大断面小净距隧道断面优化及其设计参数研究

对于大跨度小净距隧道而言,合理扁平率及双洞间距的设计对于节约成本,提高隧道线形规划具有至关重要的作用,因此,优化大跨度小净距隧道的扁平率及其间距是隧道设计施工面临的关键问题。以某双洞8车道隧道施工为研究背景,通过数值模拟及理论分析,对断面优化及其设计参数进行了深入研究。研究结果表明:随着高宽比的增加,拱顶位移逐渐减少,水平收敛逐渐增大,在高宽比为2.0时达到理想状态,这个时候的拱顶位移和水平收敛基本相同,此时断面有利于开挖。当高宽比取理想高宽比2.0时,这时应力较均匀,是开挖的理想断面,同时考虑行车通行的建筑界限,取高宽比为0.6333是合理的。隧洞埋深对塑性半径和周边位移的影响极大;弹性范围内的支护阻力与隧洞变形成正比;塑性半径随着围岩强度的增加而减小。     

基于排序二叉树的摘挂列车编组钩计划自动编制方法

根据摘挂列车编组调车作业原理,将摘挂列车下落问题抽象为排序问题,提出一种基于排序二叉树的编组钩计划自动编制方法.根据待编列车序列构造排序二叉树;利用排序二叉树的有序性快速搜索出有序车组序列,将其作为下落方案的可选集.考虑邻组、暂合列内收编固定组组别和空闲组别、端组等因素,从可选集中筛选出较优的下落方案.通过定义收编固定组简化列车收编过程,实现列车收编过程的计算机自动编制.通过实例验证,采用该方法降低了选择下落方案的复杂性,减少了列车编组钩计划的调车钩数,而且可根据实际调车线数灵活调整方案.     

大型基坑施工对临近运营地铁影响分析

某市地铁运营指挥中心大型基坑临近运营地铁车站及区间,其施工会对临近的运营地铁车站及区间产生一定的影响,特别是超近距离的基坑施工,必须对其安全性进行分析。文章运用数值模拟分析对大型基坑施工对临近运营地铁安全性进行评估,并针对近接地铁施工存在的风险提出相应防护措施,以期为本地区类似工程提供解决方案。     

大体积盖梁钢管桁架法施工设计

济南二环东路高架桥工程第三合同段跨胶济铁路段上部结构为简支变连续小箱梁,下部结构为门式墩,墩高18.1～25.5 m,墩顶设大体积盖梁,梁高达3 m,仅2.6 m宽,净跨24.7 m,施工难度大。以第114号盖梁为例,介绍了大体积盖梁的钢管桁架法施工设计。     

大地电磁约束反演在隧道勘探中的研究

研究目的:首先在OCCAM反演方法基本原理研究基础上,对OCCAM的目标函数进行修改,加入约束反演项,提出电性参数约束反演的概念,并进行电性参数约束反演模块的开发,最终提高大地电磁方法在长大隧道勘探中的分辨能力。研究结论:对比模型的常规反演和电性参数约束结果发现,利用先验信息的约束反演成像效果明显优于常规反演方法;将此方法应用到实际资料处理中,对比渝利线方斗山隧道电性参数约束反演前后结果,约束反演结果对褶皱、断层、岩溶等地质构造的反映更符合实际。     

地铁出入口大跨度接口梁数值分析

建立空间计算模型对地铁出入口大跨度接口梁的内力等进行数值分析,提出接口梁空间计算模型及其内力计算结果,对比传统平面简化计算模型的内力结果,得知空间计算模型结果更接近接口梁的真实受力状态,接口梁的扭矩不是受力的控制性因素,而接口梁的弯矩接近弹性支座梁的弯矩。     

新九燕山隧道主洞与辅助坑道交叉口施工技术

根据包西铁路大断面红黏土隧道新九燕山隧道施工实例,就斜井和大跨度红黏土隧道交叉口施工方案进行选择,并对斜井向正洞施工方法的转化、施工技术措施等进行阐述。     

高速铁路隧道高瓦斯大断面施工关键技术

针对刘家庄隧道出口段高瓦斯大断面隧道的自身特点,采取了无轨运输方案,对隧道施工的主要机械设备进行防爆改装,通过采取合理的开挖衬砌技术,引入瓦斯、视频系统及人员实时、动态监控系统,为隧道施工安全提供了可靠的保证,并且施工速度较快。     

广交会大客流下的地铁运营组织

阐明在第108界广交会(中国进出口商品交易会)举办期间,大客流对广州地铁的运营组织造成巨大压力,在对地铁客流进行预测和分析的基础上,提出在广交会举办期间客运组织的5项对策和行车组织的4项对策.实践证明,该方案为广交会的成功举办提供了坚实的后勤保障和优质的服务.     

Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.