高校基建档案建设工作探析

论述了高校基建档案建设工作对高校发展的重要性,在指出当前高校基建档案建设工作中存在的基础上,最后提出了解决这些问题相应的措施,进一步分析了它的原因.     

高架复合道路对城市空间格局的影响——以硚口区为例

城市高架桥的建设极大的提高了道路交通承载能力,减缓城市拥堵程度,是城市发展的强力引擎,但也会给周边空间格局造成一定负面影响。采取居民访问、调查问卷等手段,分析城市复合高架道路周边空间的交通组织、生态景观、土地价值的影响,并寻求产生的原因。结合硚口区建设现状,在优化既有高架复合道路桥下空间,提高桥下空间品质的基础上,提出主干路不宜采用高架复合道路建设形式、加密微循环路网、优先发展公共交通等规划建议。     

舰艇编队智能防空决策模型研究

海上战机稍纵即逝,指挥决策时间的长短往往可以决定小到1艘舰艇大到1支舰队的命运。在抗击来袭的空中目标问题上,已有的火力分配模型都存在一定的局限性,不能更好满足舰艇编队的防空需求。本文试图引入作为通用智能基础的Soar系统,对来袭的空中目标进行智能决策,建立舰艇编队智能防空决策模型。以Soar作为决策推理引擎,对所有来袭目标威胁程度不断循环推理,以期优化打击方案,大大降低决策时间,更好地满足实战需要,提高海上编队的防空作战能力。     

城市土地利用与路段交通量关系模型的研究

分析了城市土地利用与交通间的相互关系,使用引力模型建立了土地利用与路段交通量关系模型,从而了简化交通规划中交通需求预测的过程,并为寻找土地利用和交通规划的最佳结合提供了一种新思路。     

敏感环境条件下地铁停车场桥基施工对下伏高铁隧道群的扰动效应研究

深圳地铁6号线民乐停车场工程上跨3条高速铁路隧道,具有结构复杂、环境敏感、地质复杂、施工难度大、工期紧张及施工风险高的特点。为了准确分析和合理评估复杂地质环境条件下大直径桩基开挖对运营高铁隧道安全运营的影响,运用三维数值模拟软件分析了该地铁停车场桥基施工对下部侧穿高铁填土隧道的扰动效应。数值计算结果表明,在多种开挖方案和技术条件下,大直径桩基的开挖成孔不会造成紧邻地铁停车场下方各运营高铁隧道的变形和受力状态的明显改变,整体处于施工安全范围内,表明桩基施工不会危及高铁隧道的结构安全和列车的行车安全。结论对该工程建设及高铁隧道安全运营具有一定的指导意义,可供类似地质条件下相互毗邻、复杂交接工程的设计与施工参考。     

海域围堰复杂地质深基坑支护的变形规律分析

为有效控制上软下硬地质条件下海域围堰围护结构的变形,以汕头苏埃通道工程始发井及后配套基坑为依托,对基坑施工中围护结构水平位移、混凝土支撑轴力、地面沉降等项目进行全过程监测,分析围护体系的变形受力与开挖工序的对应关系。主要研究与结论如下： 1）围护结构的最大水平位移的发生位置随基坑开挖深度增加逐渐下移,围护结构水平位移与支撑轴力最大值都位于基坑中下部位置,且二者都表现了基坑西侧大于基坑东侧; 2）基坑周边未加固段地表持续沉降,加固段的地表沉降较小; 3）建立综合监测预警机制,对基坑施工薄弱部位提出预警,信息化指导施工,保证了基坑的施工安全,为后续类似地质条件下基坑支撑体系提出了优化建议。     

郊域轨道交通对土地利用演变的影响分析

选择贝叶斯网络(Bayesian Network, BN)对郊域轨道交通引起的土地利用演变规律(Land Use Change，LUC)进行研究。将影响范围外设为参照区分析LUC是否因郊域线出现差异，并与 市郊线进行对比。东京都的案例结果表明，郊域线对LUC产生了影响，其中，影响较大的是森林、 建筑与运动竞技用地(运营期)及森林、运动竞技与水域(开通前)地块，上述地块缓冲区与参照区的 差异依次是-32.08%，12.59%，8.24%与-24.23%，4.62%，4.40%；然而市郊线未产生影响，说明不同 于市区LUC的多驱动力，郊域线作为郊区LUC的强驱动力，引起的LUC变化显著，可为通过建设 郊域线推动郊区土地发展提供依据。由于市区土地发展成熟，土地利用(Land Use，LU)延续性 好，故市郊线当期总与前期LU有直接关系；郊域线作为郊区LUC的强驱动力，运营后引起LUC 活跃程度比较大，故导致运营期与前期 LU 无直接关系，可为郊域线土地开发时期提供参考依 据。BN推理显示，郊域线运营期缓冲区终态为建筑地块受建筑用地聚集程度影响低于参照区， 说明郊域线运营期终态为建筑地块的演变较独立，同样是由郊域线引起LUC活跃程度比较大引 起的；为支持郊域线运营期地块终态为建筑用地，区域需87.2%的概率为缓冲区，初始邻域用地需 98.5%为非森林地块，以上可为郊域线土地开发中建筑用地布局与选址提供参考依据。以多摩线 2006年LU作为初始态，预测2014年LU，结果精度达89.9%，表明BN具有较强的推理能力。最 后，挖掘轨道交通LUC机制，即其通过提高出行可达性影响人们愿意在其周边居住与生活，因此 出现缓冲区用地演变现象，并据此阐释了郊域线的LUC机制。     

Uni- and bi-directional pedestrian flow in the view-limited condition: Experiments and modeling

In this paper, the impact of vision on the uni- and bi-directional flow has been investigated via experiment and modeling. In the experiments, pedestrians are asked to walk clockwise/anti-clockwise in a ring-shaped corridor under view-limited condition and normal view condition. As expected, the flow rate under the view-limited condition decreases comparing with that under the normal view condition, no matter in uni- or bi-directional flow. In bidirectional flow, pedestrians segregate into two opposite moving streams very quickly under the normal view condition, and clockwise/anti-clockwise walking pedestrians are always in the inner/outer ring due to right-walking preference. In the first set of experiment, spontaneous lane formation has not occurred under the view-limited condition. Pedestrian flow does not evolve into stationary state. Local congestion occurs and dissipates from time to time. However, in the later sets of experiments, spontaneous lane formation has re-occurred. This is because participants learned from the experience and adapted right-walking preference to avoid collision. To model the flow dynamics, an improved force-based model has been proposed. The driving force has been modified. The right-walking preference has been taken into account. The fact that pedestrians cannot judge the moving direction accurately under limited-view condition has been considered. Simulation results are in good agreement with the experimental ones.     

An investigation on the performances of mode shift models in transit ridership forecasting

This paper aims at investigating the over-prediction of public transit ridership by traditional mode choice models estimated using revealed preference data. Five different types of models are estimated and analysed, namely a traditional Revealed Preference (RP) data-based mode choice model, a hybrid mode choice model with a latent variable, a Stated Preference (SP) data-based mode switching model, a joint RP/SP mode switching model, and a hybrid mode switching model with a latent variable. A comparison of the RP data-based mode choice model with the mode choice models including a latent variable showed that the inclusion of behavioural factors (especially habit formation) significantly improved the models. The SP data-based mode switching models elucidated the reasons why traditional models tend to over-predict transit ridership by revealing the role played by different transit level-of-service attributes and their relative importance to mode switching decisions. The results showed that traditional attributes (e.g. travel cost and time) are of lower importance to mode switching behaviour than behavioural factors (e.g. habit formation towards car driving) and other transit service design attributes (e.g. crowding level, number of transfers, and schedule delays). The findings of this study provide general guidelines for developing a variety of transit ridership forecasting models depending on the availability of data and the experience of the planner.     

A comprehensive dwelling unit choice model accommodating psychological constructs within a search strategy for consideration set formation

This study adopts a dwelling unit level of analysis and considers a probabilistic choice set generation approach for residential choice modeling. In doing so, we accommodate the fact that housing choices involve both characteristics of the dwelling unit and its location, while also mimicking the search process that underlies housing decisions. In particular, we model a complete range of dwelling unit choices that include tenure type (rent or own), housing type (single family detached, single family attached, or apartment complex), number of bedrooms, number of bathrooms, number of storeys (one or multiple), square footage of the house, lot size, housing costs, density of residential neighborhood, and commute distance. Bhat’s (2015) generalized heterogeneous data model (GHDM) system is used to accommodate the different types of dependent outcomes associated with housing choices, while capturing jointness caused by unobserved factors. The proposed analytic framework is applied to study housing choices using data derived from the 2009 American Housing Survey (AHS), sponsored by the Department of Housing and Urban Development (HUD) and conducted by the U.S. Census Bureau. The results confirm the jointness in housing choices, and indicate the superiority of a choice set formation model relative to a model that assumes the availability of all dwelling unit alternatives in the choice set.