排水沥青混合料比表面积的分形研究

对集料的粒径分布、级配、集料总体积、空隙率、表面积等做出相关分析,给定了集料各特征值的具体求法,建立体积分维DV和表面积分维DS之间的关系,并根据级配曲线的走向,按不同分段方式进行比表面积计算对比。结果表明:不同的分段方式对于排水沥青混合料的比表面积确定有很大的影响,在进行比表面积计算时,应按各筛级进行逐级分段计算。     

天白水电站溢洪道弯曲段流态优化试验

为了改善开县天白水电工程溢洪道弯曲段流态,使断面内流量分布均匀,提高运行稳定性,根据其实际运行情况,结合以往类似工程的经验,提出了弯段底板高程正超高的优化设计方案。物理模型试验表明,采用这种工程方案可以很好地消减急流冲击波,改善弯曲段水流流态,提高下游消能能力。     

公路路面热辐射对汽车排放NO_x扩散特性的影响

针对公路沥青路面热辐射,建立了三维大气流动及机动车排放物扩散的CFD仿真模型,进行了非定常三维湍流流动模拟;结合气象因素及单车排放NOx扩散浓度的实地测试,研究了路面热辐射对机动车排放物扩散的影响。结果表明:路表加热作用所产生的热力环流使得污染物能够被有效地输送和扩散至上空,从而使得近地面的污染物浓度下降;随地表温度增高,输送效应增强;在尾气排放方向处于距排气口10 m远处,人的呼吸带高度处NOx浓度仍然较高;NOx扩散浓度的模拟值与实测值具有较好的符合,验证了数值模型的可靠性。     

长江上游塘土坝河段水流特性及河床演变分析

分析了塘土坝上游来水来沙条件,结果表明:该河段为典型山区河流,河岸组成较为坚硬,河床变形以推移质运动为主,河段年际间来水来沙变化不大。结合三峡大坝蓄水运行后该河段水沙条件的变化及实测地形资料,深入分析了塘土坝河段河床演变规律,并预测了洲滩演变趋势。为该河段航道维护和治理提供了理论依据。     

新月拱桥结构静动力特性分析

以某城市景观桥梁——新月拱桥为工程背景,运用Midas Civil建立全桥空间杆系有限元模型,对其施工全过程的静态受力、动力特性及稳定性进行分析。研究结果表明:空间桥跨结构受力合理,具有良好的刚度与强度;结构振动基频为0.93 Hz,为横向1阶;各主要施工阶段的稳定安全系数均大于4.0,具有良好的稳定性。     

飞燕式拱桥结构静动力特性分析

飞燕式拱桥具有跨越能力大、承载能力高、自平衡推力而地基适应能力强、造型优美的优点。以一座新建三跨连续自锚飞燕式提篮钢管混凝土拱桥为工程背景,通过有限元分析软件Midas Civil建立该大桥的空间杆系有限元模型,对该拱桥的空间受力特点进行分析,评定其结构静力、动力特性和施工过程以及成桥后的稳定性能。计算结果与分析表明,主拱肋及边跨各截面的抗力均大于组合轴力,同时各个主要施工阶段结构稳定安全系数均大于4。因此,该拱桥结构静动力性能优良,满足设计规范要求。     

Au40 Pd20合金原子团簇惰性气体氛围凝聚动力学行为研究

采用蒙特卡洛方法,结合Tight-binding和Lennard-Jones作用势,对Ar原子氛围中初始随机分布的40个Au原子和20个Pd原子体系的凝聚动力学行为进行了研究．Ar原子氛围对合金团簇的形成过程及其形貌尺寸有重要影响,计算表明：不同的Ar原子氛围得到的Au40 Pd20合金原子团簇凝聚结构形貌不同;在降温退火过程中, Ar原子密度大时,得到的Au40 Pd20合金原子团簇结构更加紧凑,且Au40 Pd20合金团簇凝聚相变温度更高;而恒温退火过程中,则发现较高温度时能得到较为紧凑的合金团簇结构,Ar原子密度越大,系统到达平衡的动力学时间更短．模拟结果能为惰性气体冷凝方法中实现合金团簇结构与形貌可控制备提供参考．     

浅谈大型船舶舱口围地面组装及整体吊装方案

本文介绍舱口围地面组装及整体吊装方案实施过程中,如何进行精度控制,减少整体吊装变形,实现舱口围组装与舱口盖安装调试工作转移到地面完成。     

A computationally efficient two-stage method for short-term traffic prediction on urban roads

Abstract

Short-term traffic prediction plays an important role in intelligent transport systems. This paper presents a novel two-stage prediction structure using the technique of Singular Spectrum Analysis (SSA) as a data smoothing stage to improve the prediction accuracy. Moreover, a novel prediction method named Grey System Model (GM) is introduced to reduce the dependency on method training and parameter optimisation. To demonstrate the effects of these improvements, this paper compares the prediction accuracies of SSA and non-SSA model structures using both a GM and a more conventional Seasonal Auto-Regressive Integrated Moving Average (SARIMA) prediction model. These methods were calibrated and evaluated using traffic flow data from a corridor in Central London under both normal and incident traffic conditions. The prediction accuracy comparisons show that the SSA method as a data smoothing step before the application of machine learning or statistical prediction methods can improve the final traffic prediction accuracy. In addition, the results indicate that the relatively novel GM method outperforms SARIMA under both normal and incident traffic conditions on urban roads.     

Effective aircraft maintenance schedule adjustment following incidents

In the real world, planned aircraft maintenance schedules are often affected by incidents. Airlines may thus need to adjust their aircraft maintenance schedules following the incidents that occur during routine operations. In tradition, such aircraft maintenance schedule adjustment has been performed manually, a process which is neither effective nor efficient, especially when the problem scale is large. In this study, an aircraft maintenance schedule adjustment model is developed, with the objective of minimizing the total system cost, subject to the related operating constraints. The model is formulated as a zero-one integer program and is solved using a mathematical programing solver. The effectiveness of the model is evaluated by application to a case study using data from an aircraft maintenance center in Taiwan. The test results show the proposed model, as well as the scheduling rules abstracted from the results are useful for the decision maker to adjust good maintenance schedules.