Jin, Jiang | Engineering Papers

DOE OSTI2019

An integrated analytical and experimental study of contact acoustic nonlinearity at rough interfaces of fatigue cracks

This paper presents an analytical model that describes the relationship between interface stiffness and separation of rough interfaces such as fatigue cracks. The contact acoustic nonlinearity at the interface is simulated by a quasi-static model based on Hertzian contact theory. The model is validated using the results of dynamic acoustoelastic testing (DAET) with a Rayleigh wave probe on fatigue cracks in two aluminum alloy samples. One novel aspect of this work is that all the required geometrical parameters for the model are acquired directly from the aperture profile of real cracks extracted from their scanning electron microscopy (SEM) images. Also, the separation of the crack faces during dynamic perturbation is independently measured using a 3D laser Doppler vibrometer (LDV). In addition, using DAET allows for an unprecedented direct comparison between experimental and analytical results. Overall, this is because unlike conventional nonlinear ultrasonic tests that are based on measuring the amplitude of higher harmonics, DAET outputs directly the strain-dependency of transmission and time delay of ultrasonic waves propagating across the interface. The model is found in good qualitative agreement with the experimental results, although the predictions tend to underestimate the variation of transmission coefficient and time delay. We conduct a sensitivity analysis to investigate the influence of different assumptions and simplifications on model predictions.

36 MATERIALS SCIENCE↗

DOE OSTI2019

A data-driven approach to construct a quantitative relationship between microstructural features of fatigue cracks and contact acoustic nonlinearity

This study demonstrates the feasibility of a data-driven approach to construct a quantitative relationship between nonlinear acoustic parameters and microstructural features of contact interfaces. The near-surface nonlinearity is measured using dynamic acousto-elastic testing (DAET) with a surface wave probe, while the microstructural features are extracted from scanning electron microscopy (SEM) images of fatigue cracks. Four aluminum alloy samples, each having a fatigue crack are prepared. Six local nonlinearity parameters are measured at different locations along the crack propagation direction. A total of 40 local measurements are acquired. A principal component analysis (PCA) reveals that all six nonlinearity parameters are correlated and hence can be replaced by one principal component (PC). Fifteen crack micro-geometrical features at each measurement point were extracted from the SEM images. Regression analysis is used to relate the PC of the nonlinearity parameters to the microstructural features at the crack interface. We compare three regression models that take variable selection into account: stepwise multiple linear regression (MLR), stepwise principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO). Despite having different principles, the three predictive models identify two features as the most significant in predicting the interface nonlinearity: the crack aperture (opening) distribution and the distance to the crack tip. The differences between the three models and the physical interpretation of the data-driven predictions are discussed.

36 MATERIALS SCIENCE↗