混凝土桥梁粘贴加固技术的研究进展

粘贴加固技术是混凝土桥梁结构维修加固中常用的简捷、有效的一种技术方法。近年来，纤维增强复合材料(FRP)粘贴加固技术的研究及应用已成为业内的热点。结合工程管理实践及有关资料，对混凝土粘贴加固技术的研究进展进行了概要地总结介绍。     

桥梁加固分阶段受力抗弯承载力极限状态分析

粘贴钢板或其他纤维复合材料对梁的受拉薄弱区进行补强是桥梁加固的主要方式之一。粘贴钢板加固一般采用带载加固，其承载力应按两阶段受力构件计算。在基本假设的基础上．针对桥梁构件两阶段受力的特点．对T形截面梁，分析粘贴钢板加固桥梁构件正截面抗弯承载力的计算公式和适用条件，并给出极限状态加固设计的方法和步骤。     

大沙河桥加固维修工艺

针对大沙河桥的病害情况,介绍了采用环氧树脂灌缝、粘贴碳纤维布、粘贴钢板等新材料、新施工工艺对危旧桥梁进行加固维修的方法,并对斜撑加固及桥面铺装施工工艺进行了分析。实践表明,通过以上加固维修工艺能够解决大沙河桥的病害情况,使桥梁的使用寿命得到提高。     

粘贴附加物加固桥梁效能分析

阐述了粘贴附加物加固桥梁需中断交通施工的必要性,通过实桥算例论述了粘贴钢板和粘贴纤维加固桥梁在强度、承载力、刚度、设计、施工、造价等方面的优缺点.结果说明,粘贴钢板加固效果优于粘贴纤维加固,但在经济性和施工方面不如后者.     

粘贴钢板加固提升桥梁质量

介绍了粘贴钢板加固的概念与特征,结合工程实例,探讨分析了粘贴钢板加固提升桥梁质量的施工流程。工程运用表明,加固后钢板粘结强度合格、增强桥梁的承载力、显著提升桥梁质量,类似桥梁加固可从中得到参考与借鉴。     

CFS在大堡桥维修加固中的应用

该文通过介绍粘贴CFS加固大堡桥施工的一般工艺流程和关键控制要点,为CFS加固桥梁的进一步研究及应用提供参考。     

粘贴钢板补强技术在国贸桥加固中的应用

目前,用于桥梁补强加固的方法主要有碳纤维加固、粘贴钢板加固等。该文介绍了北京国贸桥一期异形板板底加固采用了粘贴钢板补强加固方法。即:采用化学锚栓将钢板锚固于桥面,钢板与桥面间预留缝隙,四周封口后采用高效改性环氧粘接剂灌注填充缝隙。此方法具有较高的强度、刚度、稳定性、整体性和耐久性,可供今后类似工程借鉴。     

粘贴钢板和碳纤维加固刚架拱桥的应用研究

粘贴钢板和粘贴碳纤维是加固混凝土结构常用的两种方法。为了更准确掌握和应用好上述两种方法,对其在加固混凝土结构时进行受力分析是有必要的。因此,本文以钢筋混凝土刚架拱桥的加固工程为例,应用有限元分析软件作为工具,分别计算了加固前结构设计截面的抗力与挠度,以及加固后结构关键部位的应力和挠度,分析其适用性,为确定合理的加固方案提供了保证,对其他桥梁结构的加固有一定的参考价值。     

粘贴钢板在旧桥加固中的应用

采用粘贴钢板改善构件的抗弯、抗剪能力,减少裂缝的扩展,达到提高桥梁承载能力与耐久性,是旧桥加固常用的方法。     

粘贴钢板法在桥梁横向联结加固中的应用

总结粘贴钢板加固法在实际工程中的成功应用,阐明桥梁横向联结力不足的解决办法与实际应用中的加固流程和加固材料指标。     

桥梁组合钢模板的设计施工及贴膜的应用

组合钢模板因体积小、重量轻、拆装方便而得到广泛使用,但也因使用其浇注的混凝土外观质量差而受到限制。该文通过工程实例,论述了桥梁组合钢模板设计方案的改造和贴模方法,介绍了施工中采取的技术措施和存在的问题。     

基于网络计划模型的施工危险性动态评价方法

危险源评价是公路施工中安全控制管理的关键环节,以往一般是在施工前针对施工项目对象进行危险源辨识并进行危险性评价,常用的评价方法如模糊综合评价法没有体现施工的动态变化特性。文中利用网络计划技术中时标网络图的实时动态分析特性,将其应用到公路施工危险性评价中,对危险源进行精确定位,并做出动态评价。     

“沥可贴”在高速公路沥青路面预防性养护中的应用

以广东省GZX高速公路沥青路面"沥可贴"预防性养护工程为依托,通过室内试验、工程应用、使用性能跟踪观测,表明"沥可贴"微罩面预防性养护措施可快速恢复路表功能、减缓路面的破坏速率、推迟路面的破坏及大修和重建时间,可满足高速公路沥青路面维修养护的需要。     

Highly reliable driving workload analysis using driver electroencephalogram (EEG) activities during driving

