基于ARM的机载火控雷达元器件自动化检测技术研究

为解决传统技术针对机载火控雷达元器件检测吞吐率低的问题,设计基于ARM的机载火控雷达元器件自动化检测技术。确定机载火控雷达元器件自动化检测特征,基于ARM响应曲线拟合机载火控雷达元器件检测数据,表达其自动化检测特征属性值,以此实现机载火控雷达元器件自动化检测。设计实例分析,结果表明,设计检测技术检测吞吐率均在3reqs/s以上,对比传统手段具有明显的优势,能够解决传统检测技术检测吞吐率低的问题。     

基于“嵩山”超级计算机系统的大规模管网仿真

供水管网仿真广泛应用于城市供水输配调度,是城市供水管网监测与维护的重要技术手段。由于在面向城市级的大规模管网中产生了海量的计算数据,因此在一般计算平台上无法满足管网仿真计算的算力需求。为提升城市级供水管网仿真的计算效率,提出一种有效的并行化方案。基于“嵩山”超级计算机系统采用中央处理器+数据缓存单元（CPU+DCU）架构,利用其在密集数据计算方面的优势,对“嵩山”超级计算机进行供水管网仿真。参照可移植性异构计算接口（HIP）异构编程模型,在“嵩山”超级计算机上实现供水管网仿真的异构计算,并结合管道数据分割方案,使用消息传递接口开启多进程以实现DCU加速数据通信传递。通过重定义数据类型解决计算过程中结构体传输问题,实现单节点内多DCU的大规模密集计算。在不同计算平台和多种计算策略仿真上的对比结果表明,与传统x86平台相比,该优化方案在小规模数据与大规模数据上的加速比分别达到5.269、10.760,与采用计算统一设备架构异构编程模型的传统GPU异构平台相比,计算性能有明显提高。     

Surface activation of colloidal indium phosphide nanocrystals

Against general wisdom in crystallization,the nucleation of InP and Ⅲ-Ⅴ quantum dots (QDs) often dominates their growth.Systematic studies on InP QDs identified the key reason for this:the dense and tight alkanoate-ligand shell around each nanocrystal.Different strategies were explored to enable necessary ligand dynamics—i.e.,ligands rapidly switching between being bonded to and detached from a nanocrystal upon thermal agitation—on nanocrystals to simultaneously retain colloidal stability and allow appreciable growth.Among all the surface-activation reagents tested,2,4-diketones (such as acetylacetone) allowed the full growth of InP QDs with indium alkanoates and trimethylsilylphosphine as precursors.While small fatty acids (such as acetic acid) were partially active,common neutral ligands (such as fatty amines,organophosphines,and phosphine oxides) showed limited activation effects.The existing amine-based synthesis of InP QDs was activated by acetic acid formed in situ.Surface activation with common precursors enabled the growth of InP QDs with a distinguishable absorption peak between ～450 and 650 nm at mild temperatures (140-180 ℃).Furthermore,surface activation was generally applicable for InAs and Ⅲ-Ⅴ based core/shell QDs.     

短切碳纤维增强碳化硅陶瓷基复合材料的高温冲击压缩力学性能

采用先驱体浸渍裂解法(即PIP法)制备出3种不同短切碳纤维(C_(sf))体积分数的圆柱形短切碳纤维增强陶瓷基复合材料(C_(sf)/SiC复合材料)试件,通过高温加热装置和自组装功能的霍普金森压杆装置对试件进行高温和动态荷载耦合作用下的冲击压缩试验,并通过扫描电子显微镜(SEM)观察C_(sf)/SiC复合材料断口形貌,对试件的破坏形态进行分析。试验结果表明,采用PIP法制备的C_(sf)/SiC复合材料试件中C_(sf)分布均匀,在外应力作用下C_(sf)/SiC复合材料试件发生破坏,碳纤维和碳纤维束与SiC基体脱粘被不断拔出。试件的抗压强度随C_(sf)体积含量的增加而呈现先增加后减小的变化趋势,C_(sf)体积含量为21%的试件抗压强度最高,为96.55 MPa。与常温相比,在高温压缩试验中随着复合材料试件平均温度的升高,C_(sf)/SiC复合材料试件破碎后的块度越来越大,整体性越来越好,当温度达到300℃时,C_(sf)体积含量对C_(sf)/SiC复合材料试件抗压强度的影响较小。     

颗粒整形对碳化硅陶瓷密封材料成型及烧结性能的影响

采用球磨对SiC粉体颗粒进行整形,并借助反应烧结制备SiC陶瓷密封材料,考察了颗粒整形对反应烧结SiC陶瓷成型、烧结性能、显微结构和力学性能的影响规律。结果表明,整形后的SiC颗粒的球形度高,粒径分布更为均匀;整形SiC粉体的振实密度和素坯密度明显提高,烧结体的显微结构更加均匀,主晶相为6H-SiC和Si,分布均匀,残炭很少;颗粒整形明显改善SiC陶瓷的成型性能及力学性能,当压力为15MPa时,整形后的SiC素坯密度为2.08g/cm~3,烧结体密度为3.06g/cm~3,抗弯强度和断裂韧性分别达到456MPa和3.87MPa·m1/2。     

Photoluminescent two-dimensional SiC quantum dots for cellular imaging and transport

Two-dimensional (2D) ultrathin SiC has received intense attention due to its broad band gap and resistance to large mechanical deformation and external chemical corrosion. However, the synthesis and application of ultrasmall 2D SiC quantum dots (QDs) has not been explored. Herein, we synthesize a type of monolayered 2D SiC QDs with advanced photoluminescence (PL) properties via a facile hydrothermal route. Their average size and thickness can be easily adjusted by altering the reaction time. The ultrasmall 2D SiC QDs exhibit a long fluorescence lifetime of 2.59 μs due to efficient quantum confinement. The applications of SiC QDs are demonstrated through labeling A549, HeLa, and NHDF cells and delivering agents for intracellular low-abundant microRNA (miRNA) detection. This advance in preparing photoluminescent SiC QDs is of great significance for broadening their potential in biomedical and optical applications.

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基于PCIe接口的千兆AFDX TAP卡设计与实现

近年来,大通信量使得机载网络对带宽的需求逐渐增长,目前的10/100 Mbps传输速率已经不能满足需求,故千兆AFDX技术研究急需开展;基于千兆AFDX网络,对TAP卡设计和实现进行了研究;通过系统设计和详细设计对设计过程中的问题进行分析,提出了一种基于FPGA的TAP卡设计方法;模拟不同的网络情况对设计进行了验证;结果表明该设计可以正确反映网络细节,能够给网络级调试带来了极大的便利。     

An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic of nodes by improving the K-shell method. Then, in the local scope, the calculation method of comprehensive degree is proposed to weigh the influence of nodes. Finally, the node with the highest comprehensive degree in each core layer is selected as the seed. However, the seed selection strategy of KT can easily lose some influential nodes. Thus, by optimizing the seed selection strategy, this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization (KTIM). According to the hierarchical distribution of cores, the algorithm adds nodes near the central core to the candidate seed set. It then searches for seeds in the candidate seed set according to the comprehensive degree. Experiments show that KTIM is close to the best performing improved method for influence maximization of temporal graph (IMIT) algorithm in terms of effectiveness, but runs at least an order of magnitude faster than it. Therefore, considering the effectiveness and efficiency simultaneously in temporal social networks, the KTIM algorithm works better than other baseline algorithms.