PuO2含量对MOX燃料组件物理特性的影响

当超临界水冷堆组件采用铀与钚的氧化物混合而成的MOX燃料时,与普通UO_2燃料相比其中子学特性存在差异。为了研究PuO_2含量对组件物理特性的影响,采用蒙特卡罗方法计算得到了不同PuO_2含量时MOX燃料物理特性参数,包括俘获裂变比、总微观裂变截面、燃料每次裂变平均释放的能量、每次裂变释放的中子数及有效裂变中子数。进一步得到了装载不同含量PuO_2时MOX燃料组件特性参数,包括能谱、Keff、相对功率、相对功率峰值和缓发中子份额。研究结果对MOX燃料组件的设计有一定参考价值。     

聚合物浸渍裂解法制备C/C-ZrC复合材料及其性能

本文以低密度C/C复合材料为坯体,有机锆聚合物为前驱体,采用聚合物浸渍裂解法(PIP)制备C/C-ZrC复合材料,并对其微观结构、力学性能、烧蚀性能以及烧蚀机理进行了研究。结果表明ZrC在材料内分布均匀,密度为2.05g·cm~(-3)的C/C-ZrC复合材料其弯曲强度为89.70MPa,呈脆性断裂。经氢-氧焰烧蚀150s后其线烧蚀率为-2.2×10~(-3)mm·s~(-1),质量烧蚀率为-1.0×10-3g·s~(-1),远低于密度为1.86g·cm~(-3)的C/C复合材料(线烧蚀率:4.4×10~(-3) mm·s~(-1),质量烧蚀率:7.5×10~(-4)g·s~(-1));在烧蚀的过程中,ZrC表现出优先氧化,同时生成的ZrO_2阻挡层能有效阻挡热量的传递和氧气的渗透,提高了材料的抗烧蚀性能。     

用MCM验证测长仪示值误差的测量不确定度GUM法评定

本文用蒙特卡洛法对测长仪示值误差的测量不确定度的GUM法评定进行了验证,结果一致,验证通过。     

Non-fragile dynamic output feedback H∞ control for discrete-time systems with FWL consideration

The non-fragile dynamic output feedback H _∞ controller design problem is investigated. The controller to be designed is assumed to be with additive gain variations. A two-step procedure is proposed to develop sufficient conditions for the non-fragile H _∞ controller design by employing the structured vertex separator. A comparison between the proposed and the existing controller design methods is provided, and a numerical example is carried out to support the theoretical findings.     

基于FPGA的智能视频融合技术研究

针对夜间或恶劣环境下交通事故频发的情况,提出一种在夜间或恶劣环境中辅助驾驶员改善能见度的技术,本技术是采用在FPGA内部对CCD捕获的可见光视频流和红外摄像机捕获的红外视频流进行实时融合、处理以获得极低或极强光照条件下图像信息的新方法;整个系统流程都在FPGA内实时完成,经过处理的视频流直接显示在位于司机前方的平视显示器上,以协助驾驶者在能见度低的环境中安全地行驶,在各种实验条件下经初步验证都取得了不错的效果。     

车载惯导航位推算组合导航系统误差补偿研究

当惯组(IMU)安装到车体上时存在安装偏差,推导了安装偏差及刻度系数误差对里程计速度的影响,进而导出了航位推算(DR)的位置误差方程及位置更新算法;建立了SINS/DR组合导航的状态方程和量测方程,以捷联惯导的位置与航位推算的位置之差作为组合导航卡尔曼滤波器的输入,估计出安装偏差和刻度系数误差的值并对航位推算进行补偿;仿真及跑车数据的验证分析结果表明了误差估计方法的有效性和正确性.     

嵌入式Linux中基于Qt／Embedded的键盘接口设计

采用S3C2440处理器和嵌入式Linux操作系统,选择目前比较常用的Qt／Embedded作为图形界面的开发语言,设计了嵌入式系统中的键盘接口。在介绍硬件平台的基础上,给出了嵌入式Linux下键盘设备驱动程序的工作过程及实现方法,简单介绍了Qt／Embedded的架构和字符输入策略,详细设计了Qt键盘驱动插件和应用程序。实验表明,键盘驱动采用Qt的插件系统,具有更好的独立性和移植性。     

基于词性的文本挖掘算法在IDS日志中的应用

提出一种以词性为参考值的文本挖掘算法,能有效挖掘与种子词有关的关联规则。基于Bootstrapping算法思想,既减少了预处理阶段对于词根还原的依赖,能处理日志中出现的中文词汇。增加了对于日志文本上下的理解,提高了关联规则的有效性,并应用与IDS日志挖掘之中,有效改善挖掘效率,为规则库提供关联规则。     

A multi-strategy knowledge interoperability framework for heterogeneous learning objects

This paper presents a knowledge exchange framework that can leverage the interoperability among semantically heterogeneous learning objects. With the release of various e-Learning standards, learning contents and digital courses are easy to achieve cross-platform sharing, exchanging, and even reorganizing. However, knowledge sharing in semantic level is still a challenge due to that the learning materials can be presented in any form, such as audios, videos, web pages, and even flash files. The proposed knowledge exchange framework allows users to share their learning materials (also called “learning objects”) in semantic level automatically. This framework contains two methodologies: the first is a semantic mapping between knowledge bases (i.e. ontologies) which have essentially similar concepts, and the second is an ontology-based classification algorithm for sharable learning objects. The proposed algorithm adopts the IMS DRI standard and classifies the sharable learning objects from heterogeneous repositories into a local knowledge base by their inner meaning instead of keyword matching. Significance of this research lies in the semantic inferring rules for ontology mapping and learning objects classification as well as the full automatic processing and self-optimizing capability. Focused on digital learning materials and contrasted to other traditional technologies, the proposed approach has experimentally demonstrated significantly improvement in performance.     

A TCAM-based solution for integrated traffic anomaly detection and policy filtering

The survivability of the future Internet is largely dependent on whether it will be able to successfully address both security and performance issues facing the Internet. On one hand, the Internet becomes more and more vulnerable due to fast spreading malicious attacks. On the other hand, it is under great stress to meet ever growing/changing application demands while having to sustain multi-gigabit forwarding performance. In this paper, we propose a Ternary Content Addressable Memory (TCAM) coprocessor based solution for high speed, integrated TCP flow anomaly detection and policy filtering. The attacking packets with spoofed source IP addresses are detected through two-dimensional (2D) matching. The key features of the solution are: (1) setting flag bits in TCAM action code to support various packet treatments; (2) managing TCP flow state in pair to do 2D matching. We evaluate the solution’s ability to detect TCP-based flooding attacks based on real-world-trace simulations. The results show that the proposed solution can match up OC-192 line rate. The possible modifications of the solution for the detection of low rate TCP-targeted attacks are also discussed.