滑床板摩擦力对尖轨不足位移的影响

为解决道岔尖轨不足位移问题,根据尖轨的特殊结构外形、受力特性和扳动机理,建立尖轨不足位移计算仿真模型,分析不同滑床板表面摩擦系数取值下尖轨不足位移的变化。结果表明:摩擦力是导致尖轨产生不足位移的主要原因;尖轨不足位移随滑床板摩擦系数的增加而增大,基本成线性递增关系;最后牵引点距尖轨跟端间间距越大,摩擦系数对不足位移的影响也越大。减小摩擦力和优化牵引点间距能够较好地控制尖轨不足位移。提出设置滚轮式滑床板方案,将轨底与滑床板间的滑动摩擦转化为滚动摩擦,并优化滚轮式滑床板布置方式,进一步减小了尖轨不足位移。     

预应力锚索抗滑桩在滑坡治理中的应用

介绍了预应力锚索抗滑桩技术,对其抗滑机理、受力特点、设计原则、设计流程及相关问题进行分析,并与抗滑桩进行技术经济比较,通过其在黄泥包滑坡整治中的应用,证明其较抗滑桩具有受力机理明确、结构合理、工程造价低、便于施工等优点,是一种具有广泛发展前途的新一代抗滑结构。     

受电弓刮弓事故的捕捉及事故再现试验方法的探索

阐述了自行研制的受电弓刮弓保护装置捕捉到的刮弓事故的全过程,并设计了一种受电弓滑板掉块元件及其控制系统,真实地再现了繁忙主干线上控制受电弓滑板掉块的过程,为保护装置所起作用探索了一个动态的验证方法。     

铁路绿色施工节地与土地资源保护措施评价

为了更好地促进绿色铁路建设,进而促进国家实现建设资源节约型环境友好型社会的目标,必须对施工阶段铁路的节地与土地资源保护措施进行评价。通过研究相关技术标准及铁路施工特点,建立一套完善的铁路绿色施工节地与土地资源保护措施评价指标体系。然后,利用三角模糊数层次分析法确定各指标权重,应用灰色聚类法确定评价指标体系的综合绿色等级。最后,结合实例证明三角模糊数层次法与灰色聚类法结合可以对铁路绿色施工节地与土地资源保护措施进行很好的评价,并能找出铁路施工阶段节地与土地资源保护的不足之处并进行改进。     

论高速铁路建设征地拆迁概算控制

在阐述高速铁路建设征地拆迁现状和存在主要问题的基础上,结合《铁路运输安全保护条例》和《铁路基本建设工程设计概(预)算编制办法》,论述铁路建设工程征地拆迁范围的界定、征地拆迁费用类别的界定,分析征地拆迁数量及标准发生变化超出设计调查的原因,提出工程前期、实施期间、后期3个阶段对征地拆迁费用进行有效控制的措施,并提出改进概预算编制办法的3条建议。     

具有自助吊装功能的自行式DP1000型低位悬拼架桥机

介绍自主研制并投入台湾使用的DP1000型低位悬拼架桥机的总体组成和主要技术指标,着重介绍其所具有的两大特别功能,其一是具有自助吊装前方墩前侧施工牛腿和墩顶块的功能,其二是具有抗溜车功能的自行式滑道系统。这种架桥机新颖先进,实用可靠,施工效率高,节省辅助机具和施工器材,具有明显的技术经济优势。     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

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.     

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.     

A logit-based model for measuring the effects of transportation infrastructure on land value

Mutual interactions between transportation and land use have long been debated. Despite progress made in computational technology, the study of these interactions is not adequately developed. The most important aspect of such interactions is given by the changes in land values due to changes in transportation infrastructures. We consider the behavioural features of these interactions along with the constraints on the land and/or zoning restrictions and propose a reliable model for the first time to predict land value changes with respect to changes in transportation facilities and accessibility. The proposed model is a logit-based mathematical programming methodology where the relative price of land is predicted with respect to transportation accessibility, neighbourhood amenities, location premium, availability of land, and zoning regulations. A real-world case study is used to exhibit the applicability of the proposed methodology and demonstrate the efficacy of the algorithms and procedures.