PSI - Issue 70

Maheshwari Sonker et al. / Procedia Structural Integrity 70 (2025) 477–484

484

References

Bansal, T., Talakokula, V., & Saravanan, T. J., 2024. EMI-based monitoring of prestressed concrete beam under chloride-induced corrosion using an embedded piezo sensor, Measurement: Sensors, 33, 101158. Enfedaque, A., Alberti, M., Gálvez, J., & Domingo, J. 2017. Numerical simulation of the fracture behaviour of glass fibre reinforced cement, Construction and Building Materials, 136, 108-117. H. Im, S. Hong, Y. Lee, H. Lee, and S. Kim, 2019. A colorimetric multifunctional sensing method for structural-durability-health monitoring systems,” Adv. Mater., vol. 31, no. 23, Art. no. 1807552, Inderyas, O., Tayfur, S., Alver, N., Catbas, F.N., 2025. A Machine Learning – Based Damage Estimation Model for Monitoring Reinforced Concrete Structures, In: Matarazzo, T., Hemez, F., Tronci, E.M., Downey, A. (eds) Data Science in Engineering Vol. 10. IMAC 2024. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. Chandramouli, K. & Rao, P Srinivasa Rao & Narayanan, Pannirselvam & Sekhar tirumala, Seshadri & Sravana, P.. 2010. Strength properties of glass fiber concrete. ARPN J Eng Appl Sci. 5. 1-6. Narayanan, A., & Subramaniam, K. V. L., 2017. Damage assessment in concrete structures using piezoelectric based sensors. Revista ALCONPAT, 7(1), 25-35. Peng Zhang and Qingfu Li, 2013. Fracture Properties of Polypropylene Fiber Reinforced Concrete Containing Fly Ash and Silica Fume, Research Journal of Applied Sciences, Engineering and Technology vol. 5, no.2, pp. 665-670. Salahaldein Alsadey, 2016. Effect of Polypropylene Fiber Reinforced on Properties of Concrete, Journal of Advance Research in Mechanical and Civil Engineering. Shakir, A., and Maha, E., 2008. Effect of polypropylene fibers on properties of mortar containing crushed brick as aggregate, Eng. And Tech., Vol. 26, No. 12, PP. 1508-1513. Wandowski, T., Malinowski, P., & Ostachowicz, W., 2021. Improving the EMI-based damage detection in composites by calibration of AD5933 chip. Measurement, 171, 108806. https://doi.org/10.1016/j.measurement.2020.108806. Y. Zhang, V. Adin, S. Bader and B. Oelmann, 2023. Leveraging Acoustic Emission and Machine Learning for Concrete Materials Damage Classification on Embedded Devices," in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-8, Art no. 2525108. Sonker, M., Shanker, R., 2025. Enhanced diagnostic approach for multiple damage detection and severity evaluation through EMI-based sensing and artificial neural network model. Asian J Civ Eng 26, 747 – 760.