FRP与混凝土组合结构研究综述

提出一种在塑性铰区域采用高延性纤维增强水泥基复合材料(ECC)替代混凝土来改善FRP筋-钢筋增强混凝土柱抗震性能的新方法。对FRP筋-钢筋增强ECC-混凝土构件进行了低周往复荷载试验,系统地考察了基体材料、筋材种类、轴压比对构件破坏模态、裂缝模式、承载力、残余变形、延性和耗能能力的影响。结果表明,将ECC替代塑性铰区域混凝土能够有效避免FRP筋的受压屈曲,进而显著提升组合柱的抗震性能。与钢筋增强ECC-混凝土组合柱相比,复合筋增强ECC-混凝土组合柱的残余变形明显更小,且屈服后的刚度更高。随着轴压比的增大,构件极限强度升高但变形能力降低。通过有限元参数分析可知,组合柱的承载力和变形能力均随着ECC抗压强度及总配筋率的增大而增大;在总配筋率不变的情况下,FRP筋占比越高,构件的延性越好。     

The Main Progress of Perovskite Solar Cells in 2020–2021

Perovskite solar cells (PSCs) emerging as a promising photovoltaic technology with high efficiency and low manufacturing cost have attracted the attention from ...     

多视点稀疏测量的图像绘制方法

为了减少所需采集的视频数据量, 基于图像绘制(Image-based rendering, IBR) 的前沿方法将稠密视点信息映射成压缩感知框架中的原始信号, 并将稀疏视点图像作为随机测量值, 但低维测量信号由所有稠密视点信息线性组合而成, 而稀疏视点图像仅仅来源于部分视点信息, 导致稀疏视点采集的图像与低维测量信号不一致. 本文提出利用间隔采样矩阵消除测量信号与稀疏视点图像位置之间的差异, 进而通过约束由测量矩阵和基函数构成的传感矩阵尽量满足有限等距性, 使得能够获得原始信号的唯一精确解. 仿真实验结果表明, 相比于前沿方法, 本文提出的方法对于不同复杂程度的场景重建都提高了主客观质量.     

神威太湖之光可靠性及可用性设计与分析

随着系统规模与集成度的快速增加,可靠性与可用性问题成为构建E级计算机系统所面临的重大挑战.针对神威太湖之光超级计算机可靠性与可用性设计与实现开展全面的分析.首先概要描述神威太湖之光超级计算机系统结构.其次,系统提出神威太湖之光超级计算机可靠性增强技术以及故障预测、主动迁移、任务局部降级等主被动容错技术,建立神威太湖之光超级计算机多层次主被动协同的容错系统.再次,根据系统故障统计信息,分析失效分布及主要失效来源,结合指数、对数正态与韦布尔3种典型寿命周期分布,对神威太湖之光系统故障间隔时间分布进行数据拟合分析.最大似然估计与K-S(Kolmogorov Smirnov)检验结果表明,对数正态分布与系统失效经验数据取得了最好的拟合度,建立神威太湖之光系统失效分布模型,并计算得出系统平均无故障时间.通过系统运行统计与实际应用测试,分析了故障预测精确度以及主动迁移、局部降低等容错技术的时间开销与容错效果.最后,在神威太湖之光超级计算机可靠性与可用性分析的基础上,提出E级计算机系统高可靠与高可用技术发展建议.     

粗精结合的室内机器人视觉定位方法

为实现室内机器人自身精准定位,提出一种由粗匹配到精定位相融合的视觉定位方法.利用搭载在机器人上方的1台相机观测室内天花板、水平方向的4台相机观测周边环境,得到当前环境特征形成指纹信息库.定位时,将测试图像的周边环境信息与信息库中对应的信息粗匹配,得到机器人粗略位置;使用改进的GMS算法对测试图像及粗匹配结果中对应的天花...     

基于贝叶斯网络的软件项目风险管理模型

提出了一种基于贝叶斯网络的软件项目风险管理模型。随着软件项目的进行,该风险管理模型能够利用不断更新的项目数据持续地预测潜在风险,确定风险源并采取适当的应对措施降低风险发生概率。经实践检验,在软件开发过程中引入该风险管理模型能够有效地对风险进行管理,提高软件开发的成功率。     

Neural-network-based stochastic linear quadratic optimal tracking control scheme for unknown discrete-time systems using adaptive dynamic programming

In this paper, a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time (DT) systems based on adaptive dynamic programming (ADP) algorithm. First, an augmented system composed of the original system and the command generator is constructed and then an augmented stochastic algebraic equation is derived based on the augmented system. Next, to obtain the optimal control strategy, the stochastic case is converted into the deterministic one by system transformation, and then an ADP algorithm is proposed with convergence analysis. For the purpose of realizing the ADP algorithm, three back propagation neural networks including model network, critic network and action network are devised to guarantee unknown system model, optimal value function and optimal control strategy, respectively. Finally, the obtained optimal control strategy is applied to the original stochastic system, and two simulations are provided to demonstrate the effectiveness of the proposed algorithm.     

Supervised land cover classification based on the locally reduced convex hull approach

A novel supervised learning approach, called the locally reduced convex hull (LRCH), is proposed for land cover classification. The method described is capable of increasing the class separability and the representational capacity of the training set, which leads to its high generalization ability in applications. The effectiveness of the LRCH is demonstrated on the classification problem of a multi-spectral data set. In experiments, the LRCH was compared with six common classifiers. Statistical results in terms of the overall accuracy, the Kappa coefficient and McNemar's test show that LRCH outperforms most of the other approaches, with a speed that is comparable to all of them.     

Technical note - Tracking the Indonesian forest fire using NOAA/AVHRR images

The large scale air pollution episode due to the out-of-control biomass burning for agricultural purposes in Indonesia, which started in June 1997, has become a severe environmental problem for the neighbouring countries. Its impact on the health of the residents and ecology in the affected areas is expected to be substantial, costly and possibly long lasting. In this paper, NOAA/AVHRR images of the fire in September are reported.     

An inter-bank E-payment protocol based on quantum proxy blind signature

Security and anonymity are essential to E-payment systems. However, with the increasing computing power, existing E-payment systems will gradually become insecure. In this paper, we propose an inter-bank E-payment system which is based on quantum proxy blind signature. Adopting the techniques of quantum key distribution, one-time pad and quantum proxy blind signature, our quantum E-payment system could protect user??s anonymity as the traditional E-payment systems do, and also have unconditional security which the classical E-payment systems cannot provide. Furthermore, compared with the existing quantum E-payment systems, the proposed system could support inter-bank transactions.