公路工程沥青路面施工、养护技术与质量控制分析

为有效保证公路工程沥青路面质量,对常见的公路工程沥青路面施工与养护技术进行分析,包括混合料配比技术、摊铺技术、碾压技术、接缝处理技术等。在此基础上,分析公路工程沥青路面施工与养护质量控制措施,包括重视材料与设备管控、加强技术监督与管理、加大设施投入力度等。建议综合运用相关技术与管理手段,以确保公路工程沥青路面质量的可控性和可持续性。     

市政道路桥梁施工中现场施工技术的应用与管理

为有效提高市政道路桥梁工程质量与施工过程的安全性,对现场施工技术的应用与施工管理措施进行研究。首先,总结市政道路桥梁工程的特点;其次,对市政道路桥梁现场施工技术进行分析,包括软土地基施工技术、翻模施工技术、混凝土施工技术、铺装连锁块施工技术、排水施工技术等;最后,提出市政道路桥梁现场施工管理对策,以期为市政道路桥梁施工与管理提供参考。     

技术进步与交通发展

交通运输与技术发展的关系问题,是交通运输系统工程问题,是技术进步与社会经济发展的重大课题之一,也是交通技术经济学科需要研究的问题。技术革命推动交通运输发展,极大提升了交通运输的技术效率,交通运输发展史就是交通运输技术变迁史。本文从宏观上讨论交通运输与技术发展的一般关系,分析技术进步对交通发展的影响和作用,讨论交通运输的技术应用、技术效率及新技术对未来交通发展影响。第四次工业革命正在深度改变全球产业链和供应链的发展,重要的是,如何利用新技术为交通运输发展服务,最大限度的满足交通运输用户的需求。忽视交通运输效率和质量的技术,再高再新也没有使用价值。     

沥青路面维修与养护中的现场冷再生技术

针对目前我国高速公路维修与养护的现状,指出了利用冷再生技术的必要性与重要意义,同时详细介绍了现场冷再生技术的施工工艺与注意事项,并对我国发展冷再生技术提出了建议.     

河西地区盐渍土路基综合处治技术体系与施工质量控制研究

通过对河西地区七瓜项目沿线盐渍土类型、分布特点、损坏特征及盐胀机理的分析,按照"防盐、隔盐与消胀"为一体处治思路,首次大面积采用反渗透脱盐净水技术、闷料及非盐砂砾土填料、"两布一膜"与未筛分碎石阻断层、消胀槽、桥涵台背回填、防排水及边坡防护等技术措施,提出了不同技术措施的作用机理、技术特点与施工质量控制要点,建立了河西地区盐渍土路基综合处治技术体系,为后期类似工程提供重要理论依据与技术支撑,具有积极行业示范效益与推广价值。     

汽车新节能技术的展望

文章介绍了目前国际上几种比较新颖的节能技术,诸如能量收集与储存新技术、汽主行驶中的能量回收再生技术,电容器和电池二次电池能量回收再生技术、飞轮电动汽车的能量回收与利用技术等等。     

植筋技术在桥梁加固工程中的应用探讨

文章通过对植筋技术原理与特点的了解,以某大桥桥梁加固工程为例,探讨了植筋技术在桥梁加固工程中的应用,并对桥梁加固工程中植筋技术的详细施工工艺进行阐述,通过理论与实践的结合,强化植筋技术桥梁加固工程中的应用。     

江苏省重点营运车辆技术管理现状研究

近年来,江苏省内发生多起道路运输事故。调查表明,事故发生与涉事车辆的安全技术状况均有一定的直接关系。因此,对于交通运输管理部门来说,加强道路运输企业安全监管,督促企业认真执行道路运输车辆技术管理各项标准、规范和制度就显得尤为重要。本文从车辆技术状况抽检情况、车辆检验检测信息系统应用情况、事故发生与车辆技术状况抽检对比分析、车辆技术状况管理情况四个方面对2021年度江苏省车辆技术检测情况进行分析,归纳出车辆技术状况检测与管理中存在的主要问题,并提出相应的管理措施和发展建议。     

国内外高钢级管线钢的开发与应用

简述了高钢级管线钢的冶炼连铸技术、轧制技术和制管技术以及国内外高钢级管线钢的开发与应用现状及发展趋势,探讨了国内的管线钢与国外的差距以及进一步发展的方向。     

公路桥梁施工中现浇箱梁施工技术分析

为进一步提高公路桥梁工程施工效率与质量,对公路桥梁施工中现浇箱梁施工技术进行分析。首先,阐释现浇箱梁施工技术的优势;其次,指出现浇箱梁施工技术的不足;最后,从支架搭设与预压、模板安装、钢筋安装与绑扎、混凝土浇筑、预应力施工等方面分析公路桥梁施工中现浇箱梁施工技术要点,希望为相关工作人员提供参考。     

油气管道内腐蚀检测技术的现状与发展趋势

综述了油气管道内腐蚀检测技术的发展现状,介绍了目前较为成熟、应用较为普遍的漏磁检测、超声波检测、涡流检测、射线检测、基于光学原理的无损检测5种内检测技术的原理,并分析了各种技术的优缺点.结合近年来在油气管道内腐蚀检测方面的一些经验,提出了目前管道内腐蚀检测技术存在的问题,并指出了管道内腐蚀检测技术的发展趋势.     

