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When constructing a new railway line, its long length means there are significant financial implications associated with determining the geodynamic ground properties. Therefore, this paper presents recommendations to optimize the efficiency and depth of such a geotechnical site investigation. Firstly, a numerical analysis is performed to investigate the effect of soil layering, soil stiffness and track bending stiffness on critical velocity. It is shown that each of these variables play an important role, however for most practical cases, only the top 8 m of soil is influential. Track dynamics are rarely affected by soil properties at depths below this, meaning this is the maximum required depth of soil investigation. Using this knowledge, a hybrid experimental-analytical methodology is presented, based on a geophysical Spectral Analysis of Surface Waves (SASW) experimental setup to compute the ground dispersion curve and an analytical model to compute the track dispersion curve. The experimental and analytical results are combined directly, to accurately compute the critical velocity. This approach is attractive because: 1) SASW tests are typically accurate to ≈8 m (when using a mobile exciter) thus matching the required depth needed for critical velocity computation, 2) soil property uncertainties are inherently accounted for, 3) the uncertainties associated with SASW inversion are avoided. The approach is attractive when constructing new railway lines and upgrading the speed of existing lines because it can potentially yield site investigation cost savings. In-situ field work is performed to show the practical application of the technique., This research was financially supported by: Project POCI-01-0145-FEDER-007457–CONSTRUCT–Institute of R&D InStructures and Construction funded by FEDER funds through COMPETE2020– Programa Operacional Competitividade e Internacionalização (POCI)–and by national funds through FCT–Fundação para a Ciência e a Tecnologia; Project POCI-01-0145-FEDER-029577–funded by FEDER funds through COMPETE2020 – Programa Operacional Competitividade e Internacionalização (POCI), national funds (PIDDAC) through FCT and the Leverhulme Trust (PLP-2016-270). This work was partially carried out under the framework of In2Track2, a research project of Shift2Rail. The financial support provided by University of Leeds Cheney Award Scheme is also appreciated.

This paper reviews, synthesises and benchmarks new understandings relating to railway vibrations. Firstly, the effect of vibrations on passenger comfort is evaluated, followed by its effect on track performance. Then ground-borne vibration is discussed along with its effect on the structural response of buildings near railway lines. There is discussion of the most suitable mathematical and numerical modelling strategies for railway vibration simulation, along with mitigation strategies. Regarding ground borne vibration, structural amplification is discussed and how vibration mitigation strategies can be implemented. There is also a focus on determining how 'critical velocity' and 'track critical velocity' are evaluated - with the aim of providing clear design guidelines related to Rayleigh wave velocity. To aid this, conventional site investigation data is reviewed and related to critical velocity calculations. The aim is to provide new thinking on how to predict critical velocity from readily available conventional site investigation data.

Vibration assessments are required for new railroad lines 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 unexpected vibration abatement measures.This paper presents a new, high accuracy, initial assessment prediction tool for high speed lines. A 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 scoping 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.First, the development of the new tool is outlined. It is founded upon using a fully validated three dimensional finite element model to generate synthetic vibration records for a wide range of soil types. These records are analysed using a machine learning approach to map relationships between soil conditions, train speed and vibration levels. Its performance is tested through the prediction of two independent international vibration metrics on four European high speed lines and it is found to have high prediction accuracy.A key benefit from this increased prediction accuracy is that it potentially reduces the volume of detailed vibration analyses required for a new high speed train 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.