To a certain degree, composite railway sleepers and bearers have been recently employed as a replacement for conventional timber sleepers. Importantly, attributed to the rise in traffic demand, structural health monitoring of track structural members is essential to improve the maintenance regime and reduce risks imposed by any structural damage. A potential modern technique for detecting damage in railway components by using energy waves is called acoustic emission (AE). This technique has been widely used for concrete structures in other engineering applications, but the application for composites is relatively limited. Recently, fiber-reinforced foamed urethane (FFU) composites have been utilized as railway sleepers and bearers for applications in the railway industry. Neither does a design standard exist, nor have the inspection and monitoring criteria been properly established. In this study, three-point bending tests were performed together with using the AE method to detect crack growth in FFU composite beams. The ultimate state behaviors are considered to obtain the failure modes. This paper is thus the world's first to focus on damage detection approaches for FFU composite beams using AE technology, additionally identifying the load-deflection curves of the beams. According to the experimental results, it is apparent that the failure modes of FFU composite beams are likely to be in brittle modes. Through finite element method, the results were in good agreement with less than 0.14% discrepancy between the experimental and numerical data. The attractive insights into an alternative technique for damage assessment of the composite components will help railway engineers to establish structural monitoring guidelines for railway composite sleepers and bearers.
CITATION STYLE
Sengsri, P., Ngamkhanong, C., de Melo, A. L. O., Papaelias, M., & Kaewunruen, S. (2020). Damage detection in fiber-reinforced foamed urethane composite railway bearers using acoustic emissions. Infrastructures, 5(6). https://doi.org/10.3390/INFRASTRUCTURES5060050
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