Reliability of FTA general vibration assessment model in prediction of subway induced ground borne vibrations
Reliability of FTA general vibration assessment model in prediction of subway induced ground borne vibrations
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DOI：
10.1016/j.soildyn.2018.11.002
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发表时间：
2019-02
影响因子：
4
通讯作者：
J. Sadeghi;M. Esmaeili;M. Akbari
中科院分区：
文献类型：
--
作者：
J. Sadeghi;M. Esmaeili;M. Akbari
地铁设计中的一个主要因素是地铁引起的振动水平。地面振动通常采用预测模型来估计，其中最常用的是FTA（联邦运输协会）通用振动评估模型。虽然故障树分析方法/模型在地铁系统的设计和运营中得到了广泛的应用，但其可靠性在现有的文献中还没有得到充分的评价。这是在这项研究中解决。为此目的，在伊朗地下铁路（地铁）网络的三条新建地铁线路上进行了全面的实验研究（时域和频域）。测量了轨道和土壤特性以及地面振动。FTA模型的可靠性和准确性进行了评估，通过比较这里得到的实验结果与FTA预测。与目前的看法相反，在FTA模型预测中，地铁地面振动被大大低估。得到的结果表明高达20 dB的实验结果和FTA预测之间的差异。基于现场实测数据和理论背景，对地铁事故树模型进行了改进和优化，提高了地铁事故树模型预测的可靠性。
One of the main factors in the design of subways is the level of subway-induced vibrations. The ground borne vibrations are usually estimated by prediction models among which the FTA (Federal Transportation Association) general vibration assessment model is the most popular one. Although FTA approach/model is vastly used in the design and operation of underground railway systems, its reliability has not been sufficiently evaluated in the available literatures. This is addressed in this research. For this purpose, a comprehensive experimental investigation (both in the time and frequency domains) was conducted in three newly constructed subway lines in the Iranian underground railway (subway) network. The track and soil characteristics as well as ground borne vibrations were measured. The reliability and accuracy of the FTA model was assessed through comparisons of the experimental results obtained here with the FTA predictions. Contrary to the current belief, considerable underestimations of subway ground borne vibrations in the FTA model predictions were shown in this research. The results obtained indicate up to 20 dB differences between the experimental results and those of FTA predictions. Based on the field measurements obtained here and the theoretical background, the FTA model was improved/optimized, leading to increase the reliability of FTA model predictions in subway systems.