关于标准载荷时间历程和标准载荷谱的生成问题

在应用海洋结构物疲劳寿命预报统一方法时,必须要输入载荷时间历程.在用疲劳寿命预报统一方法设计某个结构时,就需要提供某种标准类型的载荷时间历程.在文献中,标准载荷时间历程或标准载荷谱(均用缩写SLH表示)已经研究了30多年.人们普遍认识到使用SLH有一系列优点,不管是对研究或是应用而言.文章先从现在已经建立的标准载荷时间历程的综述开始,然后详细给出生成标准载荷时间历程或标准载荷谱的步骤,最后提供了一个示范计算的例子.     

美国气垫登陆艇的技术发展及分析

基于美国气垫登陆艇(LCAC)的研制实情及其最近的延寿计划(SLEP)和其未来替代者——舰岸连接器(SSC)的发展趋势,对LCAC的快速性等总体性能进行计算和分析,并追踪LCAC有关新技术在芬兰T-2000艇与韩国LSF-II艇上的应用情况。     

Application of Computer in the Design of Process Thermal Cycle of Steel

IntroductionSteelingot.steelslabbecomest6elproductsafterheatingandrollingorforging.Steelproductsofforgingneedtobeheattfeatedinheattreatingfumace,fOrexampleannealingnormalization.Heattreatinentcandecreasestress,reducehydrogenconcentrationandimprovetheorganizationandperformanceofsteel.Everyprocessofproductionthatsteelingotschangeilltosteelproductsisaprocessofthermalcycleofsteel.Thisprocesswillconsumealargeamountofeneasmaterialandequipment.Inthepast,inmetallurgicalenterpriseofourcountrythetimeo…     

Jointly optimizing cost, service, and environmental performance in demand-responsive transit scheduling

In certain fleet systems, the environmental impacts of operation are, to some extent, a controllable function of vehicle routing and scheduling decisions. However, little prior work has considered environmental impacts in fleet vehicle routing and scheduling optimization, in particular, where the impacts were assessed systematically utilizing life-cycle impact assessment methodologies such as those described by the Society of Environmental Chemistry and Toxicology. Here a methodology is presented for the joint optimization of cost, service, and life-cycle environmental consequences in vehicle routing and scheduling, which we develop for a demand-responsive (paratransit or dial-a-ride) transit system. We demonstrate through simulation that, as a result of our methodology, it is possible to reduce environmental impacts substantially, while increasing operating costs and service delays only slightly.     

Life cycle ownership cost and environmental externality of alternative fuel options for transit buses

This paper assesses alternative fuel options for transit buses. We consider the following options for a 40-foot and a 60-foot transit bus: a conventional bus powered by either diesel or a biodiesel blend (B20 or B100), a diesel hybrid-electric bus, a sparking-ignition bus powered by Compressed Natural Gas (CNG) or Liquefied Natural Gas (LNG), and a battery electric bus (BEB) (rapid or slow charging). We estimate life cycle ownership costs (for buses and infrastructure) and environmental externalities caused by greenhouse gases (GHGs) and criteria air pollutants (CAPs) emitted from the life cycle of bus operations. We find that all alternative fuel options lead to higher life cycle ownership and external costs than conventional diesel. When external funding is available to pay for 80% of vehicle purchase expenditures (which is usually the case for U.S. transit agencies), BEBs yield large reductions (17–23%) in terms of ownership and external costs compared to diesel. Furthermore, BEBs’ advantages are robust to changes in operation and economic assumptions when external funding is available. BEBs are able to reduce CAP emissions significantly in Pittsburgh’s hotspot areas, where existing bus fleets contribute to 1% of particulate matter emissions from mobile sources. We recognize that there are still practical barriers for BEBs, e.g. range limits, land to build the charging infrastructure, and coordination with utilities. However, favorable trends such as better battery performance and economics, cleaner electricity grid, improved technology maturity, and accumulated operation experience may favor use of BEBs where feasible.     

Predictive usage mining for life cycle assessment

The usage modeling in life cycle assessment (LCA) is rarely discussed despite the magnitude of environmental impact from the usage stage. In this paper, the usage modeling technique, predictive usage mining for life cycle assessment (PUMLCA) algorithm, is proposed as an alternative of the conventional constant rate method. By modeling usage patterns as trend, seasonality, and level from a time series of usage information, predictive LCA can be conducted in a real time horizon, which can provide more accurate estimation of environmental impact. Large-scale sensor data of product operation is suggested as a source of data for the proposed method to mine usage patterns and build a usage model for LCA. The PUMLCA algorithm can provide a similar level of prediction accuracy to the constant rate method when data is constant, and the higher prediction accuracy when data has complex patterns. In order to mine important usage patterns more effectively, a new automatic segmentation algorithm is developed based on change point analysis. The PUMLCA algorithm can also handle missing and abnormal values from large-scale sensor data, identify seasonality, and formulate predictive LCA equations for current and new machines. Finally, the LCA of agricultural machinery demonstrates the proposed approach and highlights its benefits and limitations.     

An exploration of the importance of social influence in the decision to start bicycling in England

The purpose of this paper is to gain a better understanding, through qualitative exploration, of the ways in which social influence affects the decision to start bicycling in England. ‘Social influence’ is defined as the process by which an individual’s thoughts and actions are changed by the thoughts and action of others. Its role was investigated at three levels: the immediate family, household members and significant others (direct social influence); the extended family, friends, peers and colleagues (less direct social influence); and the wider cultural context (indirect social influence). Interviews with 61 individuals living in 12 towns and cities across England were analysed. Half of the interviewees were new regular bicyclists and the other half did not bicycle at all, or only occasionally. Social influence was found to be the dominant factor for a minority of the cases where participants started bicycling regularly. It played a role alongside other factors in other cases. It could take the form of direct influence from family, friends and peers or indirect influence from the social and cultural context. The analysis illustrates the difficulty of capturing social influence which is often hidden and emerges incidentally in the course of the interviews and interacts with other contributing factors. The role of social influence found in this research challenges the rational approach to explaining travel decision making that has traditionally dominated transport studies. The paper suggests that social processes could be harnessed to improve the efficacy of bicycling promotion programs.     

混合动力汽车行驶工况的仿真分析

汽车的实际行驶条件对汽车性能具有直接影响。对于混合动力汽车,其部件的选型以及控制策略的制定都与道路行驶工况密切相关文章对汽车行驶工况做了相应的分析．利用GT—DRIVE软件对某微型混合动力汽车进行了建模与仿真仿真结果表明,在经济性方面混合动力汽车比传统汽车有明显的优势．如何更好地分配混合动力汽车功率将是混合动力汽车研究的重点.     

铁路通信网质量人工智能评估系统的研究及应用

梳理和总结了铁路通信网的维护管理要求,结合铁路通信网的"全寿命管理"需求和未来的"智能运维"理念,针对适合于铁路特点的数据分析、评估决策场景进行算法研究和模型建立,采用自动采集、多维存储、大数据分析和"管理驾驶舱"可视化等新技术,研究建设了铁路通信网质量人工智能评估系统,实现对骨干通信网质量数据的全寿命期的采集、分析及管理,为网络优化调整、业务资源变更和修程修制改革提供数据基础,为推广全路通信网的质量管理提供了科学依据。     

基于BP神经网络的锂电池剩余寿命预测

准确的电池状态估算与剩余使用寿命预测能让用户及时获取电池信息并更新失效电池,保障整个电池组的安全高效运行.文章为精确地预测锂离子电池剩余寿命,引入了BP神经网络算法,并利用NASA电池循环寿命实验数据进行验证.