Nonlinear acoustics-based nondestructive evaluation (NDE) techniques have shown great promise for identification of microstructure and microcracking in a wide spectrum of materials (e.g., metals, metallic alloys, composites, rocks, cementitious materials).… Click to show full abstract
Nonlinear acoustics-based nondestructive evaluation (NDE) techniques have shown great promise for identification of microstructure and microcracking in a wide spectrum of materials (e.g., metals, metallic alloys, composites, rocks, cementitious materials). This class of NDE techniques relies on measuring nonlinearity parameters by analyzing the acoustic response of materials that are dynamically perturbed at microstrain levels (strain $$\sim $$∼10$$^{-6}$$-6–10$$^{-5})$$-5). Using a mechanical impact to induce microstrain is advantageous for concrete testing because it allows for testing of larger concrete specimens offering potential field transportability. In this paper, two impact-based nonlinear acoustic testing techniques are compared: impact-based nonlinear resonant acoustic spectroscopy (INRAS) and dynamic acousto-elastic testing (IDAET). INRAS gives a global measure of sample hysteretic nonlinearity while IDAET provides a local but comprehensive account of nonlinear elastic properties. We discuss single- versus multi-impact INRAS and propose a physics-based model to describe the data from single-impact INRAS. Then, we introduce IDAET and demonstrate how to extract both classical and non-classical nonlinear parameters from a limited set of test results. INRAS and IDAET are used to monitor the evolution of damage in two sets of concrete samples undergoing freeze-thaw (FT) cycles. Nonlinear parameters extracted from the two tests show good agreement; all exhibiting far more sensitivity to distributed FT damage than standard (i.e. linear) resonance frequency measurements. By presenting alternative ways to collect and analyze the impact-based nonlinear acoustic test data, this study will help in broadening their use and extending their applications to quantitative in-situ evaluation.
               
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