轴对称解对隧道衬砌水压力计算的适用性研究

文章根据渗流理论推导了隧道衬砌水压力的轴对称解,并利用数值分析方法研究了轴对称解对不同形状隧道断面与浅埋隧道的适用性.研究结果表明:轴对称解适用于非圆形隧道断面衬砌水压力的估算;隧道断面形状对衬砌水压力折减系数的影响较小,可以忽略不计,其影响大小主要由衬砌与围岩的渗透系数比值决定.对于浅埋低水头隧道,用轴对称解计算的毛洞流量Qm与数值解比较,其误差较大,最大误差为36.5％;但用来计算衬砌水压力p1以及衬砌后水流量Q1时,误差相对较小,最大误差为6.3％,特别是利用轴对称解得出的衬砌水压力值与利用数值解得出的衬砌水压力特征值最大误差仅为3.4％.     

Ridership drivers of bus rapid transit systems

We have collected information on 46 bus rapid transit (BRT) systems throughout the world to investigate the potential patronage drivers. From a large number of candidate explanatory variables (quantitative and qualitative), 11 sources of systematic variation are identified which have a statistically significant impact on daily passenger-trip numbers. These sources are fare, headway, the length of the BRT network, the number of corridors, average distance between stations; whether there is: an integrated network of routes and corridors, modal integration at BRT stations, pre-board fare collection and fare verification, quality control oversight from an independent agency, at-level boarding and alighting, as well as the location of BRT. The findings of this paper offer important insights into features of BRT systems that are positive contributors to growing patronage and hence should be taken into account in designing and planning BRT systems.     

A mixed Bayesian network for two-dimensional decision modeling of departure time and mode choice

The modeling of travel decision making has been a popular topic in transportation planning. Previous studies focused on random-utility discrete choice models and machine learning methods. This paper proposes a new modeling approach that utilizes a mixed Bayesian network (BN) for travel decision inference. The authors use a predetermined BN structure and calculate priori and posterior probability distributions of the decision alternatives based on the observed explanatory variables. As a “utility-free” decision inference method, the BN model releases the linear structure in the utility function but assumes the traffic level of service variables follow multivariate Gaussian distribution conditional on the choice variable. A real-world case study is conducted by using the regional travel survey data for a two-dimensional decision modeling of both departure time choice and travel mode choice. The results indicate that a two-dimensional mixed BN provides better accuracy than decision tree models and nested logit models. In addition, one can derive continuous elasticity with respect to each continuous explanatory variable for sensitivity analysis. This new approach addresses a research gap in probabilistic travel decision making modeling as well as two-dimensional travel decision modeling.     

On Safety in Dismantling Temporary Strut of Super-large Tunnels with Double-layer Primary Support北大核心CSCD

More and more multiple-track tunnels and super-large section tunnels have been built, and disman- tling of temporary strut is a weak point of the whole structure during force transfer when the secondary lining is con- structed. It is significant to guarantee structure safety during dismantling of temporary strut. Little systematic re- search on safety in dismantling of temporary strut of the super-large section tunnel with double-layer primary support has been conducted, so the internal force and security of the two-layer primary support of the Xinkaotang tunnel were analyzed by a numerical analysis and site measurement, and it proves the effect of two-layer primary support on the safety during strut dismantling. The research results indicate that: (1) with constant support thickness and one-time longitudinal dismantling length, the safety factor of secondary primary support is larger than that of the first primary support, and the safety factor of the first primary support is larger than that of the single-layer primary support. Change range of safety factor for the first primary support is smaller than that of the single-layer primary support, and the safe factor for the single-layer primary support is smaller than that of the secondary primary support; (2) with the same support pattern, the safety factors increase firstly and then decrease with an increase of the onetime dismantling length. The calculated results of various cases show that the reasonable one-time dismantling length for this project is about 9 m. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

中国近周边海域船舶排放清单及排放特征研究

为分析我国沿海船舶大气污染物排放特征,本研究以船舶自动识别系统数据为基础,收集整理国内外船舶静态数据、排放参数,结合船舶实际航行资料,采用动力法估算了中国近周边海域2014年的船舶排放清单,并分析了靠港、锚泊、港内机动、低速、巡航5个船舶状态下的排放特征,按不同海区对排放进行了统计,并给出了我国三个排放控制区的船舶大气污染物排放情况。结果表明,中国近周边海域范围内由于船舶活动一年产生的硫氧化物、氮氧化物、PM10分别约为87.98万吨、137.84万吨、11.73万吨。排放源分析表明,在船舶的主机、辅机和锅炉3种排放源中,主机是主要排放源,且在航行状态上低速巡航状态排放最大。船舶排放污染物的空间分析表明,90%的船舶排放发生在海岸线至领海基线外96海里范围内,即距离陆地200公里的海域内。     

锌氧化银电池注液激活系统仿真模拟

利用ANSYS Fluent软件对锌氧化银一次电池注液激活系统进行模拟分析,在三种不同特性的点火器匹配注液激活系统条件下,模拟计算各个阀门能否正常开启、开启时间以及开启的顺序。分析计算得出各个阀门开启的时间,能够很好的指导注液系统设计。     

城市交叉口交通流特征与短时预测模型

时间尺度大于15 min的城市交通流预测模型已无法满足交通信号实时控制和交通信息实时发布的需求,通过对广州市中心区交叉路口交通流长期观察和数据采集,分析了各种时间尺度的交通流特性,提出以路口信号周期作为时间尺度,绿灯流率作为变量的ARIMA(p,d,q)短时交通预测模型。以1个和3个信号周期的时间尺度为例,对城市交叉路口不同时间段交通流进行建模和预测。结果表明ARIMA(p,d,q)预测模型结构稳定,算法简单,时间尺度为3个信号周期的预测模型可以很好地保持交通流特征,均方根误差为0.015 9,预测精度较高。     

自动引导车辆(AGV)地图生成方法研究

提出了在人工导引方式下生成AGV数字地图的方法.利用立体视觉提取障碍物边界点,将不同视点处得到的观测集成到数字地图中,进一步提高数字地图的精度.由于AGV运动的不确定性,在将最新的观测集成到地图中之前,通过匹配新的观测数据与地图数据计算AGV位置.实验表明了该方法的有效性.     

一种基于蚁群算法的服务组合方法

Web服务是一种新型的信息集成架构,将多个Web服务组合成一个能完成复杂任务的组合技术是Web服务中关键技术之一．文中提出了一种基于蚁群算法的服务组合方法,对于服务序列可生成全局最优联盟,同时算法基于蚁群系统的学习能力可以有效减少联盟生成的搜索时间和计算量,可实现性好．     

基于复配硬质沥青的大掺量高性能热再生技术

借鉴法国耐久性高模量沥青混合料的设计理念,充分利用沥青路面回收材料中沥青老化的特性和级配细化的特点,采用硬质颗粒复配低标号沥青,并通过丰度系数指标实现大掺量高性能热再生沥青混合料。室内性能评价与验证表明,热再生沥青混合料实现了大掺量,且性能满足现行施工技术规范要求,同时满足法国耐久性高模量沥青混合料的性能指标,为热再生沥青混合料的设计和应用提供了新的思路,具有较好的经济社会效益。