废弃水泥混凝土路面板在路面基层中的再生利用

以现行交通行业规范为基础,通过与非再生集料的技术指标和水泥稳定基层混合料的路用性能对比,分析了废弃水泥混凝土路面板再生集料的技术指标,研究了水泥稳定再生集料的路用性能,铺筑了以水泥稳定再生集料为路面基层的试验段,并对再生集料的生产与使用提出了建议。研究结果表明,再生集料的技术指标能够满足规范的技术要求,水泥稳定再生集料具有良好的路用性能。无论在技术上还是实践上,废弃水泥混凝土路面板在半刚性基层中的再生利用都是可行的,从而为废弃路面水泥混凝土的重新利用开辟了有效途径。     

钢-轻骨料混凝土简支组合梁承载及变形能力研究

为了确定轻骨料混凝土组合梁的性能,以对称集中荷载为加载方式,同时考虑栓钉间距、钢梁尺寸等影响组合梁承载及变形能力的因素,研究了钢-轻骨料混凝土组合梁结构的承载及变形能力。根据剪切滑移的挠曲线方程,提出组合梁在集中荷载作用下跨中挠度的简化计算公式,并选用ANSYS软件进行了有限元对比模拟分析,计算结果吻合良好。算例表明,轻骨料混凝土组合梁相比于相同尺寸的普通混凝土组合梁,应力值偏小5%左右,跨中挠度偏大10%左右,钢-轻骨料混凝土组合梁承载力及变形能力可满足实际应用,同时验证了计算公式应用的可行性。     

不同加载方式下土石混合体抗压强度的规律性研究

土石混合体的非均匀性决定了其在等应力(柔性)以及等位移(刚性)两种加载方式下的力学性能的不同。基于CDEM软件及块石随机生成算法,分别采用等应力和等位移两种加载方式,对土石混合体的单轴压缩进行了数值分析,得到了不同加载方式下土石混合体单轴抗压强度随含石率的变化曲线。结果表明:1)土石混合体等应力加载的抗压强度较等位移加载的抗压强度低,且随着含石率的增加,两者差异逐渐增大;2)两种加载方式下,土石混合体的单轴抗压强度随着含石率的增加而增加,且含石率超过30%后强度增加速率加快;3)随着含石率的增加,土石混合体的宏观应力应变曲线呈现强化趋势。     

采用SSC分析沥青稳定碎石级配组成与高温稳定性的关系

为判别沥青稳定碎石基层级配组成与高温稳定性之间的联系,采用骨架接触度SSC(stone-on-stone contact)来评价粗集料之间相互接触的密实程度,通过大量实验得出SSC与动稳定度之间的具体关系,为沥青稳定碎石基层配合比设计提供指导。     

旧水泥混凝土再生集料作水稳基层路用性能改善研究

旧水泥混凝土再生集料改善主要解决再生集料吸水率问题。对再生集料的基本性能研究分为普通再生集料和球磨再生集料。水稳再生集料的抗压强度试验包括击实试验和无侧限抗压强度试验。水泥稳定再生集料的干燥收缩率是评价结合料耐久性的一个重要指标。     

膨胀剂及纤维对水泥稳定碎石干缩性能的影响

对掺加膨胀剂、聚丙烯纤维的水泥稳定碎石和不掺加任何添加剂的水泥稳定碎石三种类型材料进行了干缩性能的试验,通过对试验结果的比较分析及对掺加膨胀剂与掺加聚丙烯纤维改善水泥稳定碎石干缩开裂性能不同作用机理的研究,得到如下研究结果:掺加膨胀剂比掺加聚丙烯纤维对水泥稳定碎石干缩抗裂性能的改善效果更好,且累计失水率值对膨胀剂水泥稳定碎石干缩抗裂性能的改善影响很大.     

梁体混凝土静力受压弹性模量影响因素分析

简支预制梁在铁路建设中被广泛运用,而梁体混凝土弹性模量是保证梁体质量的关键因素之一。经过多次配合比和实际操作试验,得出:通过控制梁体混凝土的骨料压碎值、砂率、粉煤灰掺量和使用成熟的施工工艺,可有效保证并提高混凝土弹性模量。对提高简支预制梁梁体的工作性能和力学性能具有参考价值。     

Modeling Car Ownership in Turkey Using Fuzzy Regression

Abstract

This article develops a model which can be used to determine car ownership in Turkey. Because of the lack of disaggregated data, the model is based on aggregated data. As owning a car is mainly affected by economic, social and demographic factors, the car ownership model has a multi-variable form. In order to explain the effects of these factors on car ownership in Turkey, a fuzzy multiple-regression model is used. The major reason for applying fuzzy regression is to overcome the intercorrelation problem associated with the independent variables. In this study, the urbanization rate, average family size, gross national product per capita, average car cost, gasoline price and total length of roads are selected as independent variables. The results show that, by applying a multi-variable approach to possibilistic regression, the model provides not only a crisp output but also an output range for car ownership in Turkey between 1970 and 2000.     

Using kinematic driving data to detect sleep apnea treatment adherence

People spend a significant amount of time behind the wheel of a car. Recent advances in data collection facilitate continuously monitoring this behavior. Previous work demonstrates the importance of this data in driving safety but does not extended beyond the driving domain. One potential extension of this data is to identify driver states related to health conditions such as obstructive sleep apnea (OSA). We collected driving data and medication adherence from a sample of 75 OSA patients over 3.5 months. We converted speed and acceleration behaviors to symbols using symbolic aggregate approximation and converted these symbols to pattern frequencies using a sliding window. The resulting frequency data was matched with treatment adherence information. A random forest model was trained on the data and evaluated using a held-aside test dataset. The random forest model detects lapses in treatment adherence. An assessment of variable importance suggests that the important patterns of driving in classification correspond to route decisions and patterns that may be associated with drowsy driving. The success of this approach suggests driving data may be valuable for evaluating new treatments, analyzing side effects of medications, and that the approach may benefit other drowsiness detection algorithms.     

A network‐based dynamic air traffic flow model for short‐term en route traffic prediction

This paper presents a dynamic network‐based approach for short‐term air traffic flow prediction in en route airspace. A dynamic network characterizing both the topological structure of airspace and the dynamics of air traffic flow is developed, based on which the continuity equation in fluid mechanics is adopted to describe the continuous behaviour of the en route traffic. Building on the network‐based continuity equation, the space division concept in cell transmission model is introduced to discretize the proposed model both in space and time. The model parameters are sequentially updated based on the statistical properties of the recent radar data and the new predicting results. The proposed method is applied to a real data set from Shanghai Area Control Center for the short‐term air traffic flow prediction both at flight path and en route sector level. The analysis of the case study shows that the developed method can characterize well the dynamics of the en route traffic flow, thereby providing satisfactory prediction results with appropriate uncertainty limits. The mean relative prediction errors are less than 0.10 and 0.14, and the absolute errors fall in the range of 0 to 1 and 0 to 3 in more than 95% time intervals respectively, for the flight path and en route sector level. Copyright © 2017 John Wiley & Sons, Ltd.