Heavy-duty trucking and the energy efficiency paradox: Evidence from focus groups and interviews

Theory suggests that profit maximizing firms have an incentive to incorporate cost-effective technologies into their products. However, simple net present value calculations comparing upfront costs of fuel-saving technologies to future savings suggest this is not always the case. This puzzle is commonly referred to as the “energy efficiency paradox.” A growing number of empirical studies examine why households may under-invest in energy efficiency. Fewer studies examine similar undervaluation by businesses. We explore investment decisions within the heavy-duty trucking sector for fuel-saving technologies via focus groups and interviews to gain insight into what factors might explain apparent underinvestment in fuel-saving technologies. We find some evidence that market failures related to lack of information about technology performance and network externalities contribute to slow adoption of some technologies. However, information about new technologies for tractors seems to generate limited spillovers. There is also some evidence of split incentives between owners and drivers, though companies have invested in a variety of technologies and approaches in an attempt to address these effects. Other factors important in trucking investment decisions that are not classic market failures include tradeoffs between fuel economy and other valued truck attributes, as well as uncertainty and risk associated with new technologies if decision-makers are loss averse.     

Experimental Economics and choice in transportation: Incentives and context

This paper reviews the preconditions for successful applications of Experimental Economics methods to research on transportation problems, as new transportation and research technologies emerge. We argue that the application of properly designed incentives, the hallmark of Experimental Economics, provides a high degree of experimental control, leading to internal validity and incentive compatibility. Both of these are essential for ensuring that findings generalize to contexts outside the immediate application. New technologies, such as virtual reality simulators, can generate external validity for the experiments by providing realistic contexts. GPS and other tracking technologies, as well as smart phones, smart cards and connected vehicle technologies can allow detailed observations on actions and real-time interactions with drivers in field experiments. Proper application of these new technologies in research requires an understanding of how to maintain a high level of internal validity and incentive compatibility as external validity is increased. In this review of past applications of Experimental Economics to transportation we focus on their success in achieving external and internal validity.     

天然气脱硫工艺的研究与发展

文中介绍了几种常用的脱硫工艺,如醇胺法、Sulfatreat法、低温甲醇洗技术等,指出各方法的优势及目前存在的问题,提出了今后天然气脱硫工艺发展的趋势。认为应在成熟的天然气脱硫方法的基础上进一步改进,实现高效节能。指出膜吸收是膜基气体分离与传统的物理吸附、化学吸收、低温精馏、深冷结合起来的新型分离技术。与常规工艺相比具有明显的优势,是今后天然气脱硫技术研究发展的新方向。     

Are we ready to embrace connected and self-driving vehicles? A case study of Texans

While connected, highly automated, and autonomous vehicles (CAVs) will eventually hit the roads, their success and market penetration rates depend largely on public opinions regarding benefits, concerns, and adoption of these technologies. Additionally, the introduction of these technologies is accompanied by uncertainties in their effects on the carsharing market and land use patterns, and raises the need for tolling policies to appease the travel demand induced due to the increased convenience. To these ends, this study surveyed 1088 respondents across Texas to understand their opinions about smart vehicle technologies and related decisions. The key summary statistics indicate that Texans are willing to pay (WTP) $2910, $4607, $7589, and $127 for Level 2, Level 3, and Level 4 automation and connectivity, respectively, on average. Moreover, affordability and equipment failure are Texans’ top two concerns regarding AVs. This study also estimates interval regression and ordered probit models to understand the multivariate correlation between explanatory variables, such as demographics, built-environment attributes, travel patterns, and crash histories, and response variables, including willingness to pay for CAV technologies, adoption rates of shared AVs at different pricing points, home location shift decisions, adoption timing of automation technologies, and opinions about various tolling policies. The practically significant relationships indicate that more experienced licensed drivers and older people associate lower WTP values with all new vehicle technologies. Such parameter estimates help not only in forecasting long-term adoption of CAV technologies, but also help transportation planners in understanding the characteristics of regions with high or low future-year CAV adoption levels, and subsequently, develop smart strategies in respective regions.     

