重载水泥混凝土路面损坏机理及对策研究

随着交通量的增加、轴载的增大和车速的提高,按照传统水泥混凝土路面规范修筑的道路出现了严重的早期破坏。本文通过分析重载交通作用下现有混凝土路面出现的早期破坏特征及其机理,从材料与结构上提出防止水泥混凝土路面在重载作用下发生早期破坏的对策。     

基于实测数据评估交通事件检测中神经网络应用性的研究

神经网络为交通事件自动检测技术摆脱传统方法探测率低、误报率高的状况提供了新的解决思路。在以往局限于仿真数据研究的基础上,本文利用I-880数据库实测交通事件数据对神经网络在交通事件自动检测中的实际应用进行了研究,结果表明:神经网络应用于交通事件自动检测技术中,具有较高的探测率和较低的误报率,但该算法可移植性较差,在实际应用中要予以考虑。     

基于视觉的前方车辆探测技术研究方法综述

对国内外关于车道上本车前方车辆检测方法进行了综述。根据探测车辆所采用的传感器不同,分别对采用单目视觉、双目视觉、视觉与其他传感器融合以及非视觉传感器的几种探测方法进行了比较与分析。同时,针对每种探测方法,进一步阐述了目前车辆识别的一些具体算法。最后,指出了每种方法存在的优点和一些不足。     

灌注混凝土桩施工方法及工艺的探讨

通过对钻孔灌注桩与沉入桩的对比分析,得出了钻孔灌注桩的优点,并且详细介绍了钻孔灌注桩的施工工艺和方法,总结了提高灌注混凝土桩承载力的方法和灌注桩的检测手段及一般事故处理方法,以供今后类似工程实践参考.     

大直径盾构管片水平拼装试验方法探究

大直径盾构管片水平拼装试验存在效率低下甚至失败的情况,不能真实全面反映产品尺寸精度。分析其原因除大直径管片体积大、重量大的因素外,主要原因在于现有的试验设备工装简陋、试验方法粗放、规范要求低等。结合当前水平拼装的规范要求,分析现有试验方法存在的不足,对现有拼装设备工装进行改造,制定高标准的、更加严格的工艺措施,创造性地提出在每层管片拼装时增加标高检测的新思路。将新方法应用于南京长江第五大桥夹江隧道工程管片水平拼装试验,结果良好,证明了此试验方法的科学性与有效性。     

A regression and beam theory based approach for fatigue assessment of containership structures including bending and torsion contributions

Container shipping has been expanding dramatically during the last decade. Due to their special structural characteristics, such as the wide breadth and large hatch openings, horizontal bending and torsion play an important role to the fatigue safety of containerships. In this study the fatigue contributions from vertical bending, horizontal bending and torsion are investigated using full-scale measurements of strain records on two containerships. Further, these contributions are compared to results from direct calculations where a nonlinear 3D panel method is used to compute wave loads in time domain. It is concluded that both bending and torsion have significant impacts on the fatigue assessment of containerships. The stresses caused by these loads could be correctly computed by full-ship finite element analysis. However, this requires large computational effort, since for fatigue assessment purposes the FE analysis needs to be carried out for all encountered sea states and operational conditions with sufficient time steps for each condition. In this paper, a new procedure is proposed to run the structure finite element analysis under only one sea condition for only a few time steps. Then, these results are used to obtain a relationship between wave loads and structural stresses through a linear regression analysis. This relation can be further used to compute stresses for arbitrary sea states and operational conditions using the computed wave loads (bending and torsion moments) as input. Based on this proposed method for structure stress analysis, an efficient procedure is formulated and found to be in very good agreement with the full-ship finite element analysis. In addition it is several orders of magnitude more time efficient for fatigue assessment of containership structures.     

基于ANN的船舶撞击高桩码头群桩损伤位置预测

本文采用有限元软件ABAQUS建立了船舶撞击高桩码头群桩的空间有限元模型。通过计算评估了撞击力、桩体刚度、撞击位置和撞击角度下对群桩结构损伤位置的影响。基于人工神经网络(ANN)方法,对不同参数组合下的群桩结构损伤位置进行了预测,并对ANN方法的可行性进行了评估。     

Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data.     

Locating emergency vehicles with an approximate queuing model and a meta-heuristic solution approach

In this paper, the location of emergency service (ES) vehicles is studied on fully connected networks. Queuing theory is utilized to obtain the performance metrics of the system. An approximate queuing model the (AQM) is proposed. For the AQM, different service rate formulations are constructed. These formulations are tested with a simulation study for different approximation levels. A mathematical model is proposed to minimize the mean response time of ES systems based on AQM. In the model, multiple vehicles are allowed at a single location. The objective function of the model has no closed form expression. A genetic algorithm is constructed to solve the model. With the help of the genetic algorithm, the effect of assigning multiple vehicles on the mean response time is reported.     

论孔子人才观的历史定位与普适价值

孔子的人才观虽然产生于春秋时期动荡的社会背景下,却揭示了人才的最本质内涵———＂仁、智、勇＂。三者作为人才内涵的核心三要素,形成一个内在的三角稳定结构,它能够持久地推动包括成才在内的人的生命境界的发展,因而具有超越时代和社会阶层的普适价值。