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Finite element verification of the method of neutral axis for damage detection in composite beam structures

Author(s): Li, X; Glisic, B

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Abstract: The neutral axis in a loaded beam structure is the curve in the cross-section that experiences zero strain. With the absence of axial effects, the healthy location of the neutral axis can be predicted using the position of centroid of stiffness of the beam cross-section. Change in position of the neutral axis can indicate the change in position of centroid, and thus, can be used for damage detection purposes. In this paper, a finite element based analysis was used to verify the method of neutral axis for damage detection in a multi-girder concrete-steel composite test structure with known minute damage. Long-gauge fiber-optic strain and temperature sensors were installed on the test structure at two locations of damage and one healthy baseline location prior to the pouring of the concrete slab. A finite element model was developed and validated using strain measurements for static loading events, and used to predict the healthy neutral axis position at each monitored location. Results show that the finite element prediction of healthy neutral axis location matches very well with actual sensor measurements at the healthy baseline location. An upward shift of the neutral axis is noticed at damaged locations, which was also an observation from previous research. While the change of the position of the neutral axis at damaged locations is confirmation of the damage detection capabilities of the method, further research is needed to explain the physical cause of the detected upward shift of the neutral axis.
Publication Date: 1-Jan-2016
Citation: Li, X, Glisic, B. (2016). Finite element verification of the method of neutral axis for damage detection in composite beam structures. 8th European Workshop on Structural Health Monitoring, EWSHM 2016, 1 (747 - 754
Pages: 747 - 754
Type of Material: Conference Proceeding
Journal/Proceeding Title: 8th European Workshop on Structural Health Monitoring, EWSHM 2016



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