正六角形蜂窝芯层面内等效弹性参数研究

由于蜂窝芯层结构在外载作用下,蜂窝胞元壁板不但会产生弯曲变形,而且也会产生伸缩变形和剪切变形。过去Gibson公式在计算蜂窝芯层等效参数时只考虑了弯曲变形,虽然简便,但在导致蜂窝芯层分析时,弹性矩阵会出现不确定性;后来,宋明慧公式在Gibson公式的基础上,进一步考虑了伸缩变形的影响,但由于没有考虑剪切变形的影响,导致的蜂窝芯层结构不稳定,而且简化的弹性矩阵会出现奇异。该文新推导的面内等效弹性参数理论计算公式考虑了弯曲变形、伸缩变形和剪切变形对面内等效刚度的影响,是对Gibson和宋明慧公式的修正,克服了他们公式上的缺陷。     

路面混凝土的再生强度和弹性模量的研究

针对不同粒径再生混凝土的性能进行试验分析。试验结果表明：当骨料粒径#330～40mm时,路面再生混凝土的抗压强度最高,弹性模量略低,从而使路面混凝土再生综合性能表现最佳,进而达到新鲜混凝土路面的技术指标,而且也实现了废弃路面混凝土的再生利用。这对于保护环境、节约资源都有重要意义。     

对桩周土弹性模量确定方法的探讨

综合分析了目前确定桩基础上弹性模量的3种方法：室内试验方法、基于过去工程实践的经验关系的方法及由单桩的荷载试验曲线反算的方法,提出了一种利用单桩荷载－沉降曲线确定土弹性模量的简单方法,并给出了计算公式和图表供工程实际应用。通过实例分析表明,弹性理论法计算桩基础沉降时,应该用单桩荷载试验曲线反算方法得到的土弹性模量作为计算参数。     

基于需求弹性的城市公交票价优化方法及实证分析

城市公交票价是公交系统健康发展的重要因素,票价制定需兼顾公交企业的市场性和公益性双重属性,在保证服务质量的同时,考虑运营成本和最大限度吸引公交需求,实现经济效益和社会效益的双赢.在本文中,根据用户均衡理论,构建了城市多方式交通出行的需求分析模型,采用灵敏度分析方法给出了城市公交价格—需求弹性的计算方法.在此基础上,充分考虑了各种方式的交通特征、公交需求弹性、公交运营成本及政府限价等因素,提出了城市公交票价优化的数学规划模型,并给出了求解算法.最后,以国内某城市居民出行调查及公交运营数据为基础,分析了不同条件下公交客运需求的变化规律及城市公交票价的优化策略.     

一种建立弹性力学变分原理的新方法

本文提出一种直接利用弹性力学的基本方程、边界条件建立各种变分原理的新方法,较好地解 决了弹性力学各种变分原理的建立问题。文末还将本法与拉格朗日乘子法作了简单的比较,指 出了拉氏乘子法的一些局限性。      

需求价格弹性在制定商用车销售策略上的应用

根据管理经济学关于需求价格弹性的概念,商用车作为一种商品有其自身的需求价格弹性,并且不同车型、不同用途、不同用户会对需求价格弹性有直接的影响。因此研究不同车型、用途的商用车产品的需求价格弹性对东风商用车公司在商品规划、开发、定价、收益确定及销售市场上判断自己的价格策略和技术成本策略具有重要意义。     

基于随机效用理论的城市道路车辆自由换道行为研究

为深入分析城市道路驾驶员换道行为的影响因素，基于大连市西南路路段的车辆运行轨迹 数据，引入随机效用理论，建立了城市道路车辆自由换道模型，并对模型进行了标定和验证，且 应用弹性理论定量分析了换道概率对不同因素的敏感度。结果表明，所建模型可以较好地预测车 辆的自由换道行为；驾驶员换道决策对本车与当前车道前方车辆之间的车头间距最为敏感；相对 于当前车道前方空隙的刺激，相邻车道驾驶环境的诱惑对驾驶员换道决策的影响较小，说明在前 方无不利刺激（狭小的驾驶空间或加速空间） 的情况下，驾驶员在行驶过程中倾向于保持在当前 车道。该研究结果可进一步应用于城市道路换道行为的微观仿真研究中，以提高其仿真精度。     

Personal tradable carbon permits for road transport: Why, why not and who wins?

