LI Ning, ZHANG Hai-yue, GAO Shu-ling, LI Zhong-xian. DETECTION AND VALIDATION FOR DEBONDING IN CFST USING ULTRASONIC ENERGY DIFFUSION TEST METHOD[J]. Engineering Mechanics, 2023, 40(1): 111-120. DOI: 10.6052/j.issn.1000-4750.2021.07.0576
Citation: LI Ning, ZHANG Hai-yue, GAO Shu-ling, LI Zhong-xian. DETECTION AND VALIDATION FOR DEBONDING IN CFST USING ULTRASONIC ENERGY DIFFUSION TEST METHOD[J]. Engineering Mechanics, 2023, 40(1): 111-120. DOI: 10.6052/j.issn.1000-4750.2021.07.0576

DETECTION AND VALIDATION FOR DEBONDING IN CFST USING ULTRASONIC ENERGY DIFFUSION TEST METHOD

  • In recent years, concrete-filled steel tubular (CFST) composite members have been widely used in various engineering structures because of their excellent axial compression, bending and shear resistance capacities. For the construction process of CFST, the debonding defects between the steel tube and concrete will destroy the synthesis confined effect between them, leading to the reduction of bearing capacity. In serious cases, the structure will experience a large safety danger and high collapse probability under severe external excitations. Therefore, it is necessary to research the debonding detection of CFST. This study built the testing facility and framework with the ultrasonic energy diffusion test method. A series of tests were carried out for CFST with different dimensions of artificial debonding defects using ultrasonic waves at different frequencies. The linear fitting of the normalized diffusion and dissipation coefficients are chosen as the evaluation indexes, and the influence of different frequencies and the different sizes of debonding defects on the signals of the square CFST columns with debonding defects was studied. At last, based on the optimal excitation frequency, a model for determining the debonding defects of CFST was proposed, and COMSOL was used for numerical simulation verification. The results show that the diffusivity and dissipation coefficients are sensitive and varying with the size of the debonding defects, which can be chosen as important parameters for a defect detection. Based on the test and numerical verification, the test criteria has a favorite error, the minimum error is 3.03%, and the average error is less than 10%. The proposed model can quantitatively identify the debonding defects between the steel tube and the core concrete. Further, the proposed test method can do similar detection for CFST structural members.
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