Steel Mesh-Reinforced Cementitious Composites (SMRCC) (traditionally known as ferrocement) have been in existence for few decades, but have some limitations set on element thickness and number of reinforcing mesh layers and the resulting deflection ductility. Therefore, the author has made an attempt to explore whether deflection ductility will improve in mesh-reinforced cementitious composites (25 mm thick) if discontinuous fibres are added to slab elements. For this purpose, thin slab elements of dimensions 700 mm (length) × 200 mm (width) × 25 mm (thickness) were cast and subjected to four point bending tests. Based on the flexural tests conducted on SMRCC (Control Slab Elements, cast with Steel Mesh Volume of reinforcement, MVr = 0.78, 0.94, and 1.23%) and Hybrid Mesh-and-Fibre-Reinforced Cement Based Composite (HMFRCBC) (Test Slab Elements, combining MVr = 0.78, 0.94 and 1.23% and Polyolefin Fibre Volume fraction, PO-FVf = 0.5‒2.5% of volume of specimens, with 0.5% interval), load-deflection and the deflection ductility index were analyzed. From the flexural load-deflection curves it has been observed that HMFRCBC slabs demonstrate higher flexural load-carrying capacity and deflection ductility when compared to SMRCC slabs. This study shows that higher the polyolefin fibre volume fraction (PO-FVf) from 0.5 to 2.5% (with a 0.5% interval) in HMFRCBC slabs, the higher the flexural deflection ductility. The Deflection Ductility Index (DDI) of HMFRCBC (with 5 layers of mesh and PO-FVf = 2.5%) is 4.5 times that of SMRCC. This study recommends that HMFRCBC can be used as an innovative construction material due to its higher flexural ductility characteristics.
In order to identify the modal parameters of civil structures it is vital to distinguish the defective data from that of appropriate and accurate data. The defects in data may be due to various reasons like defects in the data collection, malfunctioning of sensors, etc. For this purpose Exploratory Data Analysis (EDA) was engaged toenvisage the distribution of sensor’s data and to detect the malfunctioning with in the sensors. Then outlier analysis was performed to remove those data points which may disrupt the accurate data analysis. Then Data Driven Stochastic Sub-space Identification (DATA-SSI) was engaged to perform the modal parameter identification. In the end to validate the accuracy of the proposed method stabilization diagrams were plotted. Sutong Bridge, one of the largest span cable stayed bridge was used as a case study and the suggested technique was employed. The results obtained after employing the above mentioned techniques are very valuable, accurate and effective.