Author: S M Arafath Uzzaman
Uzzaman, S M Arafath, 2024 THERMO ELASTIC STRESS ANALYSIS FOR DETECTION OF DAMAGE IN BEAMS, Flinders University, College of Science and Engineering
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The effectiveness of thermoelastic stress analysis (TSA) for finding flaws in metal structural components is evaluated in this study. The study investigates the impact of varying loading conditions and defect locations on the efficacy of TSA in identifying damages. Experimental procedures involved cyclical bending loading to evaluate the effects of frequency and displacement on damage detectability. Additionally, a Finite Element model was developed to validate its accuracy under different load conditions and frequencies. The findings indicate that TSA is highly effective in precisely detecting and locating internal defects. Higher load amplitudes enhance detectability by reducing data noise, thus facilitating defect identification. In-plane amplitude measurements are particularly effective for detecting surface-level damages, while quadrature amplitude measurements excel in identifying defects by high peaks in the results section. Both high and low frequencies can identify damage locations; however, lower frequencies introduce noise into the results. There is a nonlinear link between TSA amplitude levels and frequency that needs further research. Although there is still need for further research on the implications of load signal frequency, the Finite Element model accurately covers a variety of cyclic bending loading scenarios. All things considered; this study validates TSA as a very effective full-field non-destructive testing technique for finding internal flaws in metals. Subsequent investigations need to look more into the nonlinear correlation between frequency and TSA amplitude levels, as well as expand on the potential of TSA.
Keywords: Thermoelastic stress , Finite Element Analysis, Frequencies, Beams
Subject: Engineering thesis
Thesis type: Masters
Completed: 2024
School: College of Science and Engineering
Supervisor: Dr. Stuart Wildy