一种三维时域格林函数计算方法

如何高效地计算出三维时域格林函数是线性时域方法能否有效地求解船舶水动力问题的关键.本文在前人工作的基础上,采用了一种半解析的数值求积方法,对三维时域格林函数及其导数作了计算,这种方法十分有效,计算结果令人满意.     

基于鲁棒性的空调自控系统设计

分析了空调自控系统的主要特性,并介绍了一种基于组合自校正控制策略的自适应控制算法,同时采取一些解决工程实际问题的辅助措施,以增强系统的抗干扰能力和对未建模动态、时变参数的鲁棒性.     

堤防水泥固化培土强度的试验研究

水泥固化土是近年来用于堤防防渗、提高边坡稳定性及提高抗冲刷能力的一种新技术，为了提高水泥土的应用水平，通过室内试验研究了水泥土的无侧限强度与水泥掺人比、水灰比、龄期的关系，认为满足工程应用的最佳水泥掺量比大于8％。     

基于ABAQUS的板桩码头地震动力响应研究*

基于ABAQUS软件的隐式模块和有限元-无限元方法对单锚板桩码头进行了地震动响应研究。研究发现,在相同地震波不同加速度峰值情况下,峰值加速度对板桩码头的板桩弯矩、剪力和拉杆拉力有重要影响,与静力分析时的情况相比较,地震加速度峰值每增大0.1g,板桩最大弯矩相应增大约40%,拉杆拉力增大约10%~50%,但拉杆拉力增幅在后期逐渐趋于稳定;地震作用下,拉杆最大拉力与板桩墙最大剪力(单宽)基本相等;地震加速度峰值对板桩墙底与锚碇之间塑性区开展范围也有一定的影响。结果表明,与静载相比,地震对板桩码头的影响不容忽视。研究结果可为板桩码头考虑地震影响的设计提供参考。     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

Estimation of delay variability at signalized intersections for urban arterial performance evaluation

Urban arterial performance evaluation has been broadly studied, with the major focus on average travel time estimation. However, in view of the stochastic nature of interrupted flow, the ability to capture the characteristics of travel time variability has become a critical step in determining arterial level of service (LOS). This article first presents a stochastic approach that integrates classic cumulative curves and probability theories in order to investigate delay variability at signalized intersections, as a dominant part of the link travel time variability. This serves as a basis for arterial travel time estimation, which can be obtained through a convolution of individual link travel time distributions. The proposed approach is then applied in the estimation of travel time along one arterial in Shanghai, China, with abundant automatic vehicle identification (AVI) data sources. The travel time variability is evaluated thoroughly at 30-min intervals, with promising results achieved in comparison to the field measurements. In addition, the estimated travel time distributions are utilized to illustrate the probability of multiple LOS ranges, namely, reliability LOS. The results provide insights into how we might achieve a more reliable and informative understanding of arterial performance.     

考虑多人相互影响的舰船通道最短路径规划

将时间维引入既定舰船通道网络,把考虑多人相互影响的动态最优路径规划问题转化为时间依赖网络中的最优路径搜索问题。首先,论文的算法为所有人员随机生成走行路径,为了预测网络中的弧(路段)的走行时间,按人员速度从慢到快的顺序依次计算并记录人员到达路径中的各路段首节点的时刻,先记录到的人员将成为后记录到的人员的动态障碍。然后,将遗传算法与网络中弧的走行时间预测方法相结合,借助遗传算法的个体多样性天然地解决了人员走行任意性问题,因而获得了全局动态最优路径算法,并仿真计算了两人以及三人的最短时间路径;经与不考虑人员间相互影响时获得的最优路径相比较,论文的算法获得了人员遇到障碍时(或跟行或绕行)的最优走行路径。最后,借助时间依赖网络中的最优路径充要条件定理,说明了算法的有效性。     

响应谱法与时程法在管道水锤分析中的对比研究

水锤是输流管道中经常发生的现象,由于阀门操作不当或设备突然停车引起的水锤极易引起管道的振动,造成设备及支架的破坏,严重影响管道系统的正常运行。文章运用CAESAERⅡ软件,对管道中的水锤现象分别采用响应谱法和时程分析法进行分析。结果表明:响应谱法有利于对振动响应过大模态的精确控制,时程法能精确求解时间历程内各时刻系统的整体响应。为全面分析水锤对管道应力的影响提供了一个研究思路。     

Assessment of factors associated with travel time reliability and prediction: an empirical analysis using probabilistic reasoning approach

Significant efforts have been made in modeling a travel time distribution and establishing measures of travel time reliability (TTR). However, the literature on evaluating the factors affecting TTR is not well established. Accordingly, this paper presents an empirical analysis to determine potential factors that are associated with TTR. This study mainly applies the Bayesian Networks model to assess the probabilistic association between road geometry, traffic data, and TTR. The results from this model reveal that land use characteristics, intersection factors, and posted speed limits are directly associated with TTR. Evaluating the strength of the association between TTR and the directly related variables, the log odds ratio analysis indicates that the land use factor has the highest impact (0.83) followed by the intersection factor (0.57). The findings from this study can provide valuable resources to planners and traffic operators in their decision-making to improve TTR with quantitative evidence.     

基于同方差的递增时间序列自回归预测的改善方法

提出了"利用反双曲正弦函数变换提高数据列光滑程度"的新结论,获得了递增时间序列改善的自回归预测新方法。