沥青玛蹄脂混合料的高温性能影响因素分析

沥青玛蹄脂混合料作为良好的钢桥面铺装层材料,其高温性能一直是关注的焦点,本文基于室内车辙试验研究了其高温性能影响因素,重点分析了荷载和温度、拌合时间及加铺SMA对沥青玛蹄脂混合料的高温性能指标动稳定度的影响规律,为今后玛蹄脂混合料的路用实践提供了借鉴.     

低阻通风船体的远程控制测试平台开发（英文）

This paper addresses the development and testing of a remotely controlled boat platform with an innovative air-ventilated hull. The application of air cavities on the underside of ship hulls is a promising means for reducing hydrodynamic drag and pollutant emissions and increasing marine transportation efficiency. Despite this concept’s potential, design optimization and high-performance operation of novel air-cavity ships remain a challenging problem. Hull construction and sensor instrumentation of the model-scale air-cavity boat is described in the paper. The modular structure of the hull allows for easy modifications, and an electric propulsion unit enables self-propelled operation. The boat is controlled remotely via a radio transmission system. Results of initial tests are reported, including thrust, speed, and airflow rate in several loading conditions. The constructed platform can be used for optimizing air-cavity systems and testing other innovative hull designs. This system can be also developed into a high-performance unmanned boat.     

Lagrangian flow in the California Undercurrent, an observation and model comparison

During the period 1992–1998, 38 isobaric RAFOS floats were deployed to sample the subsurface flow of the California Undercurrent. The deployments, released over the California continental slope west of San Francisco, have sampled robust year-round poleward subsurface flow associated with the Undercurrent most seasons and the combined inshore current and Undercurrent in winter. Two other types of flow have been seen: a region of weak flow with little net displacement just west of the California Undercurrent, and an active westward propagating eddy field. This eddy field appears to be the primary mechanism for moving floats from the Undercurrent into the ocean interior. The observations and statistics from the RAFOS floats are compared with Lagrangian estimates of particles tracked in a global high resolution ocean simulation in order to evaluate the fidelity of the model along an eastern boundary. The results show that the model reproduces the general character of the flow reasonably well, but underestimates both the mean and eddy energies by a substantial amount.     

Analysis of factors that may be essential in the decision to fly on fully autonomous passenger airliners

This research investigates factors that influence opinion in the decision to fly on fully autonomous passenger airliners primarily from the perspective of aviation and technology professionals. Bayesian statistical inference and a two‐level fractional factorial survey are used to sample passengers' views on fully autonomous airliners. Eight trust, safety, and cost factors are incorporated into a vignette set in the future. Factors include automation levels, safety records, liability guarantees, airline integrity, and service disruptions. Dependent variables exist in five post‐vignette questions and essentially ask “Would you” or “Would you not” be willing to fly on a fully autonomous airliner? Sixteen versions of the vignette, each with unique trust, safety, and cost levels, present varying (unknown) degrees of influence to the survey respondents. For every demographic, the research shows a 99% statistically significant difference between the “prior” and “posterior” sampled population proportions willing to fly. The most significant positive influence involves integrity characteristics of the airline, while the most negative influence relates to life insurance liability guarantees. Research from 2003 suggested that this mode of travel would be acceptable to only 10.5% of respondents. When the 2003 research is used as a Bayesian prior probability, the resulting posterior probability for the demographics sampled can be modeled as a beta distribution, indicating 95% probability that the sampled proportion of the population willing to fly is between 33.2% and 36.4%. After adjusting for age and profession demographics to match the US population, the 95% probability bounds on the proportion willing to fly are 31.35% and 34.15%. Copyright © 2015 John Wiley & Sons, Ltd.     

Modelling and Analysis of Turning Motion of a Subsurface Mapping AUV with Split-Hull Design

There is much need for autonomous underwater vehicles (AUVs) for inspection and mapping purposes. Most conventional AUVs use torpedo-shaped single-rigid hull, b...     

