国内外铁路轮对组装标准的对比分析

主要介绍国际、国外和我国铁道行业标准中轮对标准的架构，对比分析国际、国外和我国铁道行业标准轮对组装标准的内容，提出对采用国际、国外标准的建议。     

汽车、摩托车铝合金车轮粉末涂料的研究及进展

粉末涂料是一种不含任何有机溶剂以粉末形态进行涂装,经过固化交联成膜的新型表面涂装材料。粉末涂料作为车轮的底层涂装和面层罩光涂料,在国内得到了大量应用。随着21世纪车轮用粉末涂料新产品、新技术和新应用工艺的开发,应用前景将更加广阔。     

油料应用技术

主要介绍机械设备中常用的燃料油、润滑油、润滑脂、液压油和某些特种油的特性、牌号、分类和使用范围，以及实际工作中如何正确选用．     

铁路客运专线900t箱梁提运架设备研究

研究目的:客运专线建设目前已成为我国铁路发展的大趋势,而实现900t箱梁的吊装、运输和架设的提梁机、运梁机和架桥机则是客运专线建设中至关重要的施工装备,是决定客运专线能否如期建成的关键因素之一,因此对其进行研究,以配合实际施工。研究结果:成功研制提梁机、运梁车和架桥机,并在铁路客运专线建设中达到广泛应用。对设备选型应重点考量的问题、设备的应用和管理也获得了一定成果。     

基于GA和SVM的水火弯板焰道布置优化方法

水火弯板是目前船舶建造中普遍采用的曲型外板加工方法,由于机理复杂,其加工过程参数确定往往依赖于工人的加工经验,难以实现标准化和规范化。文章提出基于遗传算法(GA)和支持向量机(SVM)的水火弯板焰道布置优化方法,以成形曲面和设计曲面之间的形状误差最小为优化目标,将焰道布置优化问题分解成计算最小形状误差和搜寻最佳匹配位置两个问题,并分别运用嵌套GA和SVM来实现这两个问题的求解。实例验证表明该方法能快速高效确定最优的加热线布置方案。     

60 kg/m钢轨和60N钢轨轮轨接触几何关系对比分析

为揭示我国新研究设计的60N钢轨的轮轨接触几何关系,运用常用的迹线法,以LM型和LMA型车轮踏面为例,对60 kg/m钢轨(简称60钢轨)和60N钢轨轮轨接触几何关系及其对轨底坡和轮对摇头的适应性进行详细研究。结果表明:相比60钢轨,60N钢轨与LM型和LMA型踏面匹配时,轮轨接触点在钢轨上位于钢轨中心位置附近,同时不会在钢轨轨距角附近出现轮轨接触,且在发生轮缘接触前,60N钢轨相比60钢轨对应的等效锥度随着轮对横移量变化很小,说明60N钢轨有效的改善了轮轨接触几何关系;同60钢轨,60N钢轨对于LM型车轮踏面,当轨底坡为1/20时匹配更佳,对于LMA型车轮踏面,当轨底坡为1/40时匹配更佳,而摇头角对60钢轨和60N钢轨的影响基本一致。     

Analyzing passenger train arrival delays with support vector regression

We propose machine learning models that capture the relation between passenger train arrival delays and various characteristics of a railway system. Such models can be used at the tactical level to evaluate effects of various changes in a railway system on train delays. We present the first application of support vector regression in the analysis of train delays and compare its performance with the artificial neural networks which have been commonly used for such problems. Statistical comparison of the two models indicates that the support vector regression outperforms the artificial neural networks. Data for this analysis are collected from Serbian Railways and include expert opinions about the influence of infrastructure along different routes on train arrival delays.     

Towards data-driven car-following models

Car following models have been studied with many diverse approaches for decades. Nowadays, technological advances have significantly improved our traffic data collection capabilities. Conventional car following models rely on mathematical formulas and are derived from traffic flow theory; a property that often makes them more restrictive. On the other hand, data-driven approaches are more flexible and allow the incorporation of additional information to the model; however, they may not provide as much insight into traffic flow theory as the traditional models. In this research, an innovative methodological framework based on a data-driven approach is proposed for the estimation of car-following models, suitable for incorporation into microscopic traffic simulation models. An existing technique, i.e. locally weighted regression (loess), is defined through an optimization problem and is employed in a novel way. The proposed methodology is demonstrated using data collected from a sequence of instrumented vehicles in Naples, Italy. Gipps’ model, one of the most extensively used car-following models, is calibrated against the same data and used as a reference benchmark. Optimization issues are raised in both cases. The obtained results suggest that data-driven car-following models could be a promising research direction.     

Analysis of air traffic control operational impact on aircraft vertical profiles supported by machine learning

The Air Traffic Management system is under a paradigm shift led by NextGen and SESAR. The new trajectory-based Concept of Operations is supported by performance-based trajectory predictors as major enablers. Currently, the performance of ground-based trajectory predictors is affected by diverse factors such as weather, lack of integration of operational information or aircraft performance uncertainty.Trajectory predictors could be enhanced by learning from historical data. Nowadays, data from the Air Traffic Management system may be exploited to understand to what extent Air Traffic Control actions impact on the vertical profile of flight trajectories.This paper analyses the impact of diverse operational factors on the vertical profile of flight trajectories. Firstly, Multilevel Linear Models are adopted to conduct a prior identification of these factors. Then, the information is exploited by trajectory predictors, where two types are used: point-mass trajectory predictors enhanced by learning the thrust law depending on those factors; and trajectory predictors based on Artificial Neural Networks.Air Traffic Control vertical operational procedures do not constitute a main factor impacting on the vertical profile of flight trajectories, once the top of descent is established. Additionally, airspace flows and the flight level at the trajectory top of descent are relevant features to be considered when learning from historical data, enhancing the overall performance of the trajectory predictors for the descent phase.     

基于ANSYS Workbench的越野汽车轮毂有限元分析及优化

文章利用三维软件Creo建立轮毂的三维模型,导入ANSYS Workbench后进行网格化,形成有限元计算模型并进行计算,得出其极限工况时的应力、变形结果。依据分析计算结果,提出结构改进方案并进行验证计算,为优化设计提供重要的理论依据。