In this thesis a train-track-bridge interaction (TTBI) model is developed in order to study the dynamic amplification from track irregularities on railway bridges traversed by freight trains. These simulations are of great importance since rail freight transport is expected to increase in order to meet the climate goals. The shift of the freight industry is however not accomplished without complications, because of the heavier and more frequent transportation higher demand is put on the infrastructure supporting the railways. In order to adequately assess the bearing capacity of the railway bridges, more detailed models assessing the dynamic behavior of the bridges are needed. The research underlying the current model in Eurocode were made during the 1970s (ORE, 1976) and the 1990s (ERRI, 1999) which were based on very simplified relations of the interaction and irregularities. Two research questions are therefore established in this thesis. The first one is if the current dynamic amplification factor in Eurocode which accounts for track irregularities is over conservative and secondly if the same factor is suitable to utilize for both section forces and deflections. The model developed in order to answer the stated research questions is a 2D model (considering only vertical excitation) with a linearized Hertz contact spring coupling the vehicle subsystem to the track-bridge system. The bridges examined in the thesis are limited to simply supported bridges with a span length between 4-20 m carrying a ballasted track. The studied train speeds vary between 60 - 120 km/h in order to replicate the speed range utilized by freight trains. The quality of the track (irregularities) is varied between a standard variation of 0.5-5 mm and is generated based on the German power spectral density (PSD) function. Research have previously been carried out in the field of TTBI system but have mostly been focusing on high-speed railway engineering and few studies have been performed on heavy transportation. One of the pioneers in the field of TTBI modelling is Wanming Zhai and the model developed in this thesis is validated against one of his 2D models. Based on the simulations performed in this thesis it is evident that the current model in Eurocode EN 1991-2 is over conservative and in great need of a revision. The model presented in this thesis is for the case with the largest dynamic amplification (120 km/h and a 4 m span length) significantly lower than the model presented in Eurocode. From the sensitivity analysis it is possible to conclude that many of the parameters in the system have low influence on the dynamic amplification while others have considerable influence. The parameters that have a considerable influence might be more suitable with a probabilistic approach instead of a deterministic which was utilized in this thesis. / I denna avhandling upprättas en tåg-spår-bro interaktionsmodell i syfte att studera den dynamiska förstorningsfaktorn som uppkommer av ojämnheter från spåret för järnvägsbroar trafikerade av godståg. Dessa typer av simuleringar är viktiga då järnvägstransporter förväntas öka för att klara av att möta de klimatmål som fastställts. Denna ökning av järnvägstransporter genomförs dock inte utan problem. Ökningen medför fler och tyngre transporter vilket skapar problem för järnvägsinfrastrukturen (främst broarna). För att med säkerhet kunna fastställa bärförmågan hos broarna, behövs mer avancerade modeller än de som idag finns i Eurokod. Modellerna som finns angivna i Eurokod bygger på forskning genomförd under 70- (ORE, 1976) och 90-talet (ERRI, 1999), där det användes väldigt förenklade interaktions- och ojämnhets-modeller. På grund av detta har två frågeställningar upprättats. Den första är om den dynamiska förstoringsfaktorn som används i Eurokod för att ta hänsyn till ojämnheterna i spåret är överdrivet konservativ och den andra är om samma faktor är lämplig att använda för både snittkrafter och nedböjning. Modellen som upprättats för att besvara dessa forskningsfrågor är en 2D modell (vertikalt led) med en linjäriserad Hertz kontaktfjäder för att koppla samman fordonet med spår-bro systemet. Broarna som har studerats i denna avhandling är endast fritt upplagda broar med en spannlängd mellan 4-20 m med ballasterat spår. Tåg-hastigheten har varierats mellan 60-120 km/h i syfte att simulera relevanta hastigheter för godståg. Spårkvalitén (ojämnheterna) har beskrivits m.h.a. standardavvikelsen från det perfekta spårläget och har varierats mellan 0.5-5 mm. Dessa ojämnheter har genererats baserat på den tyska power spectral density (PSD) funktionen. Tidigare forskning har utförts inom ämnet tåg-spår-bro interaktion men med huvudsaklig fokus på höghastighetståg/resonans-beteenden och få studier har genomförts på godståg. En av föregångsmännen inom ämnet är Wanming Zhai, och modellen som upprättas i denna avhandling har därav validerats mot hans 2D modell. Baserat på simuleringarna i denna avhandling är det tydligt att den nuvarande modellen som används i Eurokod EN 1991-2 är överdrivet konservativ och i stort behov av en uppdatering. Det fall med stört dynamisk förstoringsfaktor (120 km/h och en spannlängd på 4 m) som behandlas i denna rapport är avsevärt lägre än det som återfinns i Eurokod. Från känslighetsanalysen som genomfördes kunde det fastställas att många av parametrarna i systemet har en låg inverkan på förstoringsfaktorn. För parametrarna som dock hade inflytande skulle ett probabilistiskt angreppssätt kunna vara mer passande än det deterministiska som använts i denna avhandling.

