管道内防腐层补口技术研究进展

管道内衬或内防腐涂层现场施焊时,焊缝两侧的防腐层会由于高温作用而破坏,使环焊缝处不能得到有效的保护,内补口技术也成为影响管道质量的主要瓶颈。文中介绍了国内外主要的内补口技术,如内补口机法、内衬保护套（管）焊接法、不锈钢接头法、机械连接法等,并指出各方法的特点。文中还就内补口技术的质量控制和研究方向等提出了建议。     

压气条件下泥膜进气值测量试验研究

在压气条件下,进气是泥膜透气失效的起始点。为测量并研究泥膜在气压下的进气压力值（进气值）,通过自制的试验装置,在不同压气条件下对3种泥膜进行进气值测量试验。试验结果表明： 1)由闭气排水与固结排水的差值可以辨别泥膜是否进气,得到泥膜进气值; 2)采用泥膜特征孔径D90/2代入推导公式可近似计算泥膜进气值; 3)泥膜在不同压气条件下进气值不同,增压速率越低,泥膜进气值越大; 4)在较快和较慢的增压速率下存在进气值变化趋于稳定的现象,最大进气值为最小值的2倍以上。     

盾构法T接隧道结构受力现场试验研究——以宁波轨道交通3号线联络通道为例

为了了解盾构法T接隧道在施工过程中主隧道外部的荷载以及响应,以国内第一条使用机械法施工的联络通道--宁波轨道交通3号线为背景进行研究。本文通过研究施工过程中的施工工况节点,现场监测主隧道结构的外荷载、收敛变形并计算结构内力,得到在整个施工过程中主隧道的结构响应及其变化规律。通过本文的研究,可以得出以下结论： 1）施工过程可依据外部荷载和结构体系进行划分工况,各工况具有明显的不同响应; 2）始发端和接收端的内力变化主要受到盾构顶力和外部注浆荷载的影响,且主要影响切削侧,切削过程中的内力增量在10%～20%,注浆压力影响的增量部分达到了50%; 3）各环及内支撑轴力增量在200 kN以下,破洞位置导致的轴力损失可以由其余位置共同承担,不需要特殊的破洞阶段超载设计。     

金门特长公路隧道通风方案比选研究

为解决目前特长公路隧道通风方案比选时局限于送排式通风的问题,从方案设计角度分析几种不同纵向通风模式的功能特点、适用条件,结合送排式通风与互补式通风的特点,提出单通道互补式通风的组合通风模式,并以金门特长公路隧道为例,从全寿命周期角度,对“通风井送排式”“单通道互补式”“双通道互补式”“吸尘式”4种通风方案进行比选研究。结果表明： 1）送排式通风受通风井位置影响较大,从运营通风角度,宜设置在上坡隧道中部偏下风方向; 2）互补式、吸尘式通风能够突破通风井选址的限制,但对于超过5 km的隧道,需要设置专用排烟井; 3）单通道互补式通风省去送风井,保留了送排式通风的排烟功能,具备比选价值。     

地下工程平衡稳定理论再研究

目前,地下工程结构在计算分析方面主要采用传统松弛荷载理论（类似荷载结构法）和数值分析法;在合理结构构造、施工工法等方面主要采用岩承理论（类似地层结构法）,这些已有理论或方法隐含“变形协调控制”假定,实际应用中往往将这些假定忽视,因而需进一步发展新的理论方法以适应实际应用的需求。在大量工程实践和试验的基础上,揭示地下工程有效承载结构层与围岩荷载转移规律之间的关联性,建立地下工程平衡稳定理论,此理论既能反映传统“松弛荷载理论”和现代“岩承理论”的基本内容,又能拓宽平衡稳定性等内容,是地下工程平衡稳定性的新认识、新理念; 同时提出能量控制技术、预支护技术、受力独立性综合技术、变形协调控制技术4项关键技术。将这些技术合理地运用到实际工程施工中,将便于利用已有或新成果分类预防和控制地下工程质量和安全,为解决新型地下工程问题提供新的依据。     

船舶中速主机低频排气噪声控制研究

结合在船舶建造中遇到的低频主机排气噪声控制问题,从实船噪声源的确定、主机排气噪声谱分析和消声器声学性能验证等方面进行探索,并从排气噪声控制角度对船舶柴油机排气系统设计提出了建议。     

考虑螺旋桨体积力的水下机器人水动力特性仿真

为在初步设计时预测ROV的水动力性能,使用CFD技术进行分析,以ROV模型为例,最大程度地保留ROV内部的构件,使模型更加接近真实状况。分别计算ROV在不同工况下的阻力、不同漂角下的横向力和转艏力矩以及添加体积力模型之后的螺旋桨流场状况,很好地模拟出ROV周围的流场,并与已有的试验数据进行对比。结果验证了CFD水动力仿真的可行性和准确性,并还可预测ROV在螺旋桨作用下的进速等,对ROV设计具有实际的参考价值和指导意义。     

Shared autonomous electric vehicle (SAEV) operations across the Austin,Texas network with charging infrastructure decisions

Shared autonomous vehicles, or SAVs, have attracted significant public and private interest because of their opportunity to simplify vehicle access, avoid parking costs, reduce fleet size, and, ultimately, save many travelers time and money. One way to extend these benefits is through an electric vehicle (EV) fleet. EVs are especially suited for this heavy usage due to their lower energy costs and reduced maintenance needs. As the price of EV batteries continues to fall, charging facilities become more convenient, and renewable energy sources grow in market share, EVs will become more economically and environmentally competitive with conventionally fueled vehicles. EVs are limited by their distance range and charge times, so these are important factors when considering operations of a large, electric SAV (SAEV) fleet.This study simulated performance characteristics of SAEV fleets serving travelers across the Austin, Texas 6-county region. The simulation works in sync with the agent-based simulator MATSim, with SAEV modeling as a new mode. Charging stations are placed, as needed, to serve all trips requested (under 75 km or 47 miles in length) over 30 days of initial model runs. Simulation of distinctive fleet sizes requiring different charge times and exhibiting different ranges, suggests that the number of station locations depends almost wholly on vehicle range. Reducing charge times does lower fleet response times (to trip requests), but increasing fleet size improves response times the most. Increasing range above 175 km (109 miles) does not appear to improve response times for this region and trips originating in the urban core are served the quickest. Unoccupied travel accounted for 19.6% of SAEV mileage on average, with driving to charging stations accounting for 31.5% of this empty-vehicle mileage. This study found that there appears to be a limit on how much response time can be improved through decreasing charge times or increasing vehicle range.     

Incorporating the extended theory of planned behavior in a school travel mode choice model: a case study of Shaoxing,China

Travel to and from school can have social, economic, and environmental implications for students and their parents. Therefore, understanding school travel mode choice behavior is essential to find policy-oriented approaches to optimizing school travel mode share. Recent research suggests that psychological factors of parents play a significant role in school travel mode choice behavior and the Multiple Indicators and Multiple Causes (MIMIC) model has been used to test the effect of psychological constructs on mode choice behavior. However, little research has used a systematic framework of behavioral theory to organize these psychological factors and investigate their internal relationships. This paper proposes an extended theory of planned behavior (ETPB) to delve into the psychological factors caused by the effects of adults’ cognition and behavioral habits and explores the factors’ relationship paradigm. A theoretical framework of travel mode choice behavior for students in China is constructed. We established the MIMIC model that accommodates latent variables from ETPB. We found that not all the psychological latent variables have significant effects on school travel mode choice behavior, but habit can play an essential role. The results provide theoretical support for demand policies for school travel.     

A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts.