Abstract
A comprehensive nonlinear seepage simulation study for rough fractures remains technically challenging due to the number of indoor tests and computational volume of numerical simulations. This study fills this gap by developing a cosimulation program to accomplish the automatic cycling of rough fracture modelling and nonlinear fracture seepage simulation. With the developed cosimulation program, 81 sets of rough fracture models are generated, and 427 sets of seepage simulations are performed. Combined with a theoretical analysis, the mechanism of the effects of roughness and fracture aperture on the flow field structure during nonlinear seepage is determined. The equivalent hydraulic aperture (EHA) is introduced as an index to quantitatively evaluate the fluid transport efficiency in the seepage process. The results show that there is a linear relationship between the fracture aperture and the EHA and a logarithmic relationship between the fracture roughness and the EHA. Finally, a regression prediction model of EHA with roughness and average fracture aperture characteristics is established through regression analysis, and a neural network prediction model of EHA is established based on a BP neural network optimized by an SSA algorithm. The developed models are verified to provide high accuracy for EHA prediction.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.