Abstract
The discrete fracture network model is a powerful tool for fractured rock mass fluid flow simulations and supports safety assessments of coal mine hazards such as water inrush. Intersection analysis, which identifies all pairs of intersected fractures (the basic components composing the connectivity of a network), is one of its crucial procedures. This paper attempts to improve intersection analysis through parallel computing. Considering a seamless interfacing with other procedures in modeling, two algorithms are designed and presented, of which one is a completely independent parallel procedure with some redundant computations and the other is an optimized version with reduced redundancy. A numerical study indicates that both of the algorithms are practical and can significantly improve the computational performance of intersection analysis for large-scale simulations. Moreover, the preferred application conditions for the two algorithms are also discussed.
Highlights
Water inrush is one of the most concerning safety problems in coal production
The discrete fracture network model is a powerful tool for fractured rock mass fluid flow simulations and supports safety assessments of coal mine hazards such as water inrush
Intersection analysis, which identifies all pairs of intersected fractures, is one of its crucial procedures
Summary
Water inrush is one of the most concerning safety problems in coal production. Fractures act as channels for fluid flows that are highly relevant to this type of disaster. A revised method was proposed in which the entire process of intersection analysis can be implemented in a stepwise manner (Yu et al 2006) The concept of this approach is based on the theory of computer graphics, where each fracture is wrapped inside an individual bounding box, and the spatial relation between the boxes is analyzed in the first step, a procedure known as ‘coarse analysis’. Because the computation cost for a single analysis on one pair of bounding boxes is far less than that of the fractures themselves, the stepwise procedure reduces the total execution time of a high-cost algorithm (precise analysis) by introducing a preprocessing technique such as a low-cost algorithm (coarse analysis) that acts as a filter This approach can result in a considerable performance gain compared to the traditional method where the precise analysis is used alone.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Coal Science & Technology
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.
