Enhanced Ruiz criterion for the evaluation of crack initiation in contact subjected to fretting fatigue

The fatigue-fretting damage parameter (FFDP) introduced by Ruiz is comprehensively discussed in this paper. Shortcomings and limitations of this criterion are presented resulting in a combined energetic-multiaxial enhancement (eFFDP). Specific frictional power was supposed to control the fretting damage and the critical plane approach is used to solve the multiaxial stress state in the fretting contact. The significance of the eFFDP is evaluated for the key–shaft–hub connection under combined torque and bend loading. Applying the analysis to recent fatigue tests, a comparison of stress and fretting parameters is made for different loading conditions including estimation of the fretting fatigue limit.     

Accumulation and Mixing of Oils in Jinghu Sag of Subei Basin： Constraints from Thermal Maturity Parameters

Oils in Jinghu sag are abundant with high content of polar compounds and have a low ratio of saturate to aromatic hydrocarbons and a high ratio of resin to asphaltene. The gross composition of oils in the Jinghu sag suggests typical immature to low mature characteristics. Some compounds with low thermal stability were identified. Light hydrocarbons, a carbon preference index, an odd even index, n-alkane and hopane maturity parameters show mature features and little differences in the maturity level among oils. Sterane isomerization parameters indicate an immature to low mature status of oil. Transfer of the sedimentary center during sedimentation has led to different thermal histories among subsags and thus generated oils with different maturities. On the basis of source analyses, four migration and accumulation patterns with different maturity can be classified. Combined with available information on mergers of source, reservoir and long distance oil lateral migration, mixing conditions were present in the Jinghu sag. Experimental results indicate that maturity variations are caused by mixtures of hydrocarbons with different maturity.     

Performance parameters of an ejector-absorption heat transformer

Ejector-absorption heat transformers (EAHTs) are attractive for increasing a solar-pond's temperature and for recovering low-level waste-heat. Thermodynamic analysis of the performance of an EAHT is complicated due to the associated complex differential equations and simulation programs. This paper proposes the use of artificial neural-networks (ANNs) as a new approach to determine the performance parameters, as functions of only the working temperatures of the EAHT, which is used to increase the solar pond's temperature under various working conditions. Thus, this study is helpful in predicting the performance of an EAHT where the temperatures are known. Scaled conjugate gradient (SCG) and Levenberg–Marquardt (LM) learning algorithms and a logistic sigmoid transfer-function were used in the network. The best approach was investigated for performance parameters with developed software using various algorithms. The best statistical coefficients of multiple determinations (R²-values) equal 0.99995, 0.99997 and 0.99995 for the coefficient of performance (COP), exergetic coefficient of performance (ECOP) and circulation ratio (F), respectively obtained by the LM algorithm with seven neurons. In the comparison of performances, results obtained via analytic equations and by means of the ANN, the COP, ECOP and F for all working situations differ by less than 1.05%, 0.7% and 3.07%, respectively. These accuracies are acceptable in the design of the EAHT. The ANN approach greatly reduces the time required by design engineers to find the optimum solution. Apart from reducing the time required, it is possible to find solutions that make solar-energy applications more viable and thus more attractive to potential users. Also, this approach has the advantages of high computational speed, low cost for feasibility, rapid turn-around, which is especially important during iterative design phases, and ease of design by operators with little technical experience.     

一种面向车辆实时数据并行处理的任务调度算法

车辆实时监管正面临着不断增长的大规模车辆监测数据的实时处理需求,需要采用分布式的并行计算架构来提升大规模车辆监测数据处理的性能,支撑多样化的车辆监测数据处理任务,应对支撑环境的伸缩性需求。在这种架构下,对系统中不同计算节点间的车辆监测数据处理任务的调度提出了更高的要求。针对这一要求,并结合流式到达及历史积累的车辆监测数据的持续化处理需求以及大规模车辆监测数据实时处理中内存敏感的特征,提出一种基于路由表的并行任务调度算法。该算法基于车辆监测数据时空属性以及各计算节点的内存信息建立路由表,并以路由表的形式来进行任务的并行划分和分配调度,从而使得各计算节点达到负载均衡的状态。实验表明该算法能够使计算节点间的负载差异缩小到12%以内。此外,该算法在某市车辆监管实时系统中的实际应用也证明了其有效性。     

