Using GPS-data to determine optimum electric vehicle ranges: A Michigan case study

Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation.     

Are French millenials less car-oriented? Literature review and empirical findings

Generation effects play a key role in shaping long-term trends in travel behaviors. Though cohorts born until the 1970s have been increasingly car-focused, a reversal of this trend was noticed among the millenials. Determining whether this break-in-trend resulted from changes in living conditions and economic difficulties, or demonstrates a shift in attitudes away from the car, is critical to future travel trends. We bring a contribution to this debate in the French context, through a literature review followed by empirical findings, using the French Base of Local Household Travel Surveys. Through age-cohort analysis, we find evidence of changing travel patterns among the millenials, taking the form of a shift from driving to transit, along with a decline of car ownership. However, travel attitudes of the millenials play little role, as they do not differ substantially from their elders. Besides, we show that generation effects disappear once a large number of structural factors are controlled for. It looks like the main driver of change in travel behaviors comes from a shift in residential patterns, in relation with longer studies and a delayed entrance into the workforce, and possibly because of increasing work pressure, degraded transport conditions and changes in residential attitudes and desired lifestyles. In the end, these assumptions should be further explored, along with complementary research tracks, including the role of economic factors, the effects of learning experience, as well as heterogeneity in travel patterns, in relation with issues of social and spatial equity.     

不同数值积分方式对海洋结构物疲劳裂纹扩展模拟结果的影响

海洋结构物的疲劳寿命预报是当前的研究热点,文章根据第二作者率领的课题组提出的海洋结构物疲劳寿命预报统一方法比较了疲劳裂纹扩展模拟的三种数值积分方法：逐周数值积分法、△N积分法和△a积分法,并分析了每种方法的适用条件。随后,以中心表面裂纹承受单向交变拉伸载荷的平板为例,分别运用三种方法计算了裂纹扩展寿命和最终裂纹尺寸。同时,研究了△N和△a取值不同对结果的影响。最后,综合考虑计算耗时和计算结果精度,给出了△N积分法和△a积分法的建议值,即△N/N≤1.0%,△a≤0.1 mm。     

A stochastic optimization approach for the selection of reflective cracking mitigation techniques

PurposeIn Hot Mix Asphalt (HMA) overlays, the existing cracks in the underlying pavements can propagate upward to the new added overlay and may cause Reflective Cracks (RC). These cracks allow water infiltration to the underlying layers and causes further moisture damage as well as weakening the unbound layers. Over the years, several methods have been developed for mitigating the RCs. This study aims to investigate the current reflective cracking mitigation methods and develop a methodology for the selection of appropriate mitigation technique. The developed model is then applied to a case study in the state of Florida.MethodTo accomplish this goal, a nationwide literature review was conducted to better understand the current in practice methods in the United States. Moreover, a life cycle cost analysis (LCCA) in five different road types was performed to find the annuity of roadway rehabilitation for each of the mitigation methods. The uncertainty in the LCCA results is represented using Exploratory Modeling and Analysis (EMA) method. Then through a Multi Criteria Decision Making (MCDM) model, a stochastic optimization model was developed to find the appropriate reflective cracking mitigation solution under Florida’s climate and road conditions, based on different cost and performance weights.ResultsBased on the available data for the state of Florida, the LCCA results indicate that the annuity of maintaining the roadway with Fabrics and ISAC are lower compared to other methods. However, the results of stochastic optimization model reveal that while looking at the performance and cost at the same time, different methods would be more feasible. For instance, while the cost of the used method does not matter at all and only performance matters, STRATA® is more probable to be the appropriate mitigation technique. The findings of this research are critical for decision makers to better understand the most cost-effective mitigation technique in different conditions.     

Development of behavioral context addressable loggers in the shell for travel-activity analysis

This study attempts to develop a small, portable travel-activity measuring instrument that requires no entry from respondents. Conventional surveys have collected identification information such as facility type, transport mode, and activity content through the operation of instruments, questionnaires, etc. However, these complicated surveys burden the respondents and rely on their memory, often leading to recording omissions or incorrect records. We propose a method for estimating behavioral contexts using BCALs (Behavioral Context Addressable Loggers in the Shell), a wearable, behavioral context information-measuring instrument, for re-estimating label information such as facility type and transport mode from ecological and environmental sensors based on learning models. The numerical values observed by these sensors differed greatly among locations or means of transportation, revealing the high possibility of automatic identification of locations and means of transportation using BCALs.     

