掺纤维三灰砂砾基层性能试验分析

在三灰砂砾中添加纤维丝和纤维带,进行抗压、劈裂和抗折实验,结果表明添加纤维能明显提高三灰砂砾的抗拉强度和抗裂性能,从而提出改善路面基层性能的新途径。     

基于UG NX4.0的塑料模具设计

介绍了利用UGNX4．0软件进行注塑模具设计的方法。通过具体实例,阐述了如何利用UGNX4．0软件的参数化实体建模技术实现模具型腔、型芯的设计,模具装配、干涉分析、生成二雏图形。研究结果表明UGNX4．0软件对注塑模具的设计具有一定的参考价值。     

沥青路面设计中增加抗车辙设计指标的探讨

分析我国现行沥青路面设计指标,指出弯沉指标不能有效的控制路面车辙,在吸收国外沥青路面设计指标的基础上,增加路基顶面压应变指标作为沥青路面抗车辙设计指标;在参考城市道路设计规范,分析路面剪应力分布的基础上,提出面层材料剪应力也可作为沥青路面抗车辙设计指标。     

岩溶富水区深埋水沟排水隧道注浆圈参数研究

为合理确定深埋水沟排水方式下隧道注浆圈特征参数,以某岩溶富水区隧道工程为依托,采用FLAC3D软件建立流固耦合计算模型,针对其注浆圈参数进行合理探讨,研究注浆圈厚度、注浆圈渗透性对隧道涌水量、衬砌水压力、结构安全性的影响规律。研究结果表明： 增加注浆圈厚度或降低注浆圈渗透性可降低衬砌水压、控制涌水量、保障结构安全,但并不代表实际工程中注浆参数需要追求最值,而应兼顾安全性和经济性,选取相对合理的注浆参数;结合模拟计算结果与同类工程案例,建议依托工程注浆圈厚度以5～6 m、渗透性比值以注浆前的1/50（渗透系数为2×10-6 cm/s）为宜,并应结合实际进行技术经济对比,合理确定现场注浆参数。     

A robust non-Hertzian contact method for wheel–rail normal contact analysis

A modified Kik–Piotrowski (MKP) model is proposed in this paper for an accurate and robust calculation of wheel–rail normal contact problem. The presented method is able to consider the relationship between the elastic deformation of a line and the normal pressure distribution within the contact patch. A novel shape correction method is put forward to correctly describe the elastic deformation of the contact patch. Taking the results estimated by Kalker’s variational method and Kik–Piotrowski method as references, the proposed method is validated by three contact cases, including the assumed standardised non-Hertzian contact and the two-point contact, as well as the contact behaviours based on three actual wheel–rail profiles. The simulation results indicate that, compared with Kik–Piotrowski method, the proposed MKP method achieves better agreement with Kalker’s variational method. Moreover, the MKP method can avoid the abrupt change of wheel–rail normal force due to the sudden transfer of the contact point, which contributes to a better computational stability.     

Urban travel time reliability at different traffic conditions

The decision making of travelers for route choice and departure time choice depends on the expected travel time and its reliability. A common understanding of reliability is that it is related to several statistical properties of the travel time distribution, especially to the standard deviation of the travel time and also to the skewness. For an important corridor in Changsha (P.R. China) the travel time reliability has been evaluated and a linear model is proposed for the relationship between travel time, standard deviation, skewness, and some other traffic characteristics. Statistical analysis is done for both simulation data from a delay distribution model and for real life data from automated number plate recognition (ANPR) cameras. ANPR data give unbiased travel time data, which is more representative than probe vehicles. The relationship between the mean travel time and its standard deviation is verified with an analytical model for travel time distributions as well as with the ANPR travel times. Average travel time and the standard deviation are linearly correlated for single links as well as corridors. Other influence factors are related to skewness and travel time standard deviations, such as vehicle density and degree of saturation. Skewness appears to be less well to explain from traffic characteristics than the standard deviation is.     

插电式混合动力汽车高电压部件设计及布置

根据整车设计要求,建立插电式双电机MG1/MG2+行星轮系混合动力汽车高电压系统方案模型。通过理论计算及工程分析确定高压电池组、高电压线缆、双电机MG1/MG2、变频器(转换器/逆变器)、空调压缩机等高电压部件的结构及关键参数。针对高电压部件布置的安全及可靠性提出建议。     

公路隧道LED照明模拟控制系统设计

为更有效地设计隧道照明,针对隧道LED照明模拟设计欠缺的现状,基于Zigbee无线通信研发了隧道LED照明模拟控制系统,提出并设计了车载照度采集装置,实现对隧道内亮度的连续检测。实验分析表明:车载照度采集装置误差在-5.69%~3.06%之间,隧道模型设计亮度误差在-4.49%~5.57%之间,具有较高的可靠性。最后,研究成果已应用到隧道照明改造的模拟设计中,改造后节能百分比达53.6%。     

缓倾顺层岩质边坡变形数值模拟及处治方案研究

以黄花互通D匝道边坡为依托,采用FLAC软件对边坡进行数值模拟,探讨了水力作用对边坡变形破坏的影响;分析了预应力锚杆边坡加固前后模型水平位移变化。研究表明,加固后边坡稳定性大为改善,在水力作用下,边坡各处位移也非常小,甚至小于加固后无水力作用的情况。通过现场边坡位移监控,评价了该边坡处治效果。     

BP神经网络在解决电力消耗问题中的应用

由于BP神经网络在解决非线性复杂系统中存在很大的优势,以江西省1991—2011年人口、经济和耗电量等数据为研究对象,利用BP神经网络构建耗电量预测模型。模型一利用1991—2009年人口、经济和耗电量等数据作为训练样本,以2010—2011年作为测试样本来验证网络的准确性,再根据历史人口、经济等数据来预测历史耗电量;模型二采用传统的多元回归分析法,对非线性多元函数进行多元线性回归,通过回归模型得到的参数来预测耗电量。结果表明,模型一收敛性较好,所得预测结果绝对误差较小,而模型二传统方法得到的预测结果误差较大,因此,利用BP神经网络预测的结果具有非常大的参考价值,证明BP神经网络应用在电力消耗中的应用是可行的。