预应力锚杆-围岩耦合模型时变效应分析

为了揭示预应力锚杆-围岩耦合时变效应机理,利用分布力模型获取耦合模型的弹性解,结合材料性质和维度效应选用符合锚杆和围岩的流变模型（锚杆选用一维Kelvin模型,围岩选用三维Burgers模型）,求解预应力锚杆-围岩耦合模型在Laplace空间的解析解,通过Laplace逆变化便得到耦合模型的黏弹性解。探究锚杆预应力和流变模型的黏性参数对围岩应力、位移场和锚杆轴力的影响,并基于理论模型和数值模拟软件FLAC^3D的二次开发,开展相应数值模拟,对比分析解析解和数值解,验证解析解的正确性。研究结果表明：解析解与数值解吻合程度良好,在隧道内壁处,锚杆支护力随着时间的增大逐渐减小,且锚杆预应力和围岩的黏性参数与支护效果密切相关,其中围岩的支护效果与锚杆预应力大小呈现明显的正相关关系;围岩的位移变化表现出明显的时间相关性,并且与锚杆预应力大小呈现负相关关系;当锚杆的预应力过大时,围岩位移不再随之显著减小,由此可见,施加于锚杆的预应力不应过大;围岩Burgers模型中第Ⅰ蠕变阶段黏性系数影响锚杆的初期支护效果,而后期支护效果主要受围岩Burgers模型中第Ⅱ蠕变阶段黏性系数影响,并且随着黏性系数的增大锚杆后期支护效果越好;锚杆的流变状态不受围岩黏性系数的影响。     

基于主成分分析与BP 神经元网络的驾驶能耗组合预测模型研究

近年来交通领域能源消耗问题备受关注,本文从微观交通能耗预测出发,以实现北京市快速路基础路段的油耗预测为目的,基于出租车车载OBD/GPS终端,提取驾驶员微观驾驶行为数据,建立基于主成分分析与BP神经元网络的油耗组合预测模型,实现北京市快速路基础路段油耗的准确预测.结果表明：速度均值及标准差、最大车速、工况百分比、加速度及减速度均值、行驶距离和动能对油耗影响程度相对较高;同时模型能够实现城市快速路基础路段能耗的有效预测,预测精度达到92.46%.该方法的研究为城市交通能源消耗的监管与把控提供了支持.     

语音信息对驾驶人超速行为干预效果研究

为了明确语音信息对不安全驾驶行为的干预效果,以典型不安全驾驶行为超 速行驶为研究对象,针对超速发生前、发生时和发生后等3 个阶段设计不同风格的语音干 预信息,对30 名驾驶人在驾驶模拟器上分别进行干预模拟实验,设计合理的客观和主观 评价方法,针对干预效果进行评价和对比分析.实验结果表明,干预语音信息风格对干预 效果具有较大影响,驾驶员的客观表现与其主观认知也存在差异,超速发生前差异较大, 超速发生时和发生后差异较小,综合主客观评价结果得出了超速发生前、发生中和发生 后的最佳干预风格,可以为车载提醒设备设计、驾驶员教育策略制定等提供理论基础.     

基于Logit模型的居住区共享泊位选择行为分析

为定量描述停车者对居住区共享泊位的选择行为影响因素,将停车者的个人属性与出行属性作为效用变量,将居住区共享泊位停车和路内就近停车作为选择肢,建立二项Logit模型。分析表明：个人月收入、停车时长、额外步行距离、费率差等为影响停车者选择居住区共享泊位停车的显著影响因素,其中额外步行距离和费率差对共享泊位选择概率的影响程度更大,较低层次的个人月收入变化对共享泊位选择概率的影响更大。     

贵州软岩地区摩擦桩试验研究

灌注桩是当前较为常用的基础形式,但在软岩地区摩擦型灌注桩的理论分析、试验和测试研究远不能适应工程的需要。通过对贵州某工程在泥质粉砂岩层所做的单桩静载试验,测试了桩周侧阻力及端阻力。分析了桩的荷载传递形状。     

基于缺口应力的波形钢腹板结构疲劳分析研究

基于现行规范对波形钢腹板结构的疲劳问题没有明确的规定,为了研究这种结构的疲劳设计及评估方法,对试验模型梁进行等幅疲劳荷载试验,得到波形钢腹板梁典型疲劳细节和基础疲劳数据.应用有限元软件建模,采用子模型法计算细节处缺口应力,并采用缺口应力法对试验梁的疲劳性能进行评估.研究结果表明:缺口应力法评估波形钢腹板疲劳性能是可行的...     

铁路旅客乘车行为的层次分析

研究铁路旅客乘车行为对旅客列车开行方案的进一步优化、客运服务质量的提高和客运新产品的开发都具有重要意义。在分析铁路旅客乘车行为的基础上,采用层次分析法建立了铁路旅客乘车选择的层次结构模型,并给出了算法和步骤,用于计算旅客对不同种类列车的选择行为。最后给出了算例,所得结果较为合理。     

体育教学是A型性格健康长寿的百年大计

为了提高学生的体育知识、技能、学习兴趣,达到终身受益的目的,教师必提高教学素质,诚信教学,有的放矢,达到事半功倍.本文就学生A型性格进行体育教学,达到医疗作用与健康教育作用.     

A copula-based joint multinomial discrete–continuous model of vehicle type choice and miles of travel

In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.

Analysis of child pick-up during daily routines and for daytime no-notice evacuations

In a no-notice disaster (e.g., nuclear explosion, terrorist attack, or hazardous materials release), an evacuation may start immediately after the disaster strikes. When a no-notice evacuation occurs during the daytime, household members are scattered throughout the regional network, and some family members (e.g., children) may need to be picked up. This household pick-up and gathering behavior was seldom investigated in previous work due to insufficient data; this gap in our understanding about who within families handles child-gathering is addressed here. Three hundred fifteen interviews were conducted in the Chicago metropolitan area to ascertain how respondents planned their response to hypothetical no-notice emergency evacuation orders. This paper presents the influencing factors that affect household pick-up and gathering behavior/expectations and the logistic regression models developed to predict the probability that parents pick up a child in three situations: a normal weekday and two hypothetical emergency scenarios. The results showed that both mothers and fathers were more likely to pick up a child under emergency conditions than they were on a normal weekday. For a normal weekday, increasing the distance between parents and children decreased the probability of parents picking up children; in other words, the farther parents are from their children, the less likely they will pick them up. In an emergency, effects of distance on pick-up behavior were significant for women, but not significant for men; that is, increasing the distance between parents and children decreased the probability that mothers pick up a child, but had a less significant effect on the fathers’ probability. Another significant factor affecting child pick-up behavior/expectations was household income when controlling for distance. The results of this study confirm that parents expect to gather children under emergency conditions, which needs to be accounted for in evacuation planning; failure to do so could cause difficulties in executing the pick-ups, lead to considerable queuing and rerouting, and extend the time citizens are exposed to high levels of risk.