Simple and fast prediction of train-induced track forces, ground and building vibrations

• 作者: Lutz Auersch
• 来源期刊: 铁道工程科学（英文）
• 年，卷（期）: 2020,（3）
• 页码范围: 232-250
• 页数: 19页
• 语种: 英文

摘要

A simple and fast prediction scheme is presented for train-induced ground and building vibrations. Simple models such as (one-dimensional) transfer matrices are used for the vehicle–track–soil interaction and for the building–soil interaction. The wave propagation through layered soils is approximated by a frequency-dependent homogeneous half-space. The prediction is divided into the parts 'emission' (excitation by railway traffic), 'trans-mission' (wave propagation through the soil) and 'im-mission' (transfer into a building). The link between the modules is made by the excitation force between emission and transmission, and by the free-field vibration between transmission and immission. All formula for the simple vehicle–track, soil and building models are given in this article. The behaviour of the models is demonstrated by typical examples, including the mitigation of train vibra-tions by elastic track elements, the low-and high-frequency cut-offs characteristic for layered soils, and the interacting soil, wall and floor resonances of multi-storey buildings. It is shown that the results of the simple prediction models can well represent the behaviour of the more time-con-suming detailed models, the finite-element boundary-ele-ment models of the track, the wavenumber integrals for the soil and the three-dimensional finite-element models of the building. In addition, measurement examples are given for each part of the prediction, confirming that the methods provide reasonable results. As the prediction models are fast in calculation, many predictions can be done, for example to assess the environmental effect along a new railway line. The simple models have the additional advantage that the user needs to know only a minimum of parameters. So, the prediction is fast and user-friendly, but also theoretically and experimentally well-founded.