Effect of dynamic disturbances and dry-wet cycles on the degradation law and acoustic emission evolution characteristics of argillaceous sandstone: An experimental study

• Published in: Journal of applied geophysics Vol. 241; p. 105860
• Main Authors: Long, Nengzeng, Wu, Fei, Ren, Song, Chen, Zheng, Zhang, Ping, Zhang, Chuang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2025
• Subjects: Acoustic emission characteristics; Argillaceous sandstone; Deep learning model; Degradation; Dry-wet cycles; Dynamic disturbance; Degradation; Dynamic disturbance; Acoustic emission characteristics; Argillaceous sandstone; Deep learning model; Dry-wet cycles
• ISSN: 0926-9851
• DOI: 10.1016/j.jappgeo.2025.105860

In order to gain an in-depth understanding the influence of dynamic disturbances and dry-wet cycles on the degradation and damage of argillaceous sandstone, the uniaxial compression and acoustic emission (AE) monitoring tests were carried out under different dynamic disturbance amplitudes (r) and number of dry-wet cycles(n) in this study. The results indicate that when the UCS exceeds 20 %, the argillaceous sandstone begins to deteriorate, and the mechanical parameter variations exhibit a distinct Poly 2D function relationship with the r and n. The evolutionary characteristics of acoustic emission parameters can be divided into the active, calm, critical, and abrupt periods. By analyzing the evolution trend of cracks using the k-means clustering algorithm and AE localization, it was found that with the increase of r (20 % to 60 % UCS) and n, the tensile cracks in argillaceous sandstone gradually transitioned into composite and shear cracks. The deep learning model recognition accuracy for the test and validation samples reaching 89.27 % and 80.62 %, respectively. The research results are of guidance values for improving the operation safety and stability of muddy sandstone slope projects.