Rail roughness and rolling noise in tramways

Companies which manage railway networks have to cope continually with the problem of operating safety and maintenance intervention issues related to rail surface irregularities. A lot of experience has been gained in recent years in railway applications but the case of tramways is quite different; in this field there are no specific criteria to define any intervention on rail surface restoration. This paper shows measurements carried out on some stretches of a tram network with the CAT equipment (Corrugation Analysis Trolley) for the principal purpose of detecting different states of degradation of the rails and identifying a level of deterioration to be associated with the need for maintenance through rail grinding. The measured roughness is used as an input parameter into prediction models for both rolling noise and ground vibration to show the potential effect that high levels of roughness can have in urban environment. Rolling noise predictions are also compared with noise measurements to illustrate the applicability of the modelling approach. Particular attention is given to the way the contact filter needs to be modelled in the specific case of trams that generally operate at low speed. Finally an empirical approach to assess vibration levels in buildings is presented

A comparison of ground vibration due to ballasted and slab tracks

With the development of non-ballasted track forms (often referred to as slab tracks) over the few last decades, it is important to understand their behaviour with respect to ground-borne vibration compared with the traditional ballasted tracks. This is important in deciding between the use of the two track forms. The present work aims to quantify the differences between slab tracks and ballasted tracks numerically by using the MOTIV model. This is a general and fully coupled three-dimensional model that works in the wavenumber-frequency domain. It can predict the vibration levels of the track and the ground due to the gravitational loading of a passing train and the wheel and rail unevenness. A comparative analysis between the two track types is presented in terms of ground vibration with emphasis given to the influence of the stiffness and inertial parameters of the two track forms. It is shown that, for the same fastener stiffness there are only small differences in ground vibration behaviour, with the mass of the track slab leading to reductions of 1–3 dB at frequencies above 16 Hz. However, if softer rail fasteners are used in the slab track, as is usual, this leads to further reductions above 63 Hz. The critical velocity on soft soil is also considered. Although there is little difference between the different tracks for a homogeneous ground, for grounds with a soft surface layer the critical velocity is increased by the slab bending stiffness. The maximum rail displacement is also smaller for a slab track than the equivalent ballasted track.The work described here has been supported by the EPSRC under the programme grant EP/M025276/1, ‘The science and analytical tools to design long life, low noise railway track systems (Track to the Future)’ and the MOTIV project (Modelling of Train Induced Vibration), grants EP/K005847/2 and EP/K006002/1. All data published in this article are openly available from the University of Southampton repository at https://doi.org/10.5258/SOTON/D1001.Scopu

A holistic approach for the design and assessment of railway tracks

In spite of the global financial crisis, considerable investments are being made in railway infrastructure in the UK and many countries around the world. Improvements in the quality and capacity of current services and the development of new railway infrastructure are needed to meet the increasing demand for transferring more people and goods in a more sustainable way. In particular, the performance of the track system is crucial to the successful and cost-effective operation of the railway. This has motivated much scientific research with the aim of better understanding the performance of the railway system, including both existing railway tracks and improved tracks for the future. Much current research on railway track focuses on individual aspects of the design and performance, e.g. track settlement, rail fatigue, ballast degradation, ride quality, maintenance, and noise and vibration. However to achieve substantial advances in railway track design, it is important to consider all these aspects in an integrated way. Changes that can benefit one aspect should not be allowed to have a negative impact on others. To facilitate this, a single tool should be developed or the computational tools that consider individual aspects of the design need to be integrated. The resulting tool can therefore be used to assess the behaviour of railway tracks in a holistic manner. A preliminary version of such a holistic tool is presented here. In this version, fast running models and empirical relationships are put together in order to calculate the performance of a railway track with regard to ride quality, ground-borne noise and vibration and rolling noise. Results for practical case studies are presented and discussed. The paper also highlights the limitations of the preliminary version and the future plans to achieve a reliable and comprehensive tool

Experimental validation of a numerical model for the ground vibration from trains in tunnels

Ground vibration and ground-borne noise from trains in tunnels are attracting increasing attention from researchers and engineers. They are important environmental issues related with the operation of underground networks in intensively-populated urban areas. An accurate prediction for this train-induced vibration can be very helpful in the implementation of countermeasures to achieve the control of vibration or noise levels. In this paper, a numerical model is introduced based on the 2.5D Finite Element / Boundary Element methodology. The part of the metro line concerned is built with a cast-iron tunnel lining. The tunnel structure and the track are modelled with finite elements while the ground is modelled using boundary elements. Then the 2.5D tracktunnel-ground model is coupled with a multiple-rigid body vehicle model to determine the response caused by the passage of a train. To validate the prediction results, measurements have been carried out of the vibration of the rail, tunnel invert, tunnel wall and ground surface when the train is passing by and these are compared with the predictions with good agreement

Structural identification of Egnatia Odos bridges based on ambient and earthquake induced vibrations

