Abstract
The everyday passage of trains over railway bridges produces fatigue damage at critical bridge locations. The amount of fatigue damage accumulated is very sensitive to the stress ranges producing it. The passage of trains produces dynamic amplification of the internal stresses which depends on the train velocity. Therefore, it is imperative to have a reliable estimation of dynamic effects as these directly affect bridge member stresses. Although this topic is well treated in terms of plate girder bridges and dynamic effects considering the ultimate limit state, less literature is available on the case of truss railway bridges and the fatigue limit state. This thesis addresses this gap of quantifying dynamic effects for everyday train passages and their interaction with the accumulation of fatigue damage in truss railway bridges. Three-dimensional finite element (FE) analyses of a typical metallic truss railway bridge are carried out under the passage of railway freight loading and the effect of different modelling parameters on the internal forces is quantified. Subsequently, dynamic amplification factors (DAFs) for all the bridge members are estimated from the FE analyses, under different load models and train velocities, and compared with their bridge code counterparts. Statistical analysis of the estimated DAFs is also employed to propose distributions that capture the variability of the DAF among the bridge members which can then be used for the purposes of probabilistic analysis. Lastly, the effect of dynamic amplification on fatigue damage is explicitly quantified by comparing the damage estimates obtained through the use of codespecific DAFs with the ones obtained in this study. It is shown that modelling this type of truss bridge by using rigid connections throughout does not affect the load distribution considerably. The FE analysis has produced the highest DAFs, for this specific type of typical bridge, at a 50 km/hr velocity and these were found not to generally increase with increasing velocity. The bridge codes are found to overestimate the fatigue limit state DAFs for velocities higher than 50 km/hr. Furthermore, it is found that a one wagon model vehicle results in higher DAF estimates than a more realistic multi-wagon train model. The generalised extreme value distribution is found to provide the best fit to the DAF samples among the bridge members.