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Study on material point failure probability of complex jointed rock masses based on peridynamics
Yigong Zhao1, Xiaoyan Zhang2, Ze Li3
1Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming, 650500, Yunnan, China.
This study uses peridynamics (PD) and Monte Carlo simulations to analyze how joint dip angles affect rock mass failure. It introduces methods to identify key joints, improving predictions for geotechnical engineering.
Area of Science:
- Rock Mechanics
- Geotechnical Engineering
- Computational Mechanics
Background:
- Rock mass failure prediction is complex due to randomly distributed joints.
- Key joints significantly influence rock mass fracturing and failure paths.
Purpose of the Study:
- To investigate the impact of varying joint dip angles in complex joint networks on rock mass failure probabilities.
- To develop quantitative assessment tools for rock mass failure prediction.
- To introduce concepts for identifying key and non-key joints.
Main Methods:
- Peridynamics (PD) method combined with Monte Carlo simulation analysis.
- Development of efficient parallel computing programs for large-scale simulations.
- Introduction and application of material point failure probability (PFP) and Joint Angle Impact Coefficient (JAIC) contour maps.
Main Results:
- Demonstrated the influence of joint dip angles on rock mass failure probabilities in complex networks.
- Generated grid-based PFP and JAIC contour maps for quantitative assessment.
- Introduced grid-based concepts of key and non-key joint dip angles.
Conclusions:
- Established statistical methods for identifying key and non-key joints in rock mass grid regions.
- Provided new perspectives and tools for understanding and predicting rock mass failure.
- Contributed to rock mechanics reliability studies and geotechnical engineering guidance.
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