Multi-objective optimization for asphalt pavement maintenance plans at project level: Integrating performance,cost and environment

Traditionally, asphalt pavement maintenance mainly considers pavement performance and cost and largely ignores the environment while substantial amount of environmental burdens are released in the process. In this study, a multi-objective optimization model was developed integrating the three elements in order to optimize the asphalt pavement maintenance plans at the project level. Pavement performance element was decided as the multiplier of pavement serviceability index and traffic volume. Cost element was represented by the net present value, including components of agency cost, vehicle operation cost and salvage value. Environmental element, integrating energy consumption, global warming potential, acidification potential and respiratory effects potential, was measured by the life cycle assessment model. A hypothetic asphalt pavement maintenance case study was conducted using the developed multi-objective optimization model and harvested 103 sets of feasible combinations of maintenance plans, each of which is non-dominated by the others. Trade-offs analysis was performed among the three objectives and visualized in both two- and three-dimension forms. It is found there is an opportunity of reducing the cost and environmental impacts to 80.3% and 77.8% and increasing the pavement performance to 146.6% compared to the base case. However, they are mutually compromised and cannot be reached simultaneously. The developed model reveals the quantitatively interactive relationship of the three objectives and helps optimize the asphalt pavement maintenance plans.     

Environmental impacts of public transport systems using real-time control method

Public Transport (PT) systems rely more and more on online information extracted from both operator’s intelligent equipment and user’s smartphone applications. This allows for a better fit between supply and demand of the multimodal PT system, especially through the use of PT real-time control actions/tactics. In doing so there is also an opportunity to consider environmental-related issues to approach energy saving and reduced pollution. This study investigates and analyses the benefits of using real-time PT operational tactics in reducing the undesirable environmental impacts. A tactic-based control (TBC) optimization model is used to minimize total passenger travel time and maximize direct transfers (without waiting). The model consists of a control policy built upon a combination of three tactics: holding, skip-stops, and boarding limit. The environmental-related measure is the global warming potential (GWP) using the life cycle assessment technique. The methodology developed is applied to a real life case study in Auckland, New Zealand. Results show that TBC could reduce the GWP by means of reduction of total passenger travel times and vehicle travel cycle time. That is, the TBC model results in a 5.6% reduction in total GWP per day compared with an existing no-tactic scenario. This study supports the use of real-time control actions to maintain a reliable PT service, reducing greenhouse gas emissions and subsequently moving towards greener PT systems.     

Vehicle electrification in a developing country: Status and issue,from a well-to-wheel perspective

The increase of public attention, scientific research and political interest in environmental problems associated with transportation has provided the motivation for re-invention of electric vehicles. However the usage of grid-dependent EVs with a high-carbon electricity grid might produce more damage to the environment. This study aims to provide an environmental impact comparison of ICEVs, HEVs and EVs during their usage cycle, by modeling their energy consumption (electricity or fuel) and the supply chains of the supplied energy, (well-to-wheel) based on a life cycle assessment. The results show that running EVs with the existing mixed sources of electrical energy produce larger impacts on the environment 60% of the time; when compared to HEVs. When compared to ICEVs, EVs produce a larger environmental impact on 7 out of 15 environmental impact categories. Overall the environmental impacts of EVs are substantial based on the well-to-wheel analysis. It will continue to be so if no change is made to the methods of electricity generation in the near future. Given that the environmental profile of EVs is linked with the existing national electricity generation mix, the national electricity supply must be made cleaner before the electrification of the urban transport system.     

高速铁路生命周期碳排放计算方法

基于生命周期评价理论,对高速铁路生命周期二氧化碳排放计算的边界进行界定,将高速铁路的生命周期划分为基础设施建造、运营和回收3个阶段;根据对各阶段高速铁路二氧化碳排放清单的分析,分别给出各个阶段二氧化碳排放的计算式;通过算例分析了高速铁路在建造和运营阶段碳排放的特点.分析和数值计算结果表明,虽然在高速铁路基础设施建设过程中由于大量建设材料和高能耗施工机械的使用,使得高速铁路建造阶段的二氧化碳排放量相对较多;但是,由于高速铁路具有节约能源、节省土地和货运增量替代效应等特点,使得高速铁路进入运营阶段后二氧化碳的排放量大幅度减少,即从生命周期全过程来看,高速铁路具有较好的减排效果.     

“自立号”自升式平台延长使用寿命的评估

渤海“自立号”是一座典型的沉垫基础自升式平台,平台寿命已经超过30年,为保证平台未来安全运行,需要对其进行剩余寿命的评估。评估内容包括考虑结构腐蚀的结构强度评估,以及对平台历史和延寿期的疲劳损伤累积评估。本文简要介绍了“自立号”平台延寿的评估过程和内容,供类似工程参考。