PSI - Issue 52

Govardhan Polepally et al. / Procedia Structural Integrity 52 (2024) 280–292 Govardhan Polepally/ Structural Integrity Procedia 00 (2019) 000 – 000

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Martin caro et al., 2013). Italy has around 10,000 such bridges, while the UK has 40,000, and in the US, there are approximately 1,600 (de Santis et al., 2010b; Kamath, 2017). Similarly, in Iran, there are about 9,000 masonry bridges, and in India, 15% of bridges are constructed using masonry (Jahangiri et al., 2021; IRC, 2009). Most of these Masonry Bridges (MB) were built based on empirical principles for various purposes such as transportation, trade, communication, and water supply to populated areas. However, assessing their current state is crucial to determine their capacity for current traffic loads and speeds. However, this can be challenging due to the limited knowledge of their design and material properties (Orban et al., 2009). As the traffic demands and speeds increase, the engineering community is facing difficulties in determining the stability and capacity of these structures. Although various methods have been developed over the years to assess the condition of masonry bridges, no established methodology in the literature can determine the load-carrying capacity and remaining lifespan of these structures. Our study proposes an innovative approach to evaluate the structural integrity of a 93-year-old railway bridge located in southern India. The aim is to determine the span which might be deteriorated or damaged for various reasons. So simple comparative analysis is carried out by measuring natural frequencies and further studies can be extended to determine the remaining life span of the bridge and assess its load-carrying capacity, which could provide valuable insights into the maintenance and rehabilitation of similar masonry bridges all over the world. 2. Literature survey Numerous authors have suggested various approaches to evaluate the load-bearing capacity and functionality of MB. These methodologies include the Military Engineering Experimental Establishment (MEXE) method proposed by Heyman (1997), Limit State Analysis (LSA) introduced by Livesley (1978), and on-site experimental tests such as those by Orban et al. (2009) and Dorji, J. (2021). All of these methods have their own pros and cons. MEXE and LSA method does have certain drawbacks, such as overestimating the Load Caring Capasity (LCC). Non-destructive testing (NDT) may not provide answers to certain questions, including the actual LCC, the stresses from dead loads, and the residual life of the structure. Due to the technological developments in the field of electronics and computer science, researchers started using sensors for Vibration-based health assessment of MB (Vinay shimpi et al 2019). This technique involves using sensors and data acquisition systems to record the bridge's vibration response when subjected to ambient vibration. Subsequently, mathematical methods can be applied to estimate the system parameters, which can provide crucial information about the structure's dynamic behaviour (Brincker et al 2009). Two sensor data-based testing methods, Ambient Vibration Testing (AVT) and Operational Modal Analysis (OMA), can be used in this feild. AVT records the vibrations of the bridge caused by environmental factors such as wind, traffic, and pedestrians (Omenzetter et al 2013). OMA presents two alternatives for analysis - in either the Time Domain (TD) or Frequency Domain (FD) - based on the assumption of white noise (Brincker et al 2009). 3. Modal identification techniques Several methods for identifying modal properties from ambient vibration data have been employed previously presented in litereture (Bayraktar, A et al 2009, Brincker et al 2009, Peeters B 1999, Bayraktar, A et al 2015). The Operational Modal Analysis (OMA) approach utilizes various techniques in both the time and frequency domains in that Stochastic Subspace Identification technique (SSI) in the TD, and Frequency Domain Decomposition (FDD) in the FD are largly applied methods due to its simplicity and accuracy (Vinay shimpi et al 2019). Typically, the findings of Ambient Vibration Testing (AVT) and OMA are applied to refine the Finite Element (FE) model by integrating Non-Destructive Testing (NDT). 3.1. Frequency Domain Decomposition (FDD) FDD is output only frequency domain decomposition method which is based on singular value decomposition (SVD) of the spectral density (SD) obtained from ambient vibration test (Brincker, R et al 2000). The connection between the unknown input and the detected responses can be represented as per FDD