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针对弹性安装条件下多机脚设备总激励力估算繁琐的问题,提出一种设备等效激励力的计算方法。该方法将弹性安装的多机脚设备等效为只有一个机脚支撑的设备,将原有的多个隔振器简化为一个具有有效总阻抗的隔振器,利用原机脚隔振器上下端的响应与隔振器的有效总阻抗估算出的激励力,即可等效为该设备的总激励力。为验证该方法的准确性,利用该方法对某船用设备振动激励力进行估算。实验数据分析表明,在临界频率以内,可以忽略隔振器之间的耦合,估算值与实际测量值之间的误差小于5 dB,满足工程要求。 相似文献
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This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment,
emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked
back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting
ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air
pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the
generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately
2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving
meaningful reductions in GHGs and air pollution. 相似文献
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Xuegang Ban Peng Hao Zhanbo Sun 《Transportation Research Part C: Emerging Technologies》2011,19(6):1133-1156
We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation. 相似文献
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