基于岩体指标和掘进参数的TBM净掘进速率预测模型

净掘进速率是TBM施工速度的主要评价指标,与围岩物理力学性质、TBM掘进参数之间存在一定相关性。文章以兰州水源地建设工程输水隧洞双护盾TBM施工为背景,基于现场实测数据,选择岩石单轴抗压强度、抗拉强度、变形模量、泊松比、岩石耐磨性CAI值等岩体指标,以及刀盘推力和刀盘转速等掘进参数,进行TBM净掘进速率与有关影响参数之间的单因素相关性分析,得到相应拟合公式;基于TBM净掘进速率与岩体指标、掘进参数之间的相关性,利用多元非线性回归方法建立了TBM净掘进速率预测模型。通过将兰州水源地建设工程输水隧洞实测TBM净掘进速率和预测结果进行对比,验证了TBM净掘进速率预测模型的合理性。研究结果表明:(1)在复杂的多种地质条件下,TBM净掘进速率与岩石单轴抗压强度、抗拉强度、变形模量、岩石耐磨性CAI值、刀盘推力以及刀盘转速呈负相关关系,与泊松比呈正相关关系;(2)干湿状态对岩石耐磨性CAI值有一定影响,饱和状态下岩石耐磨性CAI值与TBM净掘进速率之间的相关性更显著;(3)建立的多元非线性回归预测模型,预测精度较高,可为相似地质条件下TBM净掘进速率估算提供参考。     

基于Bodner-Partom模型的水泥乳化沥青混合料黏弹塑压实特性

为揭示水泥乳化沥青混合料压实过程中的黏弹塑性变形特性及其变形机理,结合现场路面压路机的施工工艺参数,采用万能试验机压缩试验模拟该混合料的压实过程。针对试验循环荷载力学响应曲线变形特征,引入有效平均应力构建混合料压实变形的Bodner-Partom本构模型。通过对应变-时间的非线性拟合识别出该混合料的B-P模型参数值,进而揭示压实过程中混合料的黏弹塑性动态流变特性及变形机理。试验结果表明：压缩试验可充分反映混合料压实过程中的力学响应变形特性;随着循环荷载次数的增加,混合料塑性和黏塑性变形减小而弹性和黏弹性变形增大。据混合料复压阶段的黏塑性变形规律导出试样空隙率的计算式,进而获得有效平均应力随试样空隙率的变化规律。B-P本构模型分析结果表明：黏性参数η随荷载作用次数的增加而逐渐增大,说明混合料在压实过程中黏性增强;应变率敏感系数n₁基本保持不变,表明压实过程中混合料温度相对稳定;参数值Z,D₀随荷载作用次数的增加分别呈递增、递减的规律,前者显示随着混合料被进一步压实其非弹性变形抵抗力增大,进而导致塑性和黏塑性应变逐渐减小,后者显示塑性应变率减小,表明单次循环荷载下塑性变形占总变形量的比例逐渐减小。B-P模型参数值可准确表征水泥乳化沥青混合料与时间和荷载相关的黏弹塑性流变特性,重构后的B-P本构模型可有效揭示混合料压实过程中的黏弹塑性变形机理,可为深入研究其压实流变性能和路面压实工艺奠定基础。     

拼宽空心板桥荷载横向分布计算方法

为研究拼宽空心板桥荷载横向分布系数的计算方法,首先分别开展采用8,22 cm铺装层的空心板桥足尺模型荷载横向分布试验,接着开展采用刚性拼接结构的拼宽空心板桥足尺模型荷载横向分布试验,并将试验结果与既有铰接板法和刚接板法荷载横向分布系数的计算结果进行对比分析;最后讨论既有铰接板法和刚接板法的适用范围,进而提出了一种新的荷载横向分布系数计算方法,并探讨拼宽空心板桥的拼接结构刚度取值的合理范围。研究结果表明：既有铰接板法和刚接板法分别适用于计算铺装层厚度较小和较大的空心板桥荷载横向分布系数,但二者均无法考虑不同铺装层厚度对荷载横向分布的影响,为此提出了考虑铺装层厚度影响的荷载横向分布系数计算方法,相应的计算结果与试验结果的偏差仅为2.7%;对于采用刚性拼接结构的拼宽空心板桥,铰接板法或者刚接板法均无法正确地反映拼宽空心板桥的荷载横向分布规律,为此提出了考虑拼接结构刚度的拼宽空心板桥荷载横向分布系数计算方法,其中新旧桥板高错位布置的拼宽空心板桥拼接结构刚度为不考虑新桥铺装层厚度的刚度,该方法求得的荷载横向分布规律与试验结果的变化趋势一致,相应的计算结果与试验结果的最大偏差仅为5.4%。     

