Experimental and Numerical Investigations into Dynamic Modal Parameters of Fiber-Reinforced Foamed Urethane Composite Beams in Railway Switches and Crossings

Author:

Sengsri PasakornORCID,Ngamkhanong ChayutORCID,de Melo Andre Luis Oliveira,Kaewunruen SakdiratORCID

Abstract

Dynamic behaviors of composite railway sleepers and bearers in railway switches and crossings are not well-known and have never been thoroughly investigated. In fact, the dynamic properties of the full-scale composite sleepers and bearers are not available in practice. Importantly, the deteriorated condition or even the failure of composite materials and components in the railway system can affect the functional limitations or serviceability of the switches and crossings. Especially, it is important to identify the dynamic modal parameters of Fiber-reinforced Foamed Urethane (FFU) composite railway sleepers and bearers so that track engineers can adequately design and optimize the structural components with their superior properties, for benchmarking with the conventional sleepers and bearers. This paper is the world’s first to investigate the vibration characteristics of full-scaled FFU composite beams in healthy and damaged conditions, using the impact hammer excitation technique. This study also determines the dynamic elastic modulus of FFU composite beams from experimental dynamic measurements. It is found that the first bending mode in a vertical plane obviously is the first dominant mode of resonance under a free-free condition. The dynamic modal parameters reduce when damages occur. In this study, finite-element modeling has been used to establish a realistic dynamic model of the railway track incorporating FFU composite sleepers and bearers. Then, numerical simulations and experimental campaigns have been performed to enable new insights into the dynamic behaviors of composite sleepers and bearers. These insights are fundamental to the performance benchmarking as well as the development of vibration-based condition monitoring and inspection for predictive track maintenance.

Publisher

MDPI AG

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