Consumer preferences and willingness to pay for advanced vehicle technology options and fuel types

The automotive industry is witnessing a revolution with the advent of advanced vehicular technologies, smart vehicle options, and fuel alternatives. However, there is very limited research on consumer preferences for such advanced vehicular technologies. The deployment and penetration of advanced vehicular technologies in the marketplace, and planning for possible market adoption scenarios, calls for the collection and analysis of consumer preference data related to these emerging technologies. This study aims to address this need, offering a detailed analysis of consumer preference for alternative fuel types and technology options using data collected in stated choice experiments conducted on a sample of consumers from six metropolitan cities in South Korea. The results indicate that there is considerable heterogeneity in consumer preferences for various smart technology options such as wireless internet, vehicle connectivity, and voice command features, but relatively less heterogeneity in the preference for smart vehicle applications such as real-time traveler information on parking and traffic conditions.     

Analysis of Class 8 truck technologies for their fuel savings and economics

Non-electrification efficiency-improving technologies and powertrain technologies for reducing the heavy-duty truck fuel consumption are studied. The study indicates that improvements in engine efficiency, aerodynamic drag and rolling resistance will benefit fuel economy significantly over the day drive and over-the-road highway driving cycles; 6–13% in fuel savings can be expected from each technology. Hybridization can achieve fuel saving of 16% and is financially attractive for the day drive cycle. Compared to the baseline Class 8 conventional trucks, an improvement of 20–22% and 28–50% in fuel economy by 2020 can be expected using non-electrification efficiency-improving and a combination of non-electrification and hybrid technologies. Fuel economy improvements of a factor of four to five can be achieved by hybridizing the heavy-duty trucks used on ocean ports.     

Assessing public opinions of and interest in new vehicle technologies: An Austin perspective

Technological advances are bringing connected and autonomous vehicles (CAVs) to the ever-evolving transportation system. Anticipating public acceptance and adoption of these technologies is important. A recent internet-based survey polled 347 Austinites to understand their opinions on smart-car technologies and strategies. Results indicate that respondents perceive fewer crashes to be the primary benefit of autonomous vehicles (AVs), with equipment failure being their top concern. Their average willingness to pay (WTP) for adding full (Level 4) automation ($7253) appears to be much higher than that for adding partial (Level 3) automation ($3300) to their current vehicles.Ordered probit and other model specifications estimate the impact of demographics, built-environment variables, and travel characteristics on Austinites’ WTP for adding various automation technologies and connectivity to their current and coming vehicles. It also estimates adoption rates of shared autonomous vehicles (SAVs) under different pricing scenarios ($1, $2, and $3 per mile), choice dependence on friends’ and neighbors’ adoption rates, and home-location decisions after AVs and SAVs become a common mode of transport. Higher-income, technology-savvy males, who live in urban areas, and those who have experienced more crashes have a greater interest in and higher WTP for the new technologies, with less dependence on others’ adoption rates. Such behavioral models are useful to simulate long-term adoption of CAV technologies under different vehicle pricing and demographic scenarios. These results can be used to develop smarter transportation systems for more efficient and sustainable travel.     

井筒与输油管线的物理防蜡技术综述

文中通过对大量相关文献的分析总结,对目前各大油田常用的物理防蜡技术的发展历史、工作原理、适用环境以及使用条件进行了归纳、介绍,并对这些防蜡技术在实验室中的实验结果和近年来油田使用后的效果进行了分析总结.这些防蜡技术的分类介绍为各大油田在实践中面临不同采油条件和原油组分时筛选防蜡方法提供了理论性的依据,也为防蜡技术的进一...     

Development and evaluation of a hybrid travel time forecasting model

The purpose of this paper is to develop and evaluate a hybrid travel time forecasting model with geographic information systems (GIS) technologies for predicting link travel times in congested road networks. In a separate study by You and Kim (cf. You, J., Kim, T.J., 1999b. In: Proceedings of the Third Bi-Annual Conference of the Eastern Asia Society for Transportation Studies, 14–17 September, Taipei, Taiwan), a non-parametric regression model has been developed as a core forecasting algorithm to reduce computation time and increase forecasting accuracy. Using the core forecasting algorithm, a prototype hybrid forecasting model has been developed and tested by deploying GIS technologies in the following areas: (1) storing, retrieving, and displaying traffic data to assist in the forecasting procedures, (2) building road network data, and (3) integrating historical databases and road network data. This study shows that adopting GIS technologies in link travel time forecasting is efficient for achieving two goals: (1) reducing computational delay and (2) increasing forecasting accuracy.