The dynamic characteristics of two representative R/C bridges on Egnatia Odos motorway in Greece are estimated based on low amplitude ambient and earthquake-induced vibrations. The present work outlines the instrumentation details, algorithms for computing modal characteristics (modal frequencies, damping ratios and modeshapes), modal-based finite element model updating methods for estimating structural parameters, and numerical results for the modal and structural dynamic characteristics of the two bridges based on ambient and earthquake induced vibrations. Transverse, bending and longitudinal modes are reliably identified and stiffness-related properties of the piers, deck and elastomeric bearings of the finite element models of the two bridges are estimated. Results provide qualitative and quantitative information on the dynamic behavior of the bridge systems and their components under low-amplitude vibrations. Modeling assumptions are discussed based on the differences in the characteristics identified from ambient and earthquake vibration measurements. The sources of the differences observed between the identified modal and structural characteristics of the bridges and those predicted by finite element models used for design are investigated and properly justified

Optimal sensor location methodology for structural identification and damage detection

Theoretical and computational issues arising in the selection of the optimal sensor configuration in structural dynamics are addressed. The information entropy is introduced to measure the performance of a sensor configuration. Asymptotic estimates are used to rigorously justify that selections of optimal sensor configurations can be based solely on nominal structural models, ignoring the time history details of the measured data that are not available in the initial experimental design stage. Heuristic algorithms are proposed for constructing effective sensor configurations that are superior, in terms of computational efficiency and accuracy, to the sensor configurations provided by available algorithms suitable for solving general optimisation problems. The theoretical developments and the effectiveness of the proposed algorithms are illustrated by designing the optimal configuration for an array of acceleration sensors placed on a bridge structure

Multi-objective optimization algorithms for finite element model updating

A multi-objective optimization method is presented for estimating the parameters of finite element structural models based on modal residuals. The method results in multiple Pareto optimal structural models that are consistent with the measured modal data and the modal residuals used to measure the discrepancies between the measured modal values and the modal values predicted by the finite element model. The relation between the multi-objective identification method and conventional single-objective weighted modal residuals methods for model updating is explored. Computationally efficient methods for estimating the gradient and Hessians of the objective functions with respect to the model parameters are proposed and shown to significantly reduce the computational effort for solving the single and multiobjective optimization problems. The proposed methods exploit Nelson's formulation for the sensitivity of the eigenproperties with respect to the parameters. Theoretical and computational developments are illustrated by updating finite element models of a multi-span reinforced concrete bridge using ambient vibration measurements. In particular, multi-objective identification results indicate that there is wide variety of Pareto optimal structural models that trade off the fit in various measured modal quantities. © 2008 by the Katholieke Universiteit Leuven Department of Mechanical Engineering All rights reserved

Bayesian methodology for structural damage identification and reliability assessment

A Bayesian framework is presented for structural model selection and damage identification utilizing measured vibration data. The framework consists of a two-level approach. At the first level the problem of estimating the free parameters of a model class given the measured data is addressed. At the second level the problem of selecting the best model class from a set of competing model classes is addressed. The application of the framework in structural damage detection problems is then presented. The structural damage detection is accomplished by associating each model class to a damage location pattern in the structure, indicative of the location of damage. Using the Bayesian model selection framework, the probable damage locations are ranked according to the posterior probabilities of the corresponding model classes. The severity of damage is then inferred from the posterior probability of the model parameters corresponding to the most probable model class. Computational issues are addressed related to the estimation of the optimal model within a class of models and the optimal class of models among the alternative classes. Asymptotic approximations as well as Monte Carlo simulations are used for estimating the probability integrals arising in the formulation. The framework can be used for assessing the reliability of structures based on the measured vibration data. The proposed methodology is illustrated by applying it to the identification of the location and severity of damage of a laboratory smallscaled bridge using measured vibration data

Structural health monitoring of a ravine bridge of Egnatia Motorway during construction

The instrumental rapid monitoring of the dynamic (ambient) response of a balanced cantilevered ravine bridge of Egnatia Motorway during its construction phases, when subjected to wind and other construction loads, was implemented. The aim is to verify the conformity both of the sequential construction phases and of the final completed structure of the ravine bridge of Metsovo to the design predictions. In this paper the modal frequencies, damping ratios and modeshape components of the completed balanced cantilever of pier M3 were identified from ambient acceleration records, and its analytical dynamic model was updated to determine the actual stiffness and mass properties of the structure

Pareto optimal structural models and predictions consistent with data and modal residuals

A multi-objective identification method for model updating based on modal residuals is proposed. The method results in multiple Pareto optimal structural models that are consistent with the measured modal data, the class of models used to represent the structure and the modal residuals used to judge the closeness between the measured and model predicted modal data. The conventional single-objective weighted modal residuals method for model updating is also used to obtain Pareto optimal structural models by varying the values of the weights. Theoretical and computational issues related to the solution of the multi-objective and single optimization problems are addressed. The model updating methods are compared and their effectiveness is demonstrated using experimental results obtained from a three-story laboratory structure tested at a reference and a mass modified configuration. The variability of the Pareto optimal models and their associated response prediction variability are explored using two structural model classes, a simple 3-DOF model class and a higher fidelity 546-DOF finite element model class. It is shown that the Pareto optimal structural models and the corresponding response predictions may vary considerably. The variability of Pareto optimal structural model is affected by the size of modelling and measurement errors. This variability reduces as the fidelity of the selected model classes increases. Copyright © 2007 by ASME