journal article·2022-12Open access

Monitoring the behaviour of seven storeyed RC frame subjected to reversed cyclic loading by nonlinear NDT

Selvakumar Anbarasan, Thirumurugan Varatharajan, Satyanarayanan Kachabeswara Srinivasan

Abstract

Large-scale structures are more prone to risk than small-scale structures due to their increased weight, stiffness and ductility parameters. The main focus of this investigative study is on the structural monitoring of a building using the non-destructive method of non-linear ultrasonic pulse velocity. A single-bay seven-storeyed frame model subjected to reverse cyclic loading of varying amplitudes is monitored by non-linear ultrasonic technique based on third harmonic wave generation. The critical nodes are identified in two different ways: the points of possible plastic hinge formation (PPPHF) through the theoretical background of plastic hinge analysis and the highly sensitive regions in structures (HSR) through numerical analysis. The common nodes of PPPHF and HSR are considered to monitor the structure. The invisible primary structural damage in the initial stage and the visible structural damage up to ultimate load are observed using non-linear ultrasonic waves. The fundamental frequency value and the third harmonic frequency value are observed and processed in MATLAB in the form of a Fast Fourier Transform (FFT) algorithm. The relationship between the condition of the structure and the ratio of third harmonic parameter, load and displacement is compared. In the initial stage of loading, only slight change or no variation in third harmonic ratio is observed at the observation points indicating material disintegration. This varies consistently up to the development of visible cracks and the same varies inconsistently on further loading after the appearance of visual cracks.
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Research context

OpenAlex topics: Ultrasonics and Acoustic Wave Propagation · Structural Health Monitoring Techniques · Geophysical Methods and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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