Abstract
Health monitoring of structures using techniques based on the smart material is an innovative concept that is exploding technological revolutions in the field of civil engineering. The electro-mechanical impedance (EMI) technique is used for structural health monitoring (SHM) and to investigate the damages in the structures. The bacterial incorporation in concrete produces calcite material through metabolism process in presence of moisture and carbon dioxide, which improves the mechanical properties of concrete. Hence, its application in construction of the buildings will improve the health of structures. In this research paper, dynamic behaviour of the bacterial concrete was investigated numerically. The beams of size 700 × 150 × 150 mm of bacterial concrete and control concrete were modelled using finite element-based package ANSYS19. The beam of bacterial concrete was simulated as per the characteristics of the materials produced after the bacterial metabolism reactions. The EMI technique was applied to investigate the health of these beams. Admittance (conductance and susceptance) signatures were determined using piezo-ceramic lead zirconate titanate (PZT) sensors installed at mid-point on the top surface of concrete beams. The beams were exposed to dynamic loading and the intensity of dynamic loading was increased in four sub-steps. For the quantification of strength development in the concrete beam, the root mean square deviation (RMSD) statistical index had been applied. It was observed that the bacterial concrete beam has more resistance to the dynamic loading.
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The author would like to gratefully thank the Dept. of Civil Engineering and Structural Engineering lab of the Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India.
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Krishna Kumar Maurya: writing—original draft. Anupam Rawat: supervision. Rama Shanker: writing—review and editing.
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Maurya, K.K., Rawat, A. & Shanker, R. Health monitoring of bacterial concrete structure under dynamic loading using electro-mechanical impedance technique: a numerical approach. Environ Sci Pollut Res 30, 25382–25401 (2023). https://doi.org/10.1007/s11356-022-21949-6
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DOI: https://doi.org/10.1007/s11356-022-21949-6