PC连续刚构桥最大悬臂施工阶段稳定分析

结合重庆市巫山县某预应力混凝土连续刚构桥,利用大型通用有限元分析软件Ansys10.0建立其有限元模型,采用线弹性稳定分析方法对其最大悬臂施工状态下不同荷载工况的稳定性进行对比分析,得到了桥梁各个典型工况下的一阶失稳特征值和失稳模态。分析结果表明施工期最不利工况下该连续刚构桥的稳定性满足规范要求,其稳定安全储备是足够的。并对最大悬臂状态下挂篮坠落对结构的冲击作用进行了动力响应分析。在以上分析的基础上,对安全施工提出了一些建议。     

一种相干复合高斯海杂波仿真方法

具有拖尾的复合高斯模型非常适于描述高分辨率海杂波,对雷达最优检测算法设计和雷达性能评估具有十分重要的意义。该文讨论了复合高斯模型海杂波的建模与仿真,并详述了产生Gamma随机过程的MNLT方法。产生了复合高斯模型的高海况条件下的海杂波,并与实测数据对比,表明了该方法的有效性和可行性。     

基于RRTConCon算法的船舶装配拆卸高斯采样路径规划

船舶舱室内的零部件在进行装配拆卸时,需要依据正确可行的路径进出装配体,通常采用路径规划的方法确定拆装路径。针对RRTConCon算法是采用随机采样的方法选取位姿点,在解决船舶舱室内狭窄通道的路径规划上效率不高的问题,提出了一种基于高斯采样的RRTConCon算法(RRTGaussion),采用高斯分布函数进行分区采样:在大的开阔区域设置较少的采样点,在复杂区域或狭窄通道设置较多的采样点,然后进行局部规划,找出拆装路径。通过在虚拟环境中对该算法进行仿真验证,结果表明,该算法在解决船舶舱室中狭窄通道的路径规划问题上效率高于RRTConCon算法。     

On-line modeling of non-stationary network traffic with schwarz information criterion

Modeling of network traffic is a fundamental building block of computer science. Measurements of network traffic demonstrate that self-similarity is one of the basic properties of the network traffic possess at large time-scale. This paper investigates the change of non-stationary self-similarity of network traffic over time,and proposes a method of combining the discrete wavelet transform (DWT) and Schwarz information criterion (SIC) to detect change points of self-similarity in network traffic. The traffi...     

针对LDPC信道编码的无线视频传输性能分析

本文对H.264压缩视频使用低密度奇偶校验码(LDPC)信道编码策略,分别在加性高斯白噪声、随机误码以及瑞利平坦衰落3种无线信道传输环境下,从信噪比和误码率等信道特性与重建视频质量之间的关系分析无线视频的传输性能.结果表明:无线信道状态不稳定使视频解码质量产生较大波动,且不同数据段误码对视频解码质量的影响不同.此外LDPC码在3种信道下均具有较强的抗传输差错能力.这些分析结果对无线视频传输技术的研究与设计具有一定的参考价值.     

Managing evacuation networks

This paper proposes a non-anticipative, adaptive, decentralized strategy for managing evacuation networks. The strategy is non-anticipative because it does not rely on demand forecasts, adaptive because it uses real-time traffic information, and decentralized because all the information is available locally. It can be used with a failed communication network.The strategy pertains to networks in which no links backtrack in the direction of increased risk. For these types of networks, no other strategy exists that can evacuate more people in any given time, or finish the evacuation in less time. The strategy is also shown to be socially fair, in the sense that the time needed to evacuate all the people exceeding any risk level is, both, the least possible, and the same as if less-at-risk individuals did not participate in the evacuation. The strategy can be proven optimal even when backflows happen due to driver gaming.     

A simulation evaluation of the maximum approximate composite marginal likelihood (MACML) estimator for mixed multinomial probit models

This paper evaluates the ability of the maximum approximate composite marginal likelihood (MACML) estimation approach to recover parameters from finite samples in mixed cross-sectional and panel multinomial probit models. Comparisons with the maximum simulated likelihood (MSL) estimation approach are also undertaken. The results indicate that the MACML approach recovers parameters much more accurately than the MSL approach in all model structures and covariance specifications. The MACML inference approach also estimates the parameters efficiently, with the asymptotic standard errors being, in general, only a small proportion of the true values. As importantly, the MACML inference approach takes only a very small fraction of the time needed for MSL estimation. In particular, the results suggest that, for the case of five random coefficients, the MACML approach is about 50 times faster than the MSL for the cross-sectional random coefficients case, about 15 times faster than the MSL for the panel inter-individual random coefficients case, and about 350 times or more faster than the MSL for the panel intra- and inter-individual random coefficients case. As the number of alternatives in the unordered-response model increases, one can expect even higher computational efficiency factors for the MACML over the MSL approach. Further, as should be evident in the panel intra- and inter-individual random coefficients case, the MSL is all but practically infeasible when the mixing structure leads to an explosion in the dimensionality of integration in the likelihood function, but these situations are handled with ease in the MACML approach. It is hoped that the MACML procedure will spawn empirical research into rich model specifications within the context of unordered multinomial choice modeling, including autoregressive random coefficients, dynamics in coefficients, space-time effects, and spatial/social interactions.     

环放路网宏观基本图信号周期敏感性分析

为揭示路网宏观基本图(MFD)对信号周期的敏感性,首先,提出一种基于GMM的宏观基本图建模方法,并在此基础上提出路网运行效率和稳定性的表征方法;其次,提出MFD 对信号周期敏感性的仿真实验设计方法;再次,以环放路网为例,进行仿真实验,分析信号周期的变化对MFD的影响,进一步揭示信号周期对路网运行效率和稳定性的影响机理. 结果表明,合理的信号周期对MFD和路网的效率及稳定性影响不大,但周期过大或过小则对MFD 和路网的运行效率及稳定性造成较大影响. 该结论可以为路网交通控制和优化提供依据.     

软土地基堆载极限高度的计算分析

对软土地基堆载极限高度进行了塑性极限分析，得出了计算公式。分析了公式中各项的物理意义并结合工程实例对新公式与原有公式进行了对比。     

A novel arterial travel time distribution estimation model and its application to energy/emissions estimation

Arterial travel time information is crucial to advanced traffic management systems and advanced traveler information systems. An effective way to represent this information is the estimation of travel time distribution. In this paper, we develop a modified Gaussian mixture model in order to estimate link travel time distributions along arterial with signalized intersections. The proposed model is applicable to traffic data from either fixed-location sensors or mobile sensors. The model performance is validated using real-world traffic data (more than 1,400 vehicles) collected by the wireless magnetic sensors and digital image recognition in the field. The proposed model shows high potential (i.e., the correction rate are above 0.9) to satisfactorily estimate travel time statistics and classify vehicle stop versus non-stop movements. In addition, the resultant movement classification application can significantly improve the estimation of traffic-related energy and emissions along arterial.