Traffic accidents are caused by various factors, which can be classified into human factors, vehicle factors and environmental factors. Recently, human factors have been drawing particular attention as efforts are being made to enhance the safety performance of vehicles and improve road conditions. Driving distraction caused by an increased driving workload is a representative human factor. Various studies in the past have attempted to quantify the driving workload by using EEG activities. However, they have failed to consider vibration properties generated from vehicle engines. A number of noise signals were included in brainwave signal processing, which resulted in a failure to obtain reliable outcomes. Thus, this study suggests driver EEG activities free of vehicle engine secondary vibration in order to develop a method that analyzes the driving workload with high statistical reliability. By using the analytical method developed in this study, standard values of driving workload for straight and left-turn driving that has statistical significance could be calculated. The analytical method for driving workload created by this study can be applied to HVI and road design.     

汽车产销形势继续向好——2009年6月份汽车工产销综述

6月，汽车产销延续了3月以来的良好发展态势，总体保持平稳增长，连续4个月产销超过百万辆。上半年，汽军产销创历史新高，乘用车受政策因素影响增长明显，成为带动行业发展的最重要力量。     

纯电动汽车经济性驾驶的影响因素及应用

我国新能源汽车技术路线是以纯电驱动为主,随着纯电动汽车保有量的增加,降低其行驶能耗既符合国家节能 减排的战略,又能改善用户的用车体验。基于某纯电动SUV车型的实际道路驾驶数据,通过相关性和降维分析得到加速 度的方差是影响能耗的最关键因素;进而采用一维模型仿真,研究匀速、加减速和坡道3种典型工况下能耗的形成机理 和优化方向,得到平衡能耗与行驶时长的经济性驾驶原则,如高速巡航时应适当降低车速,市区拥堵时控制加速度变化 幅度,上下坡时利用车辆惯性,减少制动能量回收。     

Possible experimental method to determine the suspension parameters in a simplified model of a passenger car

Currently, as well as in the past, researchers have shown great interest in developing suspension systems for vehicles and especially in the design and optimization of the suspension parameters, such as the stiffness and the damping coefficient. These parameters are considered to be important factors that have an influence on safety and improve the comfort of the passengers in the vehicle. This paper describes a simplified methodology to determine, in a quick manner, the suspension parameters for different types of passenger cars equipped with passive suspension systems. Currently, different types of passenger cars are produced with different types of suspension systems. Finding a simplified methodology to determine these parameters with sufficient accuracy would contribute a simplified and quick method to the inspection of the working conditions of a suspension system. Therefore, a simple system to determine these parameters is needed. An analysis of the suspension parameters is performed using mathematical modeling and numerical analysis conducted using the Working Model software. The result derived from the developed methodology shows small errors when compared with the generic values, and it can be concluded that the design of the suspension parameter measurement device using the developed methodology is useful, simple, and has sufficient accuracy.     

Platoon recognition using connected vehicle technology

This article presents a mathematical model for real-time platoon recognition using the connected vehicle (CV) technology. Platoon information is a crucial part of traffic signal coordination and is difficult to obtain with traditional technologies such as loop detectors. The past work on platoon recognition using CV is very limited and lacked verification on the applicable range or evaluation of the performance of algorithms. The proposed algorithm is focused on estimating platoon characteristics for signal coordination and adaptive signal control with CV's vehicle-to-vehicle communication and an onboard GPS device. First, the detected platoon is identified by a modified critical time-headway. Then, platoon size and starting and ending times are estimated. Lastly, the filtering process for “qualified” detected platoon is proposed to optimize detectability. The results show that the proposed algorithm can estimate well in various traffic conditions and under both fixed-time and actuated signal control without the need for recalibration. Furthermore, two analytical models to estimate the detection rate are proposed and shown to be close to the numerical results and can be used to estimate the required market penetration ratio for the application without field experiments or microscopic simulation. The accuracy of both the recognition algorithm and detection rate estimation is obtained without relying on inputs that are hard to obtain in practice. Accordingly, the proposed algorithm can be an important part of adaptive signal control focusing on real-time coordination in CV environment.     

Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion

Collision avoidance at intersections involving a host vehicle turning left across the path of an oncoming vehicle (Left Turn Across Path/Opposite Direction) have been studied in the past, but mostly using simplified interventions and rarely considering the possibility of crossing the intersection ahead of a bullet vehicle. Such a scenario where the driver preference is to avoid a collision by crossing the intersection ahead of a bullet vehicle is considered in this work. The optimal vehicle motion for collision avoidance in this scenario is determined analytically using a particle model within an optimal control framework. The optimal manoeuvres are then verified through numerical optimisations using a two-track vehicle model, where it was seen that the wheel forces followed the analytical global force angle result independently of the other wheels. A Modified Hamiltonian Algorithm controller for collision avoidance that uses the analytical optimal control solution is then implemented and tested in CarMaker simulations using a validated Volvo XC90 vehicle model. Simulation results showed that collision risk can be significantly reduced in this scenario using the proposed controller, and that more benefit can be expected in scenarios that require larger speed changes.