• Title/Summary/Keyword: contact acoustic nonlinearity

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Evaluation of Ultrasonic Nonlinear Characteristics in Heat-Treated Aluminum Alloy (열처리된 알루미늄 합금의 초음파 비선형 특성 평가)

  • Kim, JongBeom;Cheon, Chung;Jhang, Kyung-Young;Kim, Chung-Seok
    • Journal of the Korean Society for Nondestructive Testing
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    • v.33 no.2
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    • pp.193-197
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    • 2013
  • In this study, ultrasonic nonlinear characteristics in the heat-treated aluminum alloy have been evaluated. The nonlinearity of ultrasonic wave has been measured as the acoustic nonlinear parameter ${\beta}$, depending upon the amplitude ratio of the second-order harmonic and the fundamental frequency component of ultrasonic wave propagating through the materials. The parameter ${\beta}$ measurement has been carried out with the reflected signals from the back-wall of specimens at the same plane using the contact-type transducers. The heat-treatment, aging, has been achieved at $300^{\circ}C$ for various durations in the range of 1 to 50 hours. The tensile strength and elongation are obtained by the tensile test and then compared with the parameter ${\beta}$. There is a peak of the acoustic nonlinear parameter ${\beta}$ on 5 hours aging and the ${\beta}$ decreases thereafter, exhibiting closed relations with tensile strength and elongation. Also, the heat-treatment time showing peak in the parameter ${\beta}$ was identical to that showing severe change in the ${\sigma}-{\varepsilon}$ curve. These results suggest that the acoustic nonlinear parameter ${\beta}$ can be used for monitoring the strength variations with aging of aluminum alloys.

Artificial neural network model using ultrasonic test results to predict compressive stress in concrete

  • Ongpeng, Jason;Soberano, Marcus;Oreta, Andres;Hirose, Sohichi
    • Computers and Concrete
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    • v.19 no.1
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    • pp.59-68
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    • 2017
  • This study focused on modeling the behavior of the compressive stress using the average strain and ultrasonic test results in concrete. Feed-forward backpropagation artificial neural network (ANN) models were used to compare four types of concrete mixtures with varying water cement ratio (WC), ordinary concrete (ORC) and concrete with short steel fiber-reinforcement (FRC). Sixteen (16) $150mm{\times}150mm{\times}150mm$ concrete cubes were used; each contained eighteen (18) data sets. Ultrasonic test with pitch-catch configuration was conducted at each loading state to record linear and nonlinear test response with multiple step loads. Statistical Spearman's rank correlation was used to reduce the input parameters. Different types of concrete produced similar top five input parameters that had high correlation to compressive stress: average strain (${\varepsilon}$), fundamental harmonic amplitude (A1), $2^{nd}$ harmonic amplitude (A2), $3^{rd}$ harmonic amplitude (A3), and peak to peak amplitude (PPA). Twenty-eight ANN models were trained, validated and tested. A model was chosen for each WC with the highest Pearson correlation coefficient (R) in testing, and the soundness of the behavior for the input parameters in relation to the compressive stress. The ANN model showed increasing WC produced delayed response to stress at initial stages, abruptly responding after 40%. This was due to the presence of more voids for high water cement ratio that activated Contact Acoustic Nonlinearity (CAN) at the latter stage of the loading path. FRC showed slow response to stress than ORC, indicating the resistance of short steel fiber that delayed stress increase against the loading path.