Probabilistic analysis of train running safety on railway bridges considering vehicle-structure interaction

• Grant number: 24/06964-6
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: September 01, 2024
• End date: August 31, 2025
• Field of knowledge: Engineering - Civil Engineering - Structural Engineering
• Principal Investigator: Tulio Nogueira Bittencourt
• Grantee: Eduardo Costa Granato
• Supervisor: Pedro Aires Moreira Montenegro Marques e Almeida
• Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: Universidade do Porto (UP), Portugal
• Associated to the scholarship: 21/12367-2 - Reliability analysis of the dynamic behavior of railway bridges considering the vehicle-structure interaction, BP.DR

Abstract

Railway transportation is essential for the movement of cargo and passengers around the world, and in recent decades advances in train technology have allowed a large increase in the load capacity and speed of vehicles. In this context, it was necessary to develop sophisticated dynamic analysis methods to evaluate the behaviour of structural systems of railway bridges, since large loads and high speeds induce significant dynamic responses in the bridge structure and the interaction between vehicle subsystems, track and structure is relevant for obtaining accurate answers in the structural analysis of the bridge and the comfort and safety conditions of vehicle traffic. The numerical modelling of structural systems of railway bridges is complex, involving the consideration of the characteristics of the structure, the track and the vehicle, taking into account different degrees of damping, non-linearities in wheel contact. Furthermore, there is a large degree of uncertainty regarding the different variables involved in the analysis that must be considered to obtain realistic results. Thus, a complete probabilistic analysis proves to be a necessary tool for the study of the reliability of structural systems and the safety of running traffic in the face of existing uncertainties to obtain a more realistic idea of the structural responses and train running safety both in serviceability and the ultimate limit states. Given this motivation, this thesis proposes the development of a framework for probabilistic analyses of railway bridges and the safety of trains running over them using dynamic analyses using vehicle-structure interaction models to explicitly evaluate derailment indexes under significant lateral excitations. Furthermore, it is proposed the development of an artificial intelligence-based methodology to optimize vehicle-structure interaction methods by predicting wheel-rail contact forces efficiently, which may allow multiple assessments of interaction models.