The analysis of vehicle-structure interaction systems plays a significant role in the design and maintenance of bridges. In recent years, the assessment of the health of existing bridges and the design of new ones has gained significance, in part due to the progress made in the development of faster moving locomotives, the desire for lighter bridges, and the imposition of performance criteria against rare events such as occurrence of earthquakes and fire. A probabilistic analysis would address these issues, and also assist in determination of reliability and in estimating the remaining life of the structure. In this thesis, we aim to develop tools for the probabilistic analysis techniques of state estimation, parameter identification and global response sensitivity analysis of vehicle-structure interaction systems, which are also applicable to the broader class of structural dynamical systems. The thesis is composed of six chapters and three appendices. The contents of these chapters and the appendices are described in brief in the following paragraphs. In chapter 1, we introduce the problem of probabilistic analysis of vehicle-structure interactions. The introduction is organized in three parts, dealing separately with issues of forward problems, inverse problems, and global response sensitivity analysis. We begin with an overview of the modelling and analysis of vehicle-structure interaction systems, including the application of spatial substructuring and mesh partitioning schemes. Following this, we describe Bayesian techniques for state and parameter estimation for the general class of state-space models of dynamical systems, including the application of the Kalman filter and particle filters for state estimation, MCMC sampling based filters for parameter identification, and the extended Kalman filter, the unscented Kalman filter and the ensemble Kalman filter for the problem of combined state and parameter identification. In this context, we present the Rao-Blackwellization method which leads to variance reduction in particle filtering. Finally, we present the techniques of global response sensitivity analysis, including Sobol’s analysis and distance-based measures of sensitivity indices. We provide an outline and a review of literature on each of these topics. In our review of literature, we identify the difficulties encountered when adopting these tools to problems involving vehicle-structure interaction systems, and corresponding to these issues, we identify some open problems for research. These problems are addressed in chapters 2, 3, 4 and 5. In chapter 2, we study the application of finite element modelling, combined with numerical solutions of governing stochastic differential equations, to analyse instrumented nonlinear moving vehicle-structure systems. The focus of the chapter is on achieving computational efficiency by deploying, within a single modeling framework, three sub structuring schemes with different methodological moorings. The schemes considered include spatial substructuring schemes (involving free-interface coupling methods), a spatial mesh partitioning scheme for governing stochastic differential equations (involving the use of a predictor corrector method with implicit integration schemes for linear regions and explicit schemes for local nonlinear regions), and application of the Rao-Blackwellization scheme (which permits the use of Kalman’s filtering for linear substructures and Monte Carlo filters for nonlinear substructures). The main effort in this work is expended on combining these schemes with provisions for interfacing of the substructures by taking into account the relative motion of the vehicle and the supporting structure. The problem is formulated with reference to an archetypal beam and multi-degrees of freedom moving oscillator with spatially localized nonlinear characteristics. The study takes into account imperfections in mathematical modelling, guide way unevenness, and measurement noise. The numerical results demonstrate notable reduction in computational effort achieved on account of introduction of the substructuring schemes. In chapter 3, we address the issue of identification of system parameters of structural systems using dynamical measurement data. When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. In this chapter, strategies are proposed based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples include a laboratory study on a beam-moving trolley system. In chapter 4, we consider the combined estimation of the system states and parameters of vehicle-structure interaction systems. To this end, we formulate a framework which uses MCMC sampling for parameter estimation and particle filtering for state estimation. In chapters 2 and 3, we described the computational issues faced when adopting these techniques individually. When used together, we come across both sets of issues, and find the complexity of the estimation problem is greatly increased. In this chapter, we address the computational issues by adopting the sub structuring techniques proposed in chapter 2, and the parameter identification method based on modified measurement models presented in chapter 3. The proposed method is illustrated on a computational study on a beam-moving oscillator system with localized nonlinearities, as well as on a laboratory study on a beam-moving trolley system. In chapter 5, we present global response sensitivity indices for structural dynamical systems with random system parameters excited by multiple random excitations. Two new procedures for evaluating global response sensitivity measures with respect to the excitation components are proposed. The first procedure is valid for stationary response of linear systems under stationary random excitations and is based on the notion of Hellinger’s metric of distance between two power spectral density functions. The second procedure is more generally valid and is based on the l2 norm based distance measure between two probability density functions. Specific cases which admit exact solutions are presented and solution procedures based on Monte Carlo simulations for more general class of problems are outlined. The applicability of the proposed procedures to the case of random system parameters is demonstrated using suitable illustrations. Illustrations include studies on a parametrically excited linear system and a nonlinear random vibration problem involving moving oscillator-beam system that considers excitations due to random support motions and guide-way unevenness. In chapter 6 we summarize the contributions made in chapters 2, 3, 4, and 5, and on the basis of these studies, present a few problems for future research. In addition to these chapters, three appendices are included in this thesis. Appendices A and B correspond to chapter 3. In appendix A, we study the effect on the nature of the posterior probability density functions of large measurement data set and small measurement noise. Appendix B illustrates the MCMC sampling based parameter estimation procedure of chapter 3 using a laboratory study on a bending–torsion coupled, geometrically non-linear building frame under earthquake support motion. In appendix C, we present Ito-Taylor time discretization schemes for stochastic delay differential equations found in chapter 5.