The recent application of deep learning for structural health monitoring systems for damage detection has potential for improvised structure performance and maintenance for long term durability, and reliable strength. Advancements in electro-mechanical impedance (EMI) techniques have sparked attention among researchers to develop novel monitoring techniques for structural monitoring and evaluation. This study aims to determine the performance of EMI techniques using a piezo sensor to monitor the development of bond strength in reinforced concrete through a pull-out test. The concrete cylindrical samples with embedded steel bars were prepared, cured for 28 days, and a pull-out test was performed to measure the interfacial bond between them. The piezo coupled signatures were obtained for the PZT patch bonded to the steel bar. The damage qualification is performed through the statistical indices, i.e., root-mean-square deviation (RMSD) and correlation coefficient deviation metric (CCDM), were obtained for different displacements recorded for axial pull. Furthermore, this study utilizes a novel Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM)-based hybrid model, an effective regression model to predict the EMI signatures. These results emphasize the efficiency and potential application of the deep learning-based hybrid model in predicting EMI-based structural signatures. The findings of this study have several implications for structural health diagnosis using a deep learning-based model for monitoring and conservation of building heritage.

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The mechanical performance of concrete with varying proportions of steel scraps as a composite additive is investigated in this work. A M50 grade concrete admixture with a 0.35 water-to-binder ratio was prepared for this study. The appropriate quantity of superplasticizer was included as the mineral admixture. Steel scraps are obtained as waste from local machining workshops and then included in various proportions, including 0.25, 0.5, 1.0, and 2.0 percentages. The cubical mortar specimens were being employed to determine the compressive characteristics of mortar structure with and without steel scrap, whilst the cylinder-formed specimens and beam shaped samples were being utilized to determine the indirect tensile strength and flexural strength of concrete mixture. All experiments with different percentages of steel scrap were conducted on the 3 replicates, and the mean value is provided in this paper. After 28 days, the cement without steel scrap seemed to have a mean compression, flexural, and tensile strengths of 46.3 MPa, 5.52 MPa, and 4.23 MPa, respectively, which were improved to 51.7 MPa, 6.16 MPa, and 4.58 MPa with the inclusion of 1.0% steel scrap. The proposed investigation will contribute to reducing cement use, hence reducing cement industry's adverse ecological impacts.

The prevalence of catastrophic structural member failure caused by steel corrosion in civil infrastructure underscores the importance of reducing reinforcement corrosion to enhance overall infrastructure costs, reliability, and sustainable development. This study examines the use of corrosion inhibitors to improve the durability and strength of concrete structures, with a focus on their long-term effectiveness in resisting corrosion in reinforced concrete structures. Multiple approaches such as inhibitors, repairing processes, and coatings have been explored to prevent concrete corrosion damage, with an emphasis on concrete corrosion performance in coastal and corrosive situations. This study investigates the effect of six different corrosion inhibitors (zinc oxide, magnesium oxide, urea, sodium nitrate, sodium molybdate, and diethyl ether) on the compressive strength, durability, and microstructural properties of concrete samples. The compressive strength is assessed using both destructive (28 days cube compressive strength) and non-destructive (Ultrasonic Pulse Velocity) test methods, while concrete durability is evaluated using the rapid chloride permeability test . SEM imaging is also conducted to analyze the microstructure of each mix. The findings of this study highlight the importance of inhibitors in enhancing the durability of reinforced concrete structures.

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