城市建筑物停车需求研究方法分析

建筑物配建停车场是城市停车设施的主体,其容量大小直接影响到建筑物周边的交通状况,间接影响到建筑物商业活力等社会经济活动。城市建筑物停车需求分析是开展停车配建研究的基础和依据,通过对国内外停车需求研究方法分析整理,在对停车生成率模型、出行吸引模型和停车吸引率模型分析基础上,探讨考虑公交服务水平、区位、泊位共享的停车需求模型,分析各类模型思路与特点,以期为今后建筑物停车需求研究带来启发。     

CSSRC的螺旋桨定常面元法

中国船舶科学研究中心(CSSRC)从八十年代至九十年代一直在发展螺旋桨、导管螺旋桨的定常、非定常面元法,现已在为工业服务中作为日常的计算工具,取得了非常满意的结果.本文将CSSRC过去的研究成果作一系统的归纳整理,供今后使用者参考.文中详细介绍了面元法的理论基础、网格划分、Kutta条件的实施等求解过程.同时还系统地进行了数值试验分析,使应用程序进一步规范化.对面元法对网格数的依赖性、收敛性进行了研究,提出了建议的网格数.通过对多个实例产品的计算,表明与试验结果相比误差可在3%以内,可较好地满足工程应用的目的.     

铁路内燃机车多级五代柴油机油

参照美国机车维修者协会(LMOA)、美国机车生产厂家GE公司和GM公司铁路内燃机车五代油的技术规格,确定研制的五代油暂行技术指标。通过一系列的性能筛选评定试验,包括氧化安定试验、青铜—钢摩擦磨损试验、四球磨损试验、转盘清净性试验和烟炱分散试验,经多次筛选,确定出五代油的配方。并进行L—38轴瓦腐蚀性和1G2高温清净性发动机台架试验。在为期20个月DF4D机车的现场行车试验中,对四代油和五代油两种在用油进行理化、红外光谱、发射光谱和铁谱分析,还对柴油机的动力组进行拆检:连杆轴瓦和活塞环称重、活塞清净性评分,综合考察机油的抗氧、抗磨和清净分散性能。行车试验验证使用五代油可以减少机油中烟炱凝聚的几率,降低粘度增长的速度。研究结果表明,研制的五代油具有较好的抗氧、抗磨和清净分散性能,粘度增长得以抑制,延长了机油的使用寿命。     

一种两维区域三角剖分算法的改进及其应用

经过对文献[1]S.H.LO方法的改进,考虑到海岸河口海区、河道等水域的特点,提出了一个在水动力数学模型中十分适用的三角形网格的自动生成方法,编制了三角形网格自动生成通用程序。该方法通过引入区域内节点间距函数,人为给定某一定值或渐变数值可在任一局部水域进行网格加密。应用该方法成功对胜利油田海域的数学模型计算域进行了三角自动剖分。     

SMS水动力学软件

简要介绍了水动力学软件SMS的基本功能,并用简单实例对其前后处理功能做了展示。     

A generalized partite-graph method for transportation data association

There are many problems in transportation which involve reconstructing the associations between different entities. For example, data points related to a vehicle from different sensors could be matched to reconstruct the trajectories of vehicles. Or, in population synthesis for microsimulation, lists of persons, dwellings, and vehicles could be generated individually from source data and then matched into synthetic households. There are numerous other examples. The unifying theme is a desire to construct realistic unit-level associations from aggregate or anonymized data. The problem demands a method that is behaviorally consistent and operationally efficient to handle large datasets. We adapt concepts from graph theory to formulate this class of problems as a k-partite graph. This approach is generic and can incorporate expectations of behavior in the form of edge weights. A Dijkstra algorithm based solution is proposed for a subset of k-partite graphs which permits a direct comparison with pair-wise matching and applied to a case study of bicycle tracklets. We then propose an iterative improvement algorithm as a generic method and apply it to a complete k-partite graph in a population synthesis case study. The first case study shows that the k-partite algorithm outperforms the previously used pair-wise matching algorithms. The second case study demonstrates the generality of the proposed algorithm to all k-partite graphs and shows that the generic method is fast and scalable to large problems. As a whole, this paper aims to show that k-partite methods are behaviorally consistent, efficient, and potentially applicable to a wide variety of transportation data association problems.     