基于共同好友数的在线社会网络社区发现算法

为了快速准确地找到在线社会网络的社区结构,提出了一种基于共同好友数和节点邻居信息的社区结构发现算法。该算法以共同好友数最多的两个节点为初始社区,不断寻找与社区连接性最强的节点,并以节点Q值为衡量标准,判断是否将该节点加入到初始社区中,最后根据节点邻居所在初始社区信息确定最终的社区划分。针对两个经典社会网络和人工生成网络数据的实验划分结果表明,该算法是可行和有效的。     

基于LABVIEW的电能质量在线监测和分析

本文讨论了国家标准规定的电能质量参数的计算方法,并利用LabVIEW创建了频率、谐波、三相不平衡度的测量和数据分析程序,同时采用DataSocket技术进行网络通信。设计出了基于LABVIEW的电能质量在线监测和分析系统,该系统提高了在线监测的灵活性和参数的精度并能及时记录相关的电压事件,能够长时间稳定工作,具有一定的实用价值。     

基于数据库通知服务的车辆定位系统的研究

通过对目前远程车辆定位实现方法的分析和研究,阐明了其在实时性、执行效率等方面存在的一些问题,这些问题往往会成为定位系统发展的瓶颈,所以文中主要在阐述一种可以缓解这些问题缺陷的方法。采用在原有定位系统的基础上引入数据库通知服务技术的方法将数据库定位信息的更新及时有效地通知到客户端监控程序,实现了远程车辆及时准确的定位,并且使得程序的执行效率得到明显的提高。最后通过实际的程序开发和大量的实践测试,验证了此方法的可行性。     

一种用户行为分析的动态备份机制

目前大多数分布式存储系统采用静态备份机制保证系统的高可靠性,灵活性差,不适合系统规模及用户访问量不断变化的存储系统．因此提出一种基于用户行为分析的动态备份机制,通过分析用户行为获得相关信息来动态改变备份数量及确定备份位置,具有较强的灵活性,适合大规模的分布式存储系统;实现动态备份系统将其应用于已建立的科技信息数据中心．通过实验分析表明,该动态备份机制能提高系统的可靠性。     

精品课程教学录像的建设现状分析与建议

教学录像是精品课程建设的重要内容之一。为了开发集教学性、科学性、技术性与艺术性于一体的精品课程教学录像,针对精品课程教学录像的性质,参照其上网技术指标及网上浏览的特点,对其建设现状进行分析,并提出了精品课程教学录像建设的建议。     

桥梁基桩在含沙水流冲击作用下的冲蚀磨损数值模拟研究

过水桥梁的基桩外露已成为影响桥梁安全性的重要因素,携沙水流会对外露部分的基桩产生冲蚀作用,加速混凝土的破坏,累积到一定程度,会导致桥梁安全性降低,影响桥梁交通的正常运营。为研究携沙水流对基桩的冲蚀磨损规律及其影响因素,利用ANSYS-Workbench建立三维模型,在FLUENT的工作环境下,模拟水沙两相流的流动特性,并求解得出基桩最大冲蚀磨损速率。通过数值模拟,研究了携沙水流的流场特性,并得出了在不同流速、含沙量及粒径下的冲蚀磨损规律。结果表明:流速、含沙量及粒径都对最大冲蚀率有较大影响,其中,最大冲蚀率随流速的增加而增大,并呈现出明显的指数关系;含沙量与最大冲蚀率呈现出正相关关系;最大冲蚀率随粒径的增大呈现出先减少后趋于稳定的趋势。研究成果可以为后续基桩冲蚀磨损预测的工程应用提供相关依据。