Railway critical speed assessment: A simple experimental-analytical approach

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.