,然后构建挤压铸造工艺参数的马尔可夫毯约简非关键影响因素,去除冗余影响因素并建立案例属性的关系,在此基础上,应用信息熵确定彼此的权重,然后基于案例推理原理得到新材料铸件的工艺参数。通过实验和应用,证明了该方法的有效性和准确性,为挤压铸造工艺参数设计提供了新的方法,可大幅度节省设计时间,也加强了对已有数据的利用。

氦冷固态包层氚增殖球床气体和粉末流动特性的数值研究

基于计算流体力学和离散元耦合分析,研究了氦冷固态增殖包层球床中吹扫氦气的速度分布和破碎的正硅酸锂粉末速度随时间的变化及粉末数量随氦气入口流速变化。模拟结果表明,在吹扫氦气流动方向上,用入口流速归一化的氦气速度分布与入口流速无关,在靠近球床边缘速度变化较大,在球床中部速度变化较小;用入口流速归一化的粉末平均速度与入口流速关系不大,会随吹扫时间逐渐趋于稳定;对小粒径粉末,吹扫气体流速越大,越容易被吹出球床,对大粒径粉末,因其本身体积过大,易在球床中形成堵塞。

一种近似Markov Blanket最优特征选择算法

特征选择可以有效改善分类效率和精度,传统方法通常只评价单个特征,较少评价特征子集.在研究特征相关性基础上,进一步划分特征为强相关、弱相关、无关和冗余四种特征,建立起Markov Blanket理论和特征相关性之间的联系,结合Chi-Square检验统计方法,提出了一种基于前向选择的近似Markov Blanket特征选择算法,获得近似最优的特征子集.实验结果证明文中方法选取的特征子集与原始特征子集相比,以远小于原始特征数的特征子集获得了高于或接近于原始特征集的分类结果.同时,在高维特征空间的文本分类领域,与其它的特征选择方法OCFS,DF,CHI,IG等方法的分类结果进行了比较,在20Newsgroup文本数据集上的分类实验结果表明文中提出的方法获得的特征子集在分类时优于其它方法.

基于Markov blanket和互信息的集成特征选择算法

针对大量无关和冗余特征的存在可能降低分类器性能的问题,提出一种基于近似Markov blanket和动态互信息的特征选择算法并将其应用于集成学习,进而得到一种集成特征选择算法。该集成特征选择算法运用Bagging方法结合提出的特征选择方法生成基分类器,并引入基分类器差异度进行选择性集成,最后用加权投票法融合所选基分类器的识别结果。通过仿真实验验证算法的有效性,以支持向量机(support vector machine,SVM)为分类器,在公共数据集UCI上进行试验,并与单SVM及经典的Bagging集成算法和特征Bagging集成算法进行对比。实验结果显示,该方法可获得较高的分类精度。

水稻软盘毯状苗分离机设计与试验

目前,水稻种植环节中育秧环节与移栽环节之间的水稻苗盘分离环节的机械化程度相较于其他环节较为薄弱。为提高水稻全程机械化作业水平,降低生产成本,设计了一种适用于水稻毯状苗与塑料软盘分离的机械装置,主要由输送机构、分离机构、扶苗机构、集苗机构、动力系统和机架组成。对装置的结构及工作原理进行了描述,分析确定各个机构的结构参数。以分离率、茎叶损伤率、基质损伤率为试验指标进行苗盘分离试验,结果表明:水稻软盘毯状苗分离机作业效果较好,分离成功率在95%以上,能够降低生产成本,提高生产效率;茎叶损伤率及基质损伤率均在3%以下,保证后续水稻毯状苗移栽工作的顺利进行,较小的茎叶损伤与基质损伤也保证了后续水稻生长过程中不会受到较大的影响,满足水稻育秧农艺要求和水稻工厂化技术规范要求。

基于双重约束的最优BN结构学习算法

针对现有基于动态规划的贝叶斯网络结构学习算法复杂度高、无法在合理时间内学习大规模网络的问题,提出基于双重约束的最优贝叶斯网络(Bayesian Network,BN)结构学习算法.首先,利用最大信息系数和马尔科夫毯限制条件独立性(Conditional Independence,CI)测试的候选节点集合和约束集,得到邻居节点集合;其次,利用邻居节点集合约束父节点图的搜索过程,得到候选父节点集合,从候选父节点集合中取出每个节点的最优父集构造初始有向图;再次,利用Tarjan算法计算初始有向图中的强连通分量,得到节点块序;最后,利用节点块序约束节点序图的搜索过程,获得最优的BN结构.实验表明,相比于现有的5种基于动态规划的结构学习算法,本文提出的算法在精度稍微降低的前提下,极大幅度提高了算法的学习效率,如Sachs网络,本文提出的算法相对DPCMB(Dynamic Programming Constrained with Markov Blanket)算法降低了40.3%的时耗,算法精度下降了12.1%.

