单桩荷载传递法修正计算分析

基于层状地基采用双曲线模型为荷载传递函数,提出了用Mindlin解和桩土共同作用的联合方法对荷载传递法的进行修正,并计算分析了单桩承载特性。将Lee的方法与双曲线荷载传递函数相结合使得Lee方法中考虑土体横向连续性的优点得以发挥。将横向连续性与竖向连续性修正相结合得到修正荷载传递法,用编制的计算机程序进行了工程实例的计算,结果表明,计算结果与实测值较为接近,其土层的平均SPT值较小,土体较容易产生变形,当试验荷载较高时,可能造成桩周土与桩身之间的滑移。修正荷载传递法与未修正和仅进行竖向修正的荷载传递法相比具有一定的精确性,能更好地反映单桩承载特性,且适用于群桩的分析计算。     

大直径嵌岩灌注桩水平荷载试验研究

桩在水平荷载作用下的受力性状是一个复杂的桩土相互作用过程。本文结合工程实例,通过现场水平静载试验,实测得到了水平荷载作用下大直径嵌岩灌注桩桩土共同作用时的工作性状,分析了桩体水平力、位移与时程关系、水平力与位移梯度关系、临界承载力以及地基土的水平抗力比例系数。试验结果可为今后同类桩的设计与研究提供参考。建议采用位移控制设计桩基础。     

Tractor-semitrailer model for vehicles carrying liquids

This article presents a model for solving solid-fluid interactions in vehicles carrying liquids. A tractor-semitrailer model is developed by incorporating suspension systems and tire dynamics. Owing to the solid-fluid interaction, equations of motion for the vehicle system are coupled. To simplify the complicated solution procedure, the coupled equations are solved separately using two different codes. Each code is analyzed separately; but as the parameters of the two codes depend on each other, the codes must be connected at the end of each time step. To determine the dynamic behavior of the system, different braking moments are applied. As the braking moments increase, braking time decreases. However, it turns out that increasing the braking moment to more than a certain level produces no significant results. It is also shown that vehicles carrying fluids need a greater amount of braking moments in comparison to vehicles carrying solids during braking. In addition, as the level of the fluid inside the tanker increases, from one-third to two-third of the tanker's volume, the sloshing forces applied to the tanker's walls increase. It was also concluded that the strategy used in this article to solve for the solid-fluid interaction by incorporating vehicle dynamic effects represents an effective method for determining the dynamic behavior of vehicles carrying fluids in other critical maneuvers.     

Analysing Demand for Suburban Trips: A Mixed RP/SP Model with Latent Variables and Interaction Effects

We analyse mode choice behaviour for suburban trips in the Grand Canary island using mixed revealed preference (RP)/stated preference (SP) information. The SP choice experiment allowed for interactions among the main policy variables: travel cost, travel time and frequency, and also to test the influence of latent variables such as comfort. It also led to discuss additional requirements on the size and sign of the estimated model parameters, to assess model quality when interactions are present. The RP survey produced data on actual trip behaviour and was used to adapt the SP choice experiment. During the specification searches we detected the presence of income effect and were able to derive willingness-to-pay measures, such as the subjective value of time, which varied among individuals. We also studied the systematic heterogeneity in individual tastes through the specification of models allowing for interactions between level-of-service and socio-economic variables. We concluded examining the sensitivity of travellers’ behaviour to various policy scenarios. In particular, it seems that contrary to political opinion, in a crowded island policies penalising the use of the private car seem to have a far greater impact in terms of bus patronage than policies implying direct improvements to the public transport service.     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Understanding the impacts of mobile phone distraction on driving performance: A systematic review

