中国铁路提速后技术进步对产出贡献的测算

选取我国铁路提速后1997~2007年间的相关数据,采用基于科布——道格拉斯生产函数的Solow余值法,将有限分布滞后模型和半参数回归模型引入计算模型,对数据进行拟合,计算得到铁路提速后技术进步、固定资本投入以及人力资本投入对产出的贡献率,并根据计算结果提出促进我国高速铁路建设的相关对策建议.     

螺旋桨无键过盈安装应力数值分析

针对螺旋桨无键过盈安装后桨-轴应力数值计算问题,运用弹性力学理论和ANSYS有限元法进行应力的数值计算。通过理论值与仿真值的对比分析表明:桨-轴应力的仿真值比理论值略大,理论值与仿真值具有较好的一致性;Ansys有限元法考虑了接触边缘区域存在应力奇异性、桨-轴存在轴向应力和螺旋桨外表面存在径向应力的情况,比运用弹性力学理论求解更加准确可靠;通过桨-轴应力计算可以证明过盈量选取的合理性,为检验螺旋桨无键过盈安装的可靠性提供理论基础。     

地铁车站中庭方案结构探讨

介绍某地铁车站因站位设置及管线原因采用特殊的中庭方案,以获得良好的空间感觉。与一般标准车站相比,结构侧墙及柱受力不利,因此将车站简化为平面框架模型计算。得到的结构内力表明,结构侧墙及柱受力在规范允许的范围内,证明这种新颖车站形式是可行的。     

内置橡胶支撑体空气弹簧冲击隔离分析

针对内置橡胶支撑体空气弹簧的冲击隔离问题,建立了理论模型,并给出数值解法。采用该模型和解法进行实例分析,得到了相关结论。     

柱形弹性套胀紧联接试验研究

在柱形弹性套胀紧联接理论研究基础上,为了研究柱形弹性套上的螺栓拉力与柱形弹性套所能传递的最大扭矩之间的关系设计了一套试验方案。在自主开发的弹性套胀紧联接试验台上进行试验,用Matlab采集数据,根据试验结果,最终得到柱形弹性套的螺栓压力与最大传递扭矩之间的试验公式。     

卵形钢丝气门弹簧多目标优化设计

气门弹簧广泛应用以卵形钢丝为截面的弹簧.以最大切应力最小和质量最轻作为设计目标,采用NSGA-Ⅱ算法基于MATLAB对卵形钢丝气门弹簧进行多目标优化设计.针对一实例的优化结果表明,可以准确快速得到可靠的Pareto最优解集,该优化设计方法可以为卵形钢丝气门弹簧设计提供参考.     

移动荷载下粘弹地基上刚性道面板响应分析

文中以一种更符合机场刚性道面实际情况的力学计算模型——移动荷载作用下粘弹性地基上无限大弹性薄板系统来研究道面弯沉的求解。应用线性系统的叠加原理和坐标变换,建立求解系统的动力响应广义积分公式,把运动荷载问题转化为获取位移脉冲响应函数。利用拉普拉斯和汉克尔变换求解板在瞬时点源荷载作用下的解,再结合广义积分得到道面板在移动荷载作用下的弯沉解析解。     

气动弹簧在绞吸挖泥船低频振动控制中的应用

针对绞吸挖泥船铰刀旋转切削岩石时产生的低频振动问题,基于气动弹簧的结构形式、受力分析及固有频率低的特点,研究气动弹簧在绞吸挖泥船上的应用方案,并利用船体和生活楼的位移反馈信号控制气动弹簧减振系统的工作状态,同时还介绍了船舶设计过程中需注意的问题。     

The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

On the income elasticity of the value of travel time

Transport infrastructure is long-term and in appraisal it is necessary to value travel time savings for future years. This requires knowing how the value of time (VTT) will develop over time as incomes grow. This paper investigates if the cross-sectional income elasticity of the VTT is equal to inter-temporal income elasticity. The study is based on two identical stated choice experiments conducted with a 13 year interval. Results indicate that the relationship between income and the VTT in the cross-section has remained unchanged over time. As a consequence, the inter-temporal income elasticity of the VTT can be predicted based on cross-sectional income elasticity. However, the income elasticity of the VTT is not a constant but increases with income. For this reason, the average income elasticity of the VTT in the cross-sections has increased between the two survey years and can be expected to increase further over time.