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Linear fractal evolution characteristics of rock crack distributions during loading process
Jingyi Huang1, Xu Wei2,3, Zaimin Zheng4
1School of Civil Engineering, Chongqing Jiaotong University, Chongqing, 400074, China.
Scientific Reports
|August 7, 2024
Summary
This study reveals a linear relationship between rock crack fractal dimension and strain ratio. A novel damage-fracture reduction factor, derived from this relationship, effectively quantifies rock sample damage and failure patterns.
Area of Science:
- Geotechnical Engineering
- Fracture Mechanics
- Computational Rock Physics
Background:
- Rock fracture mechanics is crucial for understanding geological stability.
- Quantifying rock damage and fracture patterns under loading is complex.
- Fractal geometry offers a potential framework for analyzing complex crack networks.
Purpose of the Study:
- To investigate the fractal characteristics of rock crack distributions during loading.
- To establish a quantitative relationship between crack fractal dimension and strain ratio.
- To develop a new metric for assessing rock damage and fracture patterns.
Main Methods:
- Discrete Element Method (DEM) simulations of rock samples with joints.
- Crack propagation monitoring during simulated loading.
- Box-counting method for quantitative fractal dimension analysis.
- Establishing a linear relationship between fractal dimension and strain ratio.
Main Results:
- A strong linear correlation was observed between crack fractal dimension and strain ratio.
- A damage-fracture reduction factor was identified from the slope of the linear function.
- This factor effectively categorizes failure modes: spilt/fracture (0.25-0.5), fracture/damage synergy (0.5-0.9), and microcrack damage (0.9-1).
- The findings were validated through acoustic emission and crack extension experiments.
Conclusions:
- The study demonstrates linear fractal characteristics in rock crack distributions under load.
- The damage-fracture reduction factor provides a geometric basis for damage assessment.
- This approach offers a novel method for predicting rock failure patterns and degrees of damage.
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