煤炭损伤样本中裂纹识别和时空演变模式的调查
Zeng Chen1,2, Ping Wang3,4, Feng Shi3,4
1BGRIMM Technology Group, Building 23, Zone 18 of ABP, No. 188, South 4th Ring Road West, Beijing, 100160, People's Republic of China. zschenzeng@126.com.
Scientific reports
|October 20, 2023
概括
了解煤裂的演变是岩石质量的稳定性的关键. 声辐射实验揭示了微裂纹模式,