Assessing Railway Vibrations in Urban Environments - A High Accuracy and Internationally Compatible Tool

Vibration assessments are required for new railroad lines (especially at high speeds) to determine the effect of vibrations on local communities. Low accuracy assessments can significantly increase future project costs in the form of further detailed assessment or vibration abatement solutions. This paper presents a new hybrid initial assessment prediction tool with higher accuracy than alternative methods. The key advantage of the new approach is that it is capable of including the effect of soil conditions in its calculation. This is novel because current models ignore soil conditions, despite such characteristics being the most dominant factor in vibration propagation. The model also has zero run times thus allowing for the rapid assessment of vibration levels across rail networks. Firstly the development of the new tool is outlined. Then its performance is analysed through the prediction of a variety of international vibration metrics on three European high speed lines. It is found to have high prediction accuracy for these vibration metrics thus showcasing its international compatibility. Furthermore, its ability to predict velocity decibel levels is compared against the commonly used Federal Railroad Administration of the United States Department of Transportation approach. The new model is found to outperform the existing approach for all test sites and that the performance benefit increases with distance from the track. Lastly, a method is presented for integrating the new model within the existing Federal Railroad Administration framework. This allows vibration levels to be predicted more accurately for a versatile combination of problems, by utilising rudimentary soil information. A key benefit from this increased prediction accuracy is that it potentially reduces the volume of detailed vibration analyses required for a new line. This avoids costly in-depth studies in the form of field experiments or large numerical models. Therefore the use of the new tool can result in cost savings in comparison to the Federal Railroad Administration approach.