激光惯性约束聚变堆包层能量沉积特性

参考国内外聚变堆技术,建立了一种200 MW激光惯性约束聚变堆包层概念设计,包层采用超临界二氧化碳和锂铅双冷结构。研究构建了瞬态和稳态耦合模型计算包层温度分布及变化。靶丸内爆反应使用MULTI-IFE进行计算,核热耦合部分基于蒙特卡罗程序OpenMC和自编程换热模型对包层模型结构、冷却和产氚进行计算。研究结果表明,核热耦合模型能够完成对包层的初步计算分析,周期性的瞬态载荷会引起第一壁面温度的振荡,但包层内部的温度最终会收敛到稳态计算结果。堆腔尺寸对于降低温度以及震荡效果明显,但仍需氙展平辐射功率峰。包层产氚和能量导出同时受到堆腔尺寸和增殖区的影响,在200 MW工况下,3 m半径和0.25 m增殖区尺寸计算结果最能满足需求。

一种基于农业废弃物的生态毯制备以及对土壤含水率的影响

【目的】对椰糠基质、稻草秸秆、麦草、芦苇秸秆和玉米秸秆等农业废弃物粉碎处理,制作成一种新型的生态毯,为生态环境的治理提供新的方法与思路。【方法】经前期试验筛选出材料,设计制作了12种生态毯配置,T1(麦草+椰糠)、T2(玉米秸秆+椰糠)、T3((稻草、玉米秸秆、麦草)+椰糠+玉米秸秆)、T4(玉米秸秆+(椰糠、麦草)+(稻草、玉米秸秆、芦苇))、T5(玉米秸秆+椰糠+芦苇)、T6(椰糠+麦草+芦苇)、T7((玉米秸秆、椰糠)+玉米秸秆+(玉米秸秆、椰糠))、T8(稻草+椰糠+麦草)、T9(玉米秸秆+麦草+芦苇)、T10(玉米秸秆+椰糠+麦草)、T11(玉米秸秆+(玉米秸秆、椰糠、麦草)+玉米秸秆)、T12(玉米秸秆),分析铺设生态毯对表层土壤含水率的影响。【结果】生态毯对土壤含水率有非常好的保持作用和抑制土壤水蒸发的作用。在与人工林下的枯落物比较中生态毯的最大平均持水率达到人工林最大平均持水率的2.07倍。【结论】总结了生态毯的现实应用场景与方法,在荒漠化和沙漠的治理中,选择配置T4、T5、T12配合草方格使用防止风力搬移的同时并在表面覆土。在一般地区没有特殊生态治理要求时可采用配置T12、T4来保持土壤含水率。山林裸地的恢复建议选择配置T1、T4、T8。在平均降水量大且易发洪水的地区建议选择配置T1、T4、T8。

基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法

利用遥感技术快速准确地提取耕地信息是耕地保护的关键环节。以山东省商河县为例,提出了一种基于多季相分形特征的Landsat 8 OLI影像耕地信息提取方法。首先采用毯子覆盖法计算多季相遥感影像每个像元的上分形信号和下分形信号,对比分析耕地和其他土地利用类型的分形特征,选取上分形信号的第3尺度作为特征尺度,提取商河县耕地空间分布特征;其次采用同时期的土地利用矢量数据、Esri land cover数据和统计数据进行耕地信息提取精度评价;最后分别设置多季相分形提取与单季相分形提取、现有土地利用数据产品的对比实验,并基于点位匹配度和面积匹配度进行评价。结果表明:多季相数据更能反映农作物生长的复杂性,有助于提高耕地信息的提取精度;不同土地利用类型在不同分形尺度的信号值各不相同,分形特征可以在不同尺度上清晰地刻画出不同土地利用类型的分异性;基于矢量数据和Esri land cover数据评价的多季相分形特征耕地提取点位匹配度为87.13%和89.83%,面积匹配度为99.73%和97.91%,均比单季相分形提取结果精度高;综合考虑点位匹配度、面积匹配度和空间分布特征,研发方法能有效区分耕地和其他土地利用类型,提取结果更优,且与统计数据有更高的一致性。该方法可准确提取耕地信息,为耕地的动态监测和损害评估提供技术支撑。

基于分形特征和阈值分析的图像边缘检测

针对传统的边缘检测算法对噪声敏感且伪边缘较多,提出一种基于分形特征和阈值分析的图像边缘检测方法。该方法利用改进的毯覆盖算法计算出图像的分形特征,将图像的灰度分布映射到分形维数空间上,再根据提取的分形特征图进行阈值分析,获得高低两个阈值,将像素值分为非边缘、弱边缘和强边缘3类,再对弱边缘像素进一步加以判断。实验结果与其他算法相比较表明,该算法检测出来的图像边缘伪边缘和噪声最少。

基于近似Markov Blanket和动态互信息的特征选择算法

针对大量无关和冗余特征的存在可能降低分类器性能的问题,提出了一种基于近似Markov Blanket和动态互信息的特征选择算法。该算法利用互信息作为特征相关性的度量准则,并在未识别的样本上对互信息进行动态估值,利用近似Markov Blanket原理准确地去除冗余特征,从而获得远小于原始特征规模的特征子集。通过仿真试验证明了该算法的有效性。以支持向量机为分类器,在公共数据集UCI上进行了试验,并与DMIFS和ReliefF算法进行了对比。试验结果证明,该算法选取的特征子集与原始特征子集相比,以远小于原始特征规模的特征子集获得了高于或接近于原始特征集合的分类结果。

高维数据局部贝叶斯网络结构学习

针对高维数据下贝叶斯网络结构学习精度和效率低的问题,提出一种基于归一化互信息和近似马尔可夫毯的特征选择(feature selection based on normalized mutual information and approximate Markov blanket,FSNMB)算法来获取目标节点的马尔可夫毯(Markov blanket,MB),进一步结合MB和Meek规则实现基于特征选择的局部贝叶斯网络结构(construct local Bayesian network based on feature selection,FSCLBN)算法,提高局部贝叶斯网络结构学习的精度和效率。实验证明,在高维数据中,FSCLBN算法与现存的局部贝叶斯网络结构学习算法相比更具优势。