基于统计能量法的船舶板架结构简化建模方法研究

统计能量法是解决复杂结构高频动力学问题的主要方法之一,限于其分析特性,过于细致化的建模会引发其计算量大、计算精度低等问题。针对典型的船体板架结构,提出基于统计能量法的船体板架结构简化建模方法,并结合数值计算加以验证。根据实际需求,提出简化建模的等效原则,给出多平板的简化建模方法;通过研究给出周期加筋板的简化建模方法;提出一种双层底结构的简化建模方法,并进行误差分析。     

基于FCM的内河一类船长实操考试效能评估

为解决内河一类船长实操考试效能评估问题,提出了一种基于模糊认知图的评价模型(FCMES).在建立影响因素层的不同评价等级基础上,通过问卷调查辨识出了25个影响因素;据专家意见将收集到的定性数据转化为三角模糊数,得到不同的模糊矩阵;利用模糊推理规则的方法聚合各模糊矩阵,再解模糊化,获取邻接矩阵.采取输入端数、输出端数及中心度3个指数的方法,分析FCMES中各因素的重要程度,选出核心变量.利用Matlab实现对FCMES认知图的推理仿真,检验核心变量的准确性.结果表明,绩效评估、评估员素质、模拟器效能、考试流程设计合理性,这4个影响因素对内河一类船长实操考试的效能有重要影响.     

信号控制下交叉口延误计算方法研究

为了对交通信号控制参数进行优化,需要对交叉口延误进行定量的分析与计算。根据信号控制交叉口理论,在以往定时信号延误研究的基础上,基于交叉口一个进口方向的车辆延误分析,针对交叉口各进口方向同时处于非饱和与同时处于过饱和交通状况,分析并推导了交叉口延误公式.并用具体的算例说明了公式的用法。公式表明了交叉口延误与信号控制参数、车辆到达率等参数之间的动态关系,为进一步研究交通信号自适应控制方法和建立交通信号控制参数优化的性能指标函数提供了信息。     

兰新高铁甘青段路基冻胀自动监测及分析研究

为查明兰新高铁甘青段路基冻胀变形原因和影响因素,提出相应的冻胀处理措施,将路基冻胀变形控制在允许范围之内,采用自动监测系统,对路肩以下5 m范围内路基的冻结深度、水分、冻胀变形等进行监测,并对监测结果进行统计分析和深入研究。研究结果表明:路基冻结深度的发展主要受气温的影响,基床表层以下填料含水量随着冻结深度增加缓慢增加;基床表层及基床底层上部1.0 m范围冻胀量占总冻胀量的80%以上;低路堤地段冻胀最严重。为减少路基冻胀量,设计及施工时应采用全冻结深度防冻胀方案,以填料防冻胀为主,辅以防水、疏水和隔热等综合措施;低路堤地段防冻胀措施应适当加强。     

神朔铁路钢轨折断风险评估模型研究

钢轨折断是一类严重的线路故障,研究钢轨折断风险评估对保障线路安全具有重要作用。基于模糊推理方法构建钢轨折断风险评估模型,该模型利用设备台账数据、钢轨状态检测数据和维修数据等相关的生产数据,识别钢轨折断致灾因子,量化评定致灾因子状态,建立模糊推理规则库,利用Mamdani模糊推理算法计算钢轨折断风险事件发生的可能性。最后采用神朔铁路神木北至黄羊城区间2013～2015年共3年的实际生产数据对模型的有效性进行验证,结果表明:所建模型可以较好地评估神朔铁路钢轨折断风险事件发生的可能性,对钢轨折断风险管理具有重要指导意义。     

多分类转导支持向量机

为了完成分类学习,传统的支持向量机基于带标记信息的经验数据归纳出一个通用的决策函数。而转导支持向量机则不同,它考虑包含测试集在内的所有数据信息并致力于最小化测试样本的分类错误数。在已有的2类分类方法的基础上构造了直接求解多类分类问题的的转导支持向量机。     

以实测振动数据为输入的水下结构振动与辐射噪声预报

  目的  潜艇的主要结构形式是环肋圆柱壳,目前关于肋骨对圆柱壳声辐射特性影响的研究大多集中在中、低频,但是振动声学问题涉及到更宽的频率范围。  方法  采用统计能量法研究宽频范围内肋骨对圆柱壳声辐射特性的影响。首先,分析圆柱壳增加肋骨后统计能量参数的变化;然后,研究耐压壳、外壳分别增加肋骨、改变肋骨间距、改变肋骨形状对圆柱壳声辐射特性的影响;最后,分析激振力作用在不同位置时,环肋圆柱壳声辐射特性的差异。  结果  得到了肋骨影响下双层圆柱壳在500 Hz~100 kHz范围内的统计能量参数和辐射噪声变化规律。  结论  研究结果对合理选用肋骨降低潜艇的振动与辐射噪声有一定参考作用。     

Factors with the greatest influence on drivers' judgment of roundabouts safety. An analysis based on web survey in Italy

The aim of this paper is to identify the roundabout geometric characteristics affecting the safety perception while the typical maneuvers (entry, circulation, exit) are being carried out. The tool used was an on-line questionnaire, filled out by about 1.650 respondents. Four different dimensionality reduction methods (Cluster Analysis, Correspondence Analysis, Exploratory Factor Analysis and Confirmatory Factor Analysis) were used to analyze the data collected from the survey, in order to examine the key factors affecting the safety perception during the typical roundabout maneuvers. The considerations arising from the final model are the following: 1) the respondents' opinions regarding the safety perception of maneuvers are not preconceived ideas, but they originate from specific safety perceptions due to roundabout geometric configurations; 2) the users prefer definitely single lane roundabouts; this is an important confirmation of most results in the literature; 3) it was quantified the extent of the relationship between the safety perception of the typical roundabout maneuvers and the following aspects: a) maneuver type, b) geometric characteristics of the roundabouts design elements. This is the innovative aspect of the present research whose results have implications regarding theory, infrastructure and the application of new safety technologies.     

Lights,camera, legal action! The effectiveness of red light cameras on collisions in Los Angeles

This study estimates the effect of red light cameras (henceforth cameras) on collisions under the Los Angeles Automated Photo Enforcement Program that ran from 2006 to 2011. To control for selection bias and unobservables, a data set is constructed such that intersections with cameras are compared to control groups of nearby intersections without cameras, matched on observable characteristics. To capture potential spillover effects of cameras, control groups at various distances from the intersections with cameras are considered. A Poisson panel data model with random coefficients is applied to these data and estimated using Bayesian methods. The program suffered from weaknesses in enforcement. The city’s courts did not uphold citations and this dampened the effect cameras had on drivers. These problems are accounted for in modeling. Controlling for these concerns, results indicate that the cameras decreased red light running related collisions, but increased right-angle and injury collisions, as well as collisions overall.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.