Experimental study on evaluating fracture processes of different rocks using multiple physical parameters

Abstract

To improve the accuracy of rock fracture evaluation, three types of rocks with different lithologies, namely, granite, coal, and sandstone, were processed into cuboid samples with unilateral notches for three-point bending tests. Real-time data were obtained via load, resistance, and acoustic emission (AE) monitoring. Various fracture patterns of the fractured rocks were collected, and the correlations between multiple physical parameters were determined. The results indicated that granite had the highest fracture toughness and initial fracture energy required for macroscopic fracturing, followed by sandstone, which had the lowest fracture toughness and initial fracture energy. The primary crack participated in the fracture process of coal and produced the most complex crack morphology, exhibiting the characteristics of “Progressive fracture” different from the “Instantaneous fracture” of granite and sandstone. The crack length reached 90.5 mm, which was much longer than that of sandstone. The temporal characteristics obtained from multiple physical quantities were synchronized with the fracture behavior. The resistivity increased gradually with the fracture, and the resistivity fluctuation caused by crack propagation increased. The resistivity change rate of granite was the highest when macrofractures occurred, whereas that of coal after complete fracture was the highest. Rock fracture produced a large number of AE events with small amplitude and low peak frequency, concentrated in the 100 ± 50 kHz band. The AE count corresponded to the crack propagation process, and the AE location indicated the crack complexity. The peak change rate of the resistivity was used to evaluate the fracture performance and exhibited a significant linear relationship with the peak load, fracture toughness, and initial fracture energy. The relationship between the accumulated AE energy and the fracture length was a quadratic function, which was used to evaluate the fracture complexity. The multiple physical quantity monitoring method is promising for predicting the fracture behavior of rocks.