The use of mobile phones while driving—one of the most common driver distractions—has been a significant research interest during the most recent decade. While there has been a considerable amount research and excellent reviews on how mobile phone distractions influence various aspects of driving performance, the mechanisms by which the interactions with mobile phone affect driver performance is relatively unexamined. As such, the aim of this study is to examine the mechanisms involved with mobile phone distractions such as conversing, texting, and reading and the driving task, and subsequent outcomes. A novel human-machine framework is proposed to isolate the components and various interactions associated with mobile phone distracted driving. The proposed framework specifies the impacts of mobile phone distraction as an inter-related system of outcomes such as speed selection, lane deviations and crashes; human-car controls such as steering control and brake pedal use and human-environment interactions such as visual scanning and navigation. Eleven literature-review/meta-analyses papers and 62 recent research articles from 2005 to 2015 are critically reviewed and synthesised following a systematic classification scheme derived from the human-machine system framework. The analysis shows that while many studies have attempted to measure system outcomes or driving performance, research on how drivers interactively manage in-vehicle secondary tasks and adapt their driving behaviour while distracted is scant. A systematic approach may bolster efforts to examine comprehensively the performance of distracted drivers and their impact over the transportation system by considering all system components and interactions of drivers with mobile phones and vehicles. The proposed human-machine framework not only contributes to the literature on mobile phone distraction and safety, but also assists in identifying the research needs and promising strategies for mitigating mobile phone-related safety issues. Technology based countermeasures that can provide real-time feedback or alerts to drivers based on eye/head movements in conjunction with vehicle dynamics should be an important research direction.     

土-结构相互作用的桥梁多尺度建模与分析

考虑土-结构相互作用(SSI)是地震激励下桥梁抗震性能评估的热难点之一.由于考虑土体影响多而建立的结构模型计算耗时极长,为了提高效率,现采用一致多尺度建模方法,将所研究部位建为实体单元,其他部位建为梁单元,单元之间采用适当的方法进行界面连接,保证宏观、精细单元间的变形协调,并对某一桥梁进行分析,验证了该方法的正确性.在此基础上,基于多尺度建模方法,建立三跨连续梁桥模型,对其进行弹塑性时程分析,对比分析考虑SSI和不考虑SSI效应的桥梁模型在地震激励下的响应结果,研究SSI效应对桥梁抗震性能的影响.结果表明:多尺度建模方法可以在保证计算精度的前提下有效地提高计算效率;考虑SSI效应能够有效地降低桥梁的抗震性能需求.因此,在设计时应加以考虑.     

基于用户认知的新能源汽车内饰研究

在体验经济时代(在消费过程中追求顾客满意、注重自我体验),新能源汽车作为汽车行业的新兴产业,不断受到人们的追捧,其内饰比外观更为重要。在新能源汽车的内饰中,许多零部件具有不可替代的互动性,这也是用户了解新能源汽车内饰的关键因素之一。在智能化时代的背景下,大多数新能源汽车制造商单纯地将智能技术应用到新能源汽车上,其内饰造型、人机交互和使用体验已经不能满足客户对新能源汽车的要求。人机工程学是新能源汽车内饰设计的出发点,掌握用户形象认知是新能源汽车内饰设计的关键。因此,本文从用户的认知角度来研究新能源汽车的内饰设计与创新。     

Parameters optimisation of a vehicle suspension system using a particle swarm optimisation algorithm

The purpose of this paper is to determine the lumped suspension parameters that minimise a multi-objective function in a vehicle model under different standard PSD road profiles. This optimisation tries to meet the rms vertical acceleration weighted limits for human sensitivity curves from ISO 2631 [ISO-2631: guide for evaluation of human exposure to whole-body vibration. Europe; 1997] at the driver's seat, the road holding capability and the suspension working space. The vehicle is modelled in the frequency domain using eight degrees of freedom under a random road profile. The particle swarm optimisation and sequential quadratic programming algorithms are used to obtain the suspension optimal parameters in different road profile and vehicle velocity conditions. A sensitivity analysis is performed using the obtained results and, in Class G road profile, the seat damping has the major influence on the minimisation of the multi-objective function. The influence of vehicle parameters in vibration attenuation is analysed and it is concluded that the front suspension stiffness should be less stiff than the rear ones when the driver's seat relative position is located forward the centre of gravity of the car body. Graphs and tables for the behaviour of suspension parameters related to road classes, used algorithms and velocities are presented to illustrate the results. In Class A road profile it was possible to find optimal parameters within the boundaries of the design variables that resulted in acceptable values for the comfort, road holding and suspension working space.