火灾高温下盾构隧道衬砌结构热力耦合模型试验

为研究火灾高温下盾构隧道衬砌结构的热力耦合行为,利用自主研制的温度加载设备和衬砌管环外压加载设备,分别设计并开展整环衬砌结构的无外压受热模型试验和热力耦合模型试验。试验使用不考虑接头效应的钢纤维混凝土匀质管片。首先,介绍2种试验设备的原理、主要构造和各类参数;在此基础上,针对模型试验过程进行细致的说明。然后,通过对衬砌管片结构形式的分析确定试验的火灾加载工况;详尽描述不同试验的相关结果,重点分析衬砌结构内表面各处温度场的变化过程、分布情况、管片的变形结果及破坏模式。研究结果表明：温度加载设备和衬砌管环外压加载设备能够较好的满足整环衬砌热力耦合研究的模型试验要求;试验初期底部管片的升温速率相对顶部管片有所滞后,但各部分间的温差数值随加热的持续进行会逐渐减小,衬砌结构内部能够形成稳定的温度场;无外力作用下匀质管片的破坏形式表现为沿幅宽方向的贯穿裂缝,各管片结构的裂缝发展路径存在差异;衬砌管片由于外压作用产生的压应变随温度的升高而减小;外压荷载对衬砌结构在高温下产生的膨胀变形存在抑制效果。研究结果可为盾构隧道整环衬砌结构热力耦合研究的进一步发展提供参考。     

薄壁墩墩顶拉力简化计算

针对薄壁墩、花瓶墩等结构,提出墩顶带拉杆的Y形墩模型,给出了墩顶拉力的简化计算公式。     

地埋式一体化污水处理系统在高速公路服务区的应用

针对高速公路污水量和水质的特点,设计采用地埋式一体化污水处理系统。通过实际应用和跟踪监测,该系统的应用可实现高速公路服务区污水的达标排放。     

多方式多类型交通分配模型(MMA)在收费型公路网中的应用研究

在对收费型公路运营模式进行研究的基础上,利用交通规划软件建立了基于广义费用的交通流量分配模型即多方式多类型交通分配模型,通过对模型参数的科学标定和网络的合理设置,得到各类车型在特定网络上的流量分配、路段饱和率以及通行费用,并对此模型的应用效果进行分析,最终为区域高速公路网规划、路段交通量预测提供依据。     

Comparative analysis of household car,motorcycle and bicycle ownership between Osaka metropolitan area,Japan and Kuala Lumpur,Malaysia

The interactions among different types of vehicle ownership including car, motorcycle and bicycle are examined by developing simultaneous vehicle ownership models in this study. Large scale person trip survey data for Osaka metropolitan area, Japan and Kuala Lumpur, Malaysia are used for empirical analysis. The results suggest that population density at residential area significantly and negatively affects car ownership for both areas, and that the effects are larger for Osaka metropolitan area than for Kuala Lumpur. Also, bicycle ownership becomes higher at higher population density area for Osaka area, while higher at lower population density area for Kuala Lumpur, which represents the different usage patterns of bicycle between the two areas.

An adaptive information fusion model to predict the short-term link travel time distribution in dynamic traffic networks

As intelligent transportation systems (ITS) approach the realm of widespread deployment, there is an increasing need to robustly capture the variability of link travel time in real-time to generate reliable predictions of real-time traffic conditions. This study proposes an adaptive information fusion model to predict the short-term link travel time distribution by iteratively combining past information on link travel time on the current day with the real-time link travel time information available at discrete time points. The past link travel time information is represented as a discrete distribution. The real-time link travel time is represented as a range, and is characterized using information quality in terms of information accuracy and time delay. A nonlinear programming formulation is used to specify the adaptive information fusion model to update the short-term link travel time distribution by focusing on information quality. The model adapts good information by weighing it higher while shielding the effects of bad information by reducing its weight. Numerical experiments suggest that the proposed model adequately represents the short-term link travel time distribution in terms of accuracy and robustness, while ensuring consistency with ambient traffic flow conditions. Further, they illustrate that the mean of a representative short-term travel time distribution is not necessarily a good tracking indicator of the actual (ground truth) time-dependent travel time on that link. Parametric sensitivity analysis illustrates that information accuracy significantly influences the model, and dominates the effects of time delay and the consistency constraint parameter. The proposed information fusion model bridges key methodological gaps in the ITS deployment context related to information fusion and the need for short-term travel time distributions.     

Understanding members' carsharing (activity) persistency by using econometric model

Carsharing is an innovative travel alternative that has recently experienced considerable growth and become part of sustainable transportation initiatives. Although carsharing is becoming increasingly a popular alternative transportation mode in North America, it is still an under‐researched area. Current research is aimed at better understanding of the behavior of carsharing users. For every member, a two‐stage approach microsimulates the probability of being active in any month using a binary probit model and given that a particular member is active during a month, the probability of that member using the service multiple times using a random utility‐based model. The model is estimated using empirical data from one of the largest carsharing companies in North America. The model estimates reveal that the activity persistency of members is positively linked to previous behaviors for up to 4 months, and that the influence of previous months weakens over time. It also shows that some attributes of the traveler (gender, age, and language spoken at home) impact his or her behaviors. Copyright © 2010 John Wiley & Sons, Ltd.