桥梁模板施工技术应用性研究

桥梁模板是桥梁施工中的重要工具。通过搜集国内外桥梁模板资料,研究总结并提出解决模板工程在桥梁施工中存在各种问题的办法,将对提高工程质量、加快施工速度、提高劳动生产率、降低工程成本和实现桥梁工程的文明施工起到一定的推动作用。     

Travel analytics: Understanding how destination choice and business clusters are connected based on social media data

Understanding how destination choice and business clusters are connected is of great importance for designing sustainable cities, fostering flourishing business clusters, and building livable communities. As sharing locations and activities on social media platforms becomes increasingly popular, such data can reveal destination choice and activity space which can shed light on human-environment relationships. To this end, this research models the relationship between characteristics of business clusters and check-in activities from Los Angeles County, California. Business clusters are analyzed via two lenses: the supply side (employment data by industry) and the demand side (on-line check-in data). Spatial and statistical analyses are performed to understand how land use and transportation network features affect the popularity of the identified clusters and their relationships. Our results suggest that a cluster with more employment opportunities and more types of employment is associated with more check-ins. A business cluster that has access to parks or recreational services is also more popular. A business cluster with a longer road network and better connectivity of roads is associated with more check-ins. The visualization of the common visitors between clusters reveals that there are a few clusters with outstanding strong ties, while most have modest ties with each other. Our findings have implications on the influence of urban design on the popularity of business clusters.     

长大货物车适应THDS轴温探测技术的研究

针对不适应THDS轴温探测系统的长大货物车,分析论证了现车轴箱改进方案适应THDS轴温探测的不足,并提出了轴箱优化方案。经计算、试验和装车验证表明,新轴箱可行、有效、安全,满足THDS轴温探测要求,保证了长大货物车运输安全。     

基于信令数据的出行强度影响因素分析模型

为探究城市交通出行强度影响因素及不同因素的影响程度，本文从土地利用与交通基础设施建设两方面出发，分析包括土地利用混合指数，职住混合率熵指数，公共交通站点 500 m覆盖率，路网可达性等17个指标与出行强度的相关关系；基于相关系数和拟合优度分析，提取7个与出行强度强相关指标，基于所识别指标构建北京市中心城区出行强度多元回归模型.模型结果表明，职住混合率熵指数对出行强度的影响最为显著，公共交通站点覆盖率对出行强度的影响比道路网密度和可达性更为明显.此外，给出单一土地利用/交通基础设施指标对出行强度拟合结果的离群特征分析方法，用于评估不同区域基础设施供给与交通出行需求之间的平衡关系.     

考虑空车调配协调的货物列车开行方案优化研究

为实现空车调配与货物列车开行方案协调优化，结合基本运行图架构与车流径路，构建货运时空服务拓展网络。考虑配空与装卸取送、集编发等环节的时间接续要求，节点与区段不对流空车要求，以重车流全程运送与空车配送等广义总费用最少为目标，建立整数规划弧路模型。针对既有算法设计局限性，结合重车或空车配空的时间接续要求，提出将不同的 k 短路重车流方案与空车配空方案相关联的改进可行解构造方法，设计混合差分进化求解算法。实例研究表明，考虑空车调配进行重车、空车流组织协调优化，能够减少空车走行费用，及时满足装车需求，有效保证作业车流配合中转车流集结编组及时挂线，提高方案可实施性。     

Environmental and transport effects of warehouse relocationing: evidence from Norway

Reducing traffic volumes and CO2-emissions from freight transport has proven difficult in many countries. Although the increasing suburbanization of warehouses is seen as a relevant land use trend, comprehensive analyses of their impact remain scarce. This study uses real data in modeling transport, costs, environmental and modal effects from warehouse relocations around Oslo and Trondheim (Norway). Results indicate that for Oslo, traffic performance (ton-km), CO2-emissions, and transport costs increase following warehouse suburbanization. For Trondheim, transport performance and CO2-emissions increase less, while transport costs decrease marginally. We conclude that specific case characteristics (geography and trade patterns) are important in determining the strength and direction of effects, and expect that common concomitant developments (warehouse centralization and consolidation) would lead to more pronounced results. Our findings confirm some, but challenge other, findings from the relatively scarcely literature available. Finally, the study's more general insights and observations can help advance similar analyses beyond Norway.     

