碗扣式支架方案的应用

对常用支架的结构、地基要求、搭设方案等做了系统论述,并提出了安全注意事项及验算应用方法。     

基于重点区域覆盖的海军护航位置选择研究

针对目前护航海军普遍使用的伴随护航策略存在的效率较低及时间难以协调 等问题,采用区域护航的理念,建立了基于重点区域覆盖的海军护航位置选择模型,该模 型分为海盗选择及劫持模型,商船求救及海军救援模型,海军护航位置选择模型等3 个子 模型,对模型得到的海盗劫持高危水域进行重点区域部署,提高护航海军的护航效率.为 了快速有效地求解该模型,综合运用遗传算法和贪心算法,提出一种改进的求解算法,使 得计算结果更加符合实际需求.案例计算结果表明,该模型和算法能够为海军选择合理的 区域护航位置,使得海军护航工作更加高效稳定.     

浅谈如何提高汽车覆盖件拉延件的质量

简要地从工艺方案制订、模具结构设计以及模具调试等方面分析了影响汽车覆盖件拉延件质量附因素．并对在实际中采取的措施进行了探讨.     

钢筋砼结构抗火参数分析

通过对钢筋砼结构抗火参数的随机性和其敏感性分析,表明了砼保护层厚度是在所给出的参数中对钢筋砼抗火性能最敏感的参数,同时也简单介绍了随机有限元可靠度的分析方法.     

大城市中心区合理干道网密度研究

公交优先是提高城市中心区道路设施利用效率、改善交通环境的有效方法,确定中心区合理干道网密度是满足公交运行、提高运输效率的重要内容. 本文在分析城市中心区交通需求特征和公共交通发展要求的基础上,提出了从宏观系统层、设施、运输组织和交通管理四个方面分析中心区道路网密度影响因素,并探讨了公交优先下公共交通与道路网的关系,考虑公交线网布设和运行的要求,并以公交站点覆盖率和最佳公交线网密度两个主要指标为导向,研究并提出了中心区干道网合理密度和间距推荐值. 该研究提出的干道网密度能够较好地满足中心区公交运行,落实公交优先.     

城市轨道交通ATP车载设备测试用例生成方法

根据对城市轨道交通ATP车载设备功能的分析,搭建了模拟车辆外部接口的城市轨道交通ATP车载设备测试环境,确定了测试ATP车载设备的10个安全输入参数和7个非安全输入参数。基于输入参数建立了可变强度覆盖矩阵,并利用回溯搜索算法优化出由20个用例组成的ATP车载设备测试用例集。测试结果表明,给出的测试用例只有穷举测试法的1%,而测试的有效性达90%以上,能够对ATP车载设备功能进行高效和可靠的测试,并大大降低了测试成本,从而验证了ATP车载设备测试用例生成方法的有效性。     

箱涵顶推施工中的降水、封水方案

在箱涵顶推施工中,为保证箱涵及涵底免受地下水的影响,需要同时进行降水和封水措施．以确保施工的顺利进行。     

Determining locations of charging stations for electric taxis using taxi operation data

The adequate provision of charging infrastructure is critical for the effective deployment of electric taxis. This study attempts to locate charging stations for electric taxis reflecting real-world taxi travel patterns identified from taxis equipped with digital tachographs. Data for one week are processed in order to estimate their charge demand. The estimated temporal distribution of charge demand indicates that it varies day-by-day and hour-by-hour. The maximum set covering model is applied for determining the locations of charging stations. The results show that the pre-specified service distance and service coverage rate (defined by the proportion of total demand served) can be critical factors for determining the number and location of charging stations. These factors should be carefully specified by considering the tradeoff between operational efficiency of charging facilities and user convenience.     

嵌入式软件自动测试技术应用研究

研究分析嵌入式软件洲试特点及嵌入式软件测试工具的工作机理,给出一套针对嵌入式平台系统以及各种DSP板、专用单板机的测试解决方案,阐述采用纯软件方式的测试工具完成高级别覆盖测试方法。     

Optimizing charging station locations for urban taxi providers

Recently, electric vehicles are gaining importance which helps to reduce dependency on oil, increases energy efficiency of transportation, reduces carbon emissions and noise, and avoids tail pipe emissions. Because of short daily driving distances, high mileage, and intermediate waiting time, fossil-fuelled taxi vehicles are ideal candidates for being replaced by battery electric vehicles (BEVs). Moreover, taxi BEVs would increase visibility of electric mobility and therefore encourage others to purchase an electric vehicle. Prior to replacing conventional taxis with BEVs, a suitable charging infrastructure has to be established. This infrastructure consists of a sufficiently dense network of charging stations taking into account the lower driving ranges of BEVs.In this case study we propose a decision support system for placing charging stations in order to satisfy the charging demand of electric taxi vehicles. Operational taxi data from about 800 vehicles is used to identify and estimate the charging demand for electric taxis based on frequent origins and destinations of trips. Next, a variant of the maximal covering location problem is formulated and solved to satisfy as much charging demand as possible with a limited number of charging stations. Already existing fast charging locations are considered in the optimization problem. In this work, we focus on finding regions in which charging stations should be placed rather than exact locations. The exact location within an area is identified in a post-optimization phase (e.g., by authorities), where environmental conditions are considered, e.g., the capacity of the power network, availability of space, and legal issues.Our approach is implemented in the city of Vienna, Austria, in the course of an applied research project that has been conducted in 2014. Local authorities, power network operators, representatives of taxi driver guilds as well as a radio taxi provider participated in the project and identified exact locations for charging stations based on our decision support system.