Personal road transport sector poses a significant challenge in reducing carbon emissions. This paper evaluates a policy approach known as personal tradable carbon permits to reduce carbon emissions from personal vehicles. The policy is a downstream tradable permit where individuals are allocated carbon emission caps. The policy is qualitatively evaluated in the context of carbon taxes and some upstream tradable permit options. The biggest disadvantage of such a policy is the initial set up costs. Personal tradable permits, however, are more effective than carbon taxes and are also capable of stabilizing the gasoline prices faced by the consumers when the underlying oil prices fluctuate. Since equity effects are often a concern to policy makers, the effect of such personal carbon permits on the distribution of burden is quantified in a partial equilibrium framework for the US population. Different permit allocation strategies are investigated in this regard. Using US consumer expenditure survey data, and incorporating a differentiated price response for different households, we find that all three allocation strategies considered are progressive: a per adult based allocation is the most progressive, a per vehicle allocation nearer to proportional, and a per capita allocation in between the two. Personal tradable permits therefore take care of equity concerns directly through the design of the policy.     

Overview of missing physical commodity trade data and its imputation using data augmentation

The physical aspects of commodity trade are becoming increasingly important on a global scale for transportation planning, demand management for transportation facilities and services, energy use, and environmental concerns. Such aspects (for example, weight and volume) of commodities are vital for logistics industry to allow for medium-to-long term planning at the strategic level and identify commodity flow trends. However, incomplete physical commodity trade databases impede proper analysis of trade flow between various countries. The missing physical values could be due to many reasons such as, (1) non-compliance of reporter countries with the prescribed regulations by World Customs Organization (WCO) (2) confidentiality issues, (3) delays in processing of data, or (4) erroneous reporting. The traditional missing data imputation methods, such as the substitution by mean, substitution by linear interpolation/extrapolation using adjacent points, the substitution by regression, and the substitution by stochastic regression, have been proposed in the context of estimating physical aspects of commodity trade data. However, a major demerit of these single imputation methods is their failure to incorporate uncertainty associated with missing data. The use of computationally complex stochastic methods to improve the accuracy of imputed data has recently become possible with the advancement of computer technology. Therefore, this study proposes a sophisticated data augmentation algorithm in order to impute missing physical commodity trade data. The key advantage of the proposed approach lies in the fact that instead of using a point estimate as the imputed value, it simulates a distribution of missing data through multiple imputations to reflect uncertainty and to maintain variability in the data. This approach also provides the flexibility to include fundamental distributional property of the variables, such as physical quantity, monetary value, price elasticity of demand, price variation, and product differentiation, and their correlations to generate reasonable average estimates of statistical inferences. An overview and limitations of most commonly used data imputation approaches is presented, followed by the theoretical basis and imputation procedure of the proposed approach. Lastly, a case study is presented to demonstrate the merits of the proposed approach in comparison to traditional imputation methods.     

Complementarity formulations for the cell transmission model based dynamic user equilibrium with departure time choice, elastic demand and user heterogeneity

In this paper we formulate the dynamic user equilibrium problem with an embedded cell transmission model on a network with a single OD pair, multiple parallel paths, multiple user classes with elastic demand. The formulation is based on ideas from complementarity theory. The travel time is estimated based on two methods which have different transportation applications: (1) maximum travel time and (2) average travel time. These travel time functions result in linear and non-linear complementarity formulations respectively. Solution existence and the properties of the formulations are rigorously analyzed. Extensive computational experiments are conducted to demonstrate the benefits of the proposed formulations on various test networks.