Making time count: Traveler activity engagement on urban transit

In practice, travel time is assigned a cost and treated as a disutility to be minimized. There is a growing body of research supporting the hypothesis that travel time has some value of its own, and the proliferation of information and communication technology (ICT) may be contributing to that value. Travelers’ attitudes are confounded with their mode choice, and as telecommunications mediate travel behavior, analysts must recognize the interaction between time use and customer satisfaction for appropriate travel demand management. To that end, this paper presents results from jointly estimated models of travelers’ latent satisfaction and on-board activity engagement using Chicago transit rider data gathered in April 2010. The simple questionnaire and small sample corroborate the findings of past research indicating travel attitudes and activity engagement have potential to influence travelers’ value of time, and many transit riders consider transit a better use of time and/or money than driving. The findings affirm the need for a more holistic understanding of value of time for travel demand management and infrastructure valuation. As time use has an influence on users’ valuation of the transit mode, offering opportunities to conduct certain leisure activities could improve the perceived value of travel time.     

Should we all just stay home? Travel,out-of-home activities,and life satisfaction

How and why travel contributes to our life satisfaction is of considerable import for transportation policy and planning. This paper empirically examines this relationship using data from the American Time Use Survey. It finds that, controlling for relevant demographic, geographic, and temporal covariates, travel time per day is significantly and positively associated with life satisfaction. This relationship is attenuated, but still significant, when the amount of time spent participating in out-of-home activities is controlled for. Time spent bicycling is strongly associated with higher life satisfaction, though it attains significance only in some models; time spent walking is also quite positive, though it is not significant. However, both walking and bicycling are positively and significantly associated with life satisfaction when time spent on purely recreational walking and bicycling is included. Life satisfaction is positively and significantly associated with time spent traveling for the purposes of eating and drinking, religious activities, volunteering, and playing and watching sports. Travel time exhibits a strong positive relationship with life satisfaction in smaller towns and cities, but in large cities the association weakens, and for very large cities travel time may actually not be associated with life satisfaction at all. This may be due to the costs of traffic congestion, which disproportionately exists in large cities. In all, while the associations between travel and life satisfaction are clear, the causal story is complex, with the positive relationships potentially being explained by (1) travel allowing us to access destinations that make us happy, (2) the act of travel itself being fulfilling, and/or (3) intrinsically happier people being more likely to travel. In all likelihood, all three factors are at play.     

From traces to trajectories: How well can we guess activity locations from mobile phone traces?

Passively generated mobile phone dataset is emerging as a new data source for research in human mobility patterns. Information on individuals’ trajectories is not directly available from such data; they must be inferred. Many questions remain in terms how well we can capture human mobility patterns from these datasets. Only one study has compared the results from a mobile phone dataset to those from the National Household Travel Survey (NHTS), though the comparison is on two different populations and samples. This study is a very first attempt that develops a procedure to generate a simulated mobile phone dataset containing the ground truth information. This procedure can be used by other researchers and practitioners who are interested in using mobile phone data and want to formally evaluate the effectiveness of an algorithm.To identify activity locations from mobile phone traces, we develop an ensemble of methods: a model-based clustering method to identify clusters, a logistic regression model to distinguish between activity and travel clusters, and a set of behavior-based algorithms to detect types of locations visited. We show that the distribution of the activity locations identified from the simulated mobile phone dataset resembles the ground truth better than the existing studies. For home locations, 70% and 97% of identified homes are within 100 and 1000 m from the truth, respectively. For work places, 65% and 86% of the identified work places are within 100 and 1000 m from the true ones, respectively. These results point to the possibility of using these passively generated mobile phone datasets to supplement or even replace household travel surveys in transportation planning in the future.     

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目前我国综合交通枢纽上盖物业开发主要基于社会经济的发展和车站经济效益的角度进行开发研究,较少考虑其对周边交通的影响,以及交通对上盖物业的体量大小的影响.本文以重庆市沙坪坝综合交通枢纽为例,根据大量的交通调查数据,结合重庆市的文化及地理情况,将重庆市沙坪坝综合交通枢纽以立体集约型的方式规划其商业设施.本文采用商圈理论估计沙坪坝综合枢纽商业建筑总体规模,并提出不同的物业分类方案.最后依据交通量调查,利用圈层外推分析综合枢纽建筑对周边道路的交通影响并检验设计方案的合理性.