LAUSR

Abstract Grasping the temporal-spatial evolution of damage inside mechanically loaded structure contributes to providing essential information for engineering safety monitoring. Active ultrasonic (UT) and passive acoustic emission (AE) testing techniques both satisfy these demands and have been widely used in fields. The basic aim of this study is to realize UT and AE integrated monitoring and characterize the damage (microcracking) using the two methods synchronously under multi-step loading procedure for concrete specimens. The AIC approach and Levenberg-Marquardt optimizing algorithm were applied to determine onset time and realize the 3D AE source location, respectively. Some UT and AE parameters, such as ultrasonic pulse velocity (UPV), attenuation coefficient α , AE energy considering geometric attenuation E ae and AE hit occurrence frequency F ( τ ), were defined and extracted from the respective wave profiles. Then the UT-AE spatiotemporal varying responses associated with microcracking process and mechanical behavior were obtained experimentally and analyzed theoretically. Results show that: The UPV and α show an opposite time-varying tendency during the loading process owing to the linear statistical correlation between α and the reciprocal of UPV. While the time-varying responses of E ae and F ( τ ) both satisfy the time-scaling power-law relation, especially prior to failure. There are some interesting and remarkable phenomena observed during multi-step loading procedure which demonstrate that the damage evolution not only depends on the stress but also on the accumulative time. The 1D fiber-bundle model (FBM) is utilized and modified by the proposed incremental summation method to interpret this stress-time double cumulative effect on the damage and the observed responses specifically for the multi-step loading case. Additionally, the theoretical predicted UPV and AE energy ratios are given based on FBM, and all those theoretical results are in pretty good agreement with the experimental ones under acceptable error range, which demonstrates the validity of the proposed model.