基于船模水池试验的船舶顺浪纯稳性损失计算扩展模式

船舶顺浪航行的纯稳性损失研究,已成为国际航海界和国际海事组织(IMO)关注的课题之一.在Ю.И.涅查耶夫根据28艘渔船和运输船船模水池试验的船舶顺浪纯稳性损失计算方法的基础上,提出了扩展模式,扩大了其适用范围,并给出了大长宽比(船长/船宽)舰艇纯稳性损失的算例,同时实现了该扩展模式的程序化,生成了实用化的软件.最后通过与CFD试验方法和一般理论计算法所得结果的对比,验证了该扩展模式计算结果的可信度.     

数值波浪水池及顶浪中船舶水动力计算

基于粘流理论建立了三维数值波浪水池,模拟了非线性波浪,并对规则波顶浪中前进的拘束船模的水动力进行了计算.数值模拟中,控制方程-RANS方程和连续性方程使用有限体积法离散,非线性自由面采用VOF方法处理;在入口边界模拟柔性造波板运动产生入射波,使用位于波浪水池尾部的人工阻尼区消波.给出了非线性规则波的模拟结果以及规则波顶浪中前进的拘束船模的水动力计算结果,并与理论解及DUT(Delfi University of Technology)的试验数据进行了比较,二者吻合良好.     

Noise level in the vicinity of signalized roundabouts

The analysis, assessment and estimation of noise levels in the vicinity of intersections is a more complex problem than a similar analysis for roads and streets. This is due to the varied geometry of the intersections, differences in the loads of individual movements, participation of heavy vehicles and mass transport vehicles, as well as the various types of traffic management and traffic control. This article analyses the influence of intersection type and traffic characteristics on the noise levels in the vicinity of classic channelized intersections with signalization, roundabouts and signalized roundabouts. Based on the conducted measurements, it has been established that, with comparable traffic parameters and the same distance from the geometric centre of the intersection, the L_Aeq value for signalized roundabouts is 2.5–10.8 dB higher in comparison to classic channelized intersections with signalization and 3.3–6.7 dB higher in relations to the analysed roundabout. Additionally the differences between L_Aeq levels at individual entries at the same signalized roundabouts may reach the value of approximately 4.5 dB. Such situation is influenced by differences in the intersection geometry, diameter of the intersection’s central island, traffic flow type, traffic management at the entries and traffic volume, especially the amount and traffic movements of multiple axle heavy vehicles. These factors have been analysed in detail in relation to signalized roundabouts in this paper.     

三维波对船舶运动响应影响研究

通常情况,实际海况的波浪更接近三维波,而在船舶运动预报时,目前主要考虑二维波(长峰波)中的响应,不能真正反映船舶在实际海浪中的运动.文中利用不同方法(频域方法、时域方法以及模型)研究了三维波的方向扩散性对船舶运动响应的影响.三种方法得到的三维波对船舶运动的影响是一致的.结果显示,在研究实际海况中的船舶运动时,考虑三维波的方向扩散性是非常重要的.     

规则波浪中舰船操纵与横摇耦合运动模拟及特性分析

采用六自由度舰船操纵性方程与横摇波浪力矩耦合构成动力学模型,对舰船在规则波浪中的操纵与横摇耦合运动特性进行了模拟研究.其中操纵性方程采用MMG模型,波浪力矩由切片法计算,舰船航向按PD控制.模拟计算了某船正横规则波浪下保持航向的横摇运动,计算结果与单自由度理论结果进行了比较,其幅频曲线与相频曲线两者符合较好,间接证明了耦合构成动力学模型的有效性.在此基础上计算了不同浪向角和航速下的横摇运动,以横摇等值极坐标曲线表征舰船规则波浪中的横摇特性,从而给出了规则波浪下舰船耦合动力学所描述的运动特征.     

运输船舶在波浪中失速的近似估算

如何准确、快速、简便地估算船舶在波浪中的失速,已成为船舶研究、设计人员及航运界有关人员共同关心的一个重要课题。文中给出了近似估算运输船舶在波浪中失速的2个方法。对处于初步设计阶段且尚未做过静水快速性能模型试验的运输船舶,可直接应用第2个方法。该方法提出的近似估算公式应用方便,也不用编程便可直接人工计算,且与模型试验结果相当吻合。     

机动车超速行驶防范对策分析

机动丰超速行驶是引起交通事故的主要原因,是严重的道路交通违法行为之一。机动丰超速是由于驾驶人没有及时纠正驾驶过程中的误判、误动的结果。引起超速的原因包括驾驶人、机动车、交通安全设施和其他因素四个方面,应从教育培训、法律、交通安全设施、交通科技四个方面采取措施预防超速。     

区域经济分析与地方公路交通量预测分析

论述区域经济分析过程中的注意要点,介绍经济发展的预测方法,阐述交通量与区域经济之间的相关性及几种模型的应用。     

Efficient missing data imputing for traffic flow by considering temporal and spatial dependence

The missing data problem remains as a difficulty in a diverse variety of transportation applications, e.g. traffic flow prediction and traffic pattern recognition. To solve this problem, numerous algorithms had been proposed in the last decade to impute the missed data. However, few existing studies had fully used the traffic flow information of neighboring detecting points to improve imputing performance. In this paper, probabilistic principle component analysis (PPCA) based imputing method, which had been proven to be one of the most effective imputing methods without using temporal or spatial dependence, is extended to utilize the information of multiple points. We systematically examine the potential benefits of multi-point data fusion and study the possible influence of measurement time lags. Tests indicate that the hidden temporal–spatial dependence is nonlinear and could be better retrieved by kernel probabilistic principle component analysis (KPPCA) based method rather than PPCA method. Comparison proves that imputing errors can be notably reduced, if temporal–spatial dependence has been appropriately considered.