2.5D MFS–FEM model for the prediction of vibrations due to underground railway traffic. (1st December 2015)

• Record Type: Journal Article
• Authors: Amado-Mendes, Paulo; Alves Costa, Pedro; Godinho, Luís M.C.; Lopes, Patrícia
• Is Part Of: Engineering structures. Volume 104(2015:Dec. 01)
• Page Start: 141
• Page End: 154
• Publication Date: 2015-12-01
• Subjects: Soil–structure interaction -- Underground railway traffic vibrations -- Frequency domain -- MFS–FEM -- 2.5D formulation; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2015.09.013
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Numerical modelling of track–ground vibrations induced by underground traffic. 2.5D coupled MFS–FEM frequency domain model is proposed. Efficient soil–structure interaction modelling at long distances. Dynamic train–track–tunnel–ground interaction is considered. Abstract: Vibrations induced by underground railway traffic have been receiving special attention from the technical and scientific communities, and different models for their prediction can be found in the literature. Since the tunnel can be seen as a longitudinally invariant structure, a 2.5D approach can be applied, minimizing the computational requirements without losing the 3D character of the problem. A global numerical strategy that allows simulating the vehicle–track–tunnel–soil interaction is proposed here. Tunnel–soil interaction is accounted by coupling the Finite Element Method and the Method of Fundamental Solutions. This model is then linked with a train–track interaction model, allowing to simulate the complete process of vibration propagation from the vehicle to the soil. The model is verified against reference solutions, and its application is illustrated for a practical engineering problem. The presented results indicate that the method can be quite accurate and competitive, when compared with other currently available models.