A new method of modelling the rock microfracturing process in double-torsion experiments using neural networks

作者：Feng XT^*; Seto M

来源：International Journal for Numerical and Analytical Methods in Geomechanics, 1999, 23(9): 905-923.

DOI：10.1002/(SICI)1096-9853(19990810)23:9<905::AID-NAG11>3.0.CO;2-F

• rock microfracturing
• self-similarity
• fractal
• neural network
• double torsion
• acoustic emission

Microfracturing of rock is a complicated damage evolution process. Inaccurate prediction of micro-fracturing behaviours suggests a need for the development of a better modelling method. Analysis of acoustic emission (AE) measurements in double-torsion tests indicates that micro-fracturing behaviours during the loading stage have fractal time structures. This fractal behaviour can be described by C(t) proportional to t(D), where D is the correlation exponent, t is the time and C(t) is the correlation integral. Furthermore, by utilizing measured AE data, a new method has been developed to model the AE behaviours of micro-fracturing in rock, in air, and following soaking in water and in a chemical solution of DTAB. The neutral models NN(10,21,2) and NN(10,20,2) were found to describe reasonably well the AE behaviours of micro-fracturing in rock under air and DTAB conditions, and water conditions, respectively. The cumulative AE events and the cumulative AE counts predicted by the neural models agreed well with those measured in experiments.

• 出版日期1999-8-10
• 单位东北大学