Microseismic Signal Characterization and Numerical Simulation of Concrete Beam Subjected to Three-Point Bending Fracture

Abstract

To study the generation mechanism and failure mode of cracks in mass concrete, microseismic monitoring is conducted on the fracture processes of the three-point bending roller compacted concrete (RCC) beam of Guanyinyan hydropower station. The spectrum characteristics of microseismic signals in different deformation and failure stages of the concrete beam are analyzed, and the identification method of the fracture stages and crack propagation precursors of concrete beam is established. Meanwhile, the Realistic Failure Process Analysis code (RFPA) is adopted to simulate and analyze the entire failure processes of concrete beam from its cracks initiation, development, propagation, and coalescence, until macroscopic fractures formation subjected to three-point bending test. The relation curve of the load, loaded displacement, and acoustic emission (AE) of concrete beam in the three-point bending test is also obtained. It is found that the failure characteristics of concrete beam obtained from numerical experiments agree well with the field physical test results. The heterogeneity of concrete is the major cause of zigzag propagation paths of beam cracks subjected to three-point bending tests. The results lay foundation for further exploring the formation mechanism of dam concrete cracks of Guanyinyan hydropower station.

Stability analysis of Xiluodu Hydropower Station right bank slope based on discontinuous deformation analysis method

“…(2015) observed that the dominant frequencies are in the low-frequency (approximately 3 kHz) and high-frequency (6–10 kHz) bands. In the present study, the sensor frequency range is 0.05–10 kHz, which is wider than that proposed by Xu et al. (2015).…”

“…The dominant micro-seismic signal frequencies in the plastic deformation and failure deformation stages of rock mass are in the kilohertz order (Zhuang et al, 2019). Xu et al (2015) observed that the dominant frequencies are in the low-frequency (approximately 3 kHz) and high-frequency (6-10 kHz) bands. In the present study, the sensor frequency range is 0.05-10 kHz, which is wider than that proposed by Xu et al (2015).…”

“…, 2019). Xu et al. (2015) observed that the dominant frequencies are in the low-frequency (approximately 3 kHz) and high-frequency (6–10 kHz) bands.…”

Time difference of arrival estimation of microseismic signals based on alpha-stable distribution

“…However, these algorithms are all based on the second-order statistics and the assumption that the noises follow the Gaussian distribution. In the process of microseismic monitoring, noisy signals are non-Gaussian and their pulse characteristics are obvious (Xu et al, 2015;Jia et al, 2016). Therefore, Eq.…”

“…Since the classic article on TDOA written by Knapp and Carter was published in 1976, this problem has perpetually been a research focus in the field of international signal processing (Knapp et al, 1976). The common method of TDOA includes the generalized cross correlation method (Knapp et al, 1976;Souden et al, 2010;Jin et al, 2013), the phase spectrum estimation method (Youn et al, 1982;Qiu et al, 2012), the generalized bi-spectral estimation method (Hinich et al, 1992;Hou et al, 2013), the adaptive estimation method (Gedalyahu et al, 2010;Salvati and Canazza, 2013), the energy method based on HilbertHuang transform and so on. These methods have been widely used in many fields.…”