台北公共交通月及无车日活动回顾与展望

台北国际无车日自2002年起举办了5次,由最早的骑自行车活动扩大至包含“走路上学日”与“公共交通月”丰富多彩的系列活动,渐渐获得民众认同。无车日活动的目标是通过活动的倡导和社会参与来改变民众使用交通工具的行为,潜移默化的效应可促使形成可持续交通政策,当可持续交通政策与基础设施建设落实后又可具体改变交通环境,形成良性的循环机制。首先说明了“无车日”的由来,并回顾台北都会区过去5年来举行无车日系列活动的内容与经验,同时基于活动的发展与成果归纳出无车日活动的成功要素,最后提出未来活动将扩大举办的内容、方式与展望,以期能为其他城市作参考。     

Assessment of factors associated with travel time reliability and prediction: an empirical analysis using probabilistic reasoning approach

Significant efforts have been made in modeling a travel time distribution and establishing measures of travel time reliability (TTR). However, the literature on evaluating the factors affecting TTR is not well established. Accordingly, this paper presents an empirical analysis to determine potential factors that are associated with TTR. This study mainly applies the Bayesian Networks model to assess the probabilistic association between road geometry, traffic data, and TTR. The results from this model reveal that land use characteristics, intersection factors, and posted speed limits are directly associated with TTR. Evaluating the strength of the association between TTR and the directly related variables, the log odds ratio analysis indicates that the land use factor has the highest impact (0.83) followed by the intersection factor (0.57). The findings from this study can provide valuable resources to planners and traffic operators in their decision-making to improve TTR with quantitative evidence.     

山区峡谷非均匀风场下大跨度斜拉桥静风稳定性分析

为研究山区峡谷地形下非均匀风场对大跨度桥梁静风稳定性的影响,以一座跨越典型山区峡谷地形的大跨度斜拉桥为工程背景,首先,采用计算流体动力学（CFD）软件Fluent对桥址区地形的风场特性进行分析,计算出沿主梁方向的非均匀风速和非均匀风攻角分布;然后,采用ANSYS APDL技术实现能考虑非均匀风速和非均匀风攻角下大桥静风稳定性的非线性分析方法。在此基础上,综合考察非均匀风攻角分布、非均匀风速分布、非均匀风速非均匀风攻角分布等风场条件对大桥静风稳定性的影响,分析各工况下主梁的静风变形与跨中处拉索刚度变化。研究结果表明：与均匀风场条件下的静风响应不同,非均匀风攻角或非均匀风速下主梁静风响应最大值点位于风荷载峰值点与跨中之间,在针对非均匀风场下大桥的静风稳定性分析时,应更注重静风响应最大值点而不是跨中处;非均匀风攻角下大桥的静风失稳临界风速要远低于均匀风攻角的静风失稳临界风速,且其静风稳定性能主要受最大风攻角而不是主跨部分非均匀风攻角的平均值来控制;非均匀风速下大桥的静风失稳临界风速主要由主跨部分的风速平均值和最大值共同影响;主梁的竖向位移和扭转角形状主要由风攻角因素来控制,而横向位移的变化规律相对较独立,其形状基本上以跨中线对称,且其值主要由风速因素来决定。     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

The Alternative Motor Fuels Act, alternative-fuel vehicles, and greenhouse gas emissions

The corporate average fuel economy (CAFE) standard is the major policy tool to improve the fleet average miles per gallon of automobile manufacturers in the US. The Alternative Motor Fuels Act (AMFA) provides special treatment in calculating the fuel economy of alternative-fuel vehicles to give manufacturers CAFE incentives to produce more alternative-fuel vehicles. AMFA has as its goals an increase in the production of alternative-fuel vehicles and a decrease in gasoline consumption and greenhouse gas emissions. This paper examines theoretically the effects of the program set up under AMFA. It finds that, under some conditions, this program may actually increase the production of fuel-inefficient gasoline vehicles, gasoline consumption and greenhouse gas emissions.