Modeling time-of-day car use behavior: A Bayesian network approach

In this research, a Bayesian network (BN) approach is proposed to model the car use behavior of drivers by time of day and to analyze its relationship with driver and car characteristics. The proposed BN model can be categorized as a tree-augmented naive (TAN) Bayesian network. A latent class variable is included in this model to describe the unobserved heterogeneity of drivers. Both the structure and the parameters are learned from the dataset, which is extracted from GPS data collected in Toyota City, Japan. Based on inferences and evidence sensitivity analysis using the estimated TAN model, the effects of each single observed characteristic on car use measures are tested and found to be significant. The features of each category of the latent class are also analyzed. By testing the effect of each car use measure on every other measure, it is found that the correlations between car use measures are significant and should be considered in modeling car use behavior.     

Time use in travel surveys and time use surveys – Two sides of the same coin?

An in-depth understanding of travel behaviour determinants, including the relationship to non-travel activities, is the foundation for modelling and policy making. National Travel Surveys (NTS) and time use surveys (TUS) are two major data sources for travel behaviour and activity participation. The aim of this paper is to systematically compare both survey types regarding travel activities and non-travel activities. The analyses are based on the German National Travel Survey and the German National Time Use Survey from 2002.The number of trips and daily travel time for mobile respondents were computed as the main travel estimates. The number of trips per person is higher in the German TUS when changes in location without a trip are included. Location changes without a trip are consecutive non-trip activities with different locations but without a trip in-between. The daily travel time is consistently higher in the German TUS. The main reason for this difference is the 10-min interval used. Differences in travel estimates between the German TUS and NTS result from several interaction effects. Activity time in NTS is comparable with TUS for subsistence activities.Our analyses confirm that both survey types have advantages and disadvantages. TUS provide reliable travel estimates. The number of trips even seems preferable to NTS if missed trips are properly identified and considered. Daily travel times are somewhat exaggerated due to the 10-min interval. The fixed time interval is the most important limitation of TUS data. The result is that trip times in TUS do not represent actual trip times very well and should be treated with caution.We can use NTS activity data for subsistence activities between the first trip and the last trip. This can potentially benefit activity-based approaches since most activities before the first trip and after the last trip are typical home-based activities which are rarely substituted by out-of-home activities.     

重载货车摩擦缓冲器阻抗特性的数值模拟

为预测摩擦缓冲器的实际工作状态,从几何特征和作用原理的角度,建立详细的MT-2型缓冲器理论模型。首先,通过对缓冲器内部各摩擦元件的运动学和静力学分析,推导出缓冲器在准静态下的阻抗特性;其次,引入附加摩擦系数量化各摩擦元件之间动静态摩擦过渡时的黏滞补偿,并模拟出缓冲器在动态下的阻抗特性;最后,利用C80型货车冲击试验数据对该缓冲器的理论模型进行验证。验证结果表明:总体上,数值模拟和现场试验下的缓冲器示功曲线基本吻合,说明模型的正确性;局部上数值模拟中缓冲器从加载Ⅰ阶段过渡至加载Ⅱ阶段的突变现象在冲击试验中表现的并不明显,还有待进一步完善。     

Does transport help people to gain employment? A systematic review and meta-analysis of the empirical evidence

ABSTRACT

The role of transport in providing access to employment has received considerable attention. Since transport policies may be motivated by assumed effects on employment probability outcomes, it is important to establish the nature of the relationship between transport and employment outcomes. While the majority of the empirical evidence suggests a positive association, it is not conclusive or consistent and often shows mixed results. To address this confusion, our study has systematically reviewed this evidence base and synthesised it through meta-analysis. We first identified 93 studies that quantitatively assessed the impact of transport on employment outcomes. By systematically merging the empirical evidence, this study establishes a positive association between transport and employment outcomes, with varying effects for four identified categories of transport measures (or combinations thereof): car ownership, public transport access, commute times, and job accessibility levels. This positive association persists in studies that control for endogeneity between transport and employment, but a larger evidence base is needed to establish a more robust relationship, in particular for cities and smaller (rural) areas outside the US-context and with regard to public transport. We then selected 20 methodologically comparable studies for inclusion in the meta-analysis. Our meta-regression models clearly demonstrate that car ownership significantly increases individual employment probabilities, in particular among welfare recipients. Young drivers benefit from access to household cars when these are not in use by their parents, and they are more sensitive to the time and cost implications of longer commutes. While our systematic review suggests that better access to public transport and higher levels of job accessibility increases employment probabilities, meta-regression analysis requires more consistent transport measures. The findings in this study are important for policymakers in that they imply that job seekers may benefit from public policies targeted at improving their access to public transport, in particular for people without access to cars and in areas with fewer job opportunities.