山区高速公路特大桥梁设计阶段造价控制分析

吉茶高速公路是典型的山区高速公路,沿线地质、地形条件复杂,其关键控制性工程矮寨大桥是目前峡谷跨度世界第一的悬索桥,工程概算占总投资的18%。由此可见,山区高速公路特大桥梁的造价控制对控制整条高速公路的造价影响重大。     

城市新区道路横断面规划设计研究

道路系统的建设是引导城市新区开发、改善投资环境的重要措施。城市道路横断面作为道路交通功能实现的重要载体,其合理规划设计有利于保障道路安全畅通,提高资源利用效率,实现城市社会经济的良性发展。     

快速公交车站设计探析——以杭州、常州快速公交设计为例

快速公交设计是个系统工程,其中车站设计部分是其中的关键要素。从宏观方面论述了路线及站点布置,在保证运营速度的情况下,论述了站间距设置的一般考虑范畴。从车站布设、车站功能和车站形式等方面简明介绍了车站设计的相关研究;并从客流角度入手,抓住快速公交的运营特征,把握车站的设计规模。并通过实践经验的总结提出了车站设计的相关技术标准。     

山区高速公路景观设计分析

在进行山区高速公路景观设计时,需充分体现动态美学观念,使公路成为自然风景的一部分,为驾驶者、乘客等用路者提供一个舒适优美的道路环境,以减少驾驶疲劳,保证行车安全。     

山区高速公路某高填方拱涵设计

涵洞设置的合理性对工程造价和使用质量有重要影响。围绕高填方拱涵设计中的关键问题,对涵台尺寸的验算、涵顶填土垂直压力的计算及地基处理方法进行探讨,提出了相应的设计建议,对同类工程具有一定的指导意义和借鉴价值。     

自升式海洋平台的防火结构设计

针对海洋平台的特点,论述了海洋平台结构防火的实际工程应用,结合某自升式海洋平台着重介绍该平台上防火等级,防火材料与防火涂料的设计应用,供海洋平台的设计建造参考.     

城市大跨度地下空间工程技术研究

随着城市地下空间开发和利用向大跨度、多功能、深地下和立体交叉方向发展,对地下工程的设计施工提出了越来越高的要求.通过对中国新建城市大跨度地下工程和欧美当代地下洞室工程的研究,分析国内外城市大跨度地下工程的建设思路和特点,总结这些地下工程在勘察选址、设计和施工以及规划方面采用的方法和经验,对今后地下工程的可持续发展具有重...     

舰船顶层设计指标最优分配问题计算方法

基于大型复杂工程系统设计的多学科设计优化算法,开展了舰船顶层设计指标最优分配的计算方法研究,基于协同优化算法提出了舰船顶层设计指标最优分配的一种通用算法框架。     

Experimental design influences on stated choice outputs: An empirical study in air travel choice

Discrete choice experiments are conducted in the transport field to obtain data for investigating travel behaviour and derived measures such as the value of travel time savings. The multinomial logit (MNL) and other more advanced discrete choice models (e.g., the mixed MNL model) have often been estimated on data from stated choice experiments and applied for planning and policy purposes. Determining efficient underlying experimental designs for these studies has become an increasingly important stream of research, in which the objective is to generate stated choice tasks that maximize the collected information, yielding more reliable parameter estimates. These theoretical advances have not been rigorously tested in practice, such that claims on whether the theoretical efficiency gains translate into practice cannot be made. Using an extensive empirical study of air travel choice behaviour, this paper presents for the first time results of different stated choice experimental design approaches, in which respective estimation results are compared. We show that D-efficient designs keep their promise in lowering standard errors in estimating, thereby requiring smaller sample sizes, ceteris paribus, compared to a more traditional orthogonal design. The parameter estimates found using an orthogonal design or an efficient design turn out to be statistically different in several cases, mainly attributed to more or less dominant alternatives existing in the orthogonal design. Furthermore, we found that small designs with a limited number of choice tasks performs just as good (or even better) than a large design. Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound. This paper will enable practitioners in better understanding the potential benefits of efficient designs, and enables policy makers to make decisions based on more reliable parameter estimates.     

Multi-objective optimization of a road diet network design

The present study focuses on the development of a model for the optimal design of a road diet plan within a transportation network, and is based on rigorous mathematical models. In most metropolitan areas, there is insufficient road space to dedicate a portion exclusively for cyclists without negatively affecting existing motorists. Thus, it is crucial to find an efficient way to implement a road diet plan that both maximizes the utility for cyclists and minimizes the negative effect on motorists. A network design problem (NDP), which is usually used to find the best option for providing extra road capacity, is adapted here to derive the best solution for limiting road capacity. The resultant NDP for a road diet (NDPRD) takes a bi-level form. The upper-level problem of the NDPRD is established as one of multi-objective optimization. The lower-level problem accommodates user equilibrium (UE) trip assignment with fixed and variable mode-shares. For the fixed mode-share model, the upper-level problem minimizes the total travel time of both cyclists and motorists. For the variable mode-share model, the upper-level problem includes minimization of both the automobile travel share and the average travel time per unit distance for motorists who keep using automobiles after the implementation of a road diet. A multi-objective genetic algorithm (MOGA) is mobilized to solve the proposed problem. The results of a case study, based on a test network, guarantee a robust approximate Pareto optimal front. The possibility that the proposed methodology could be adopted in the design of a road diet plan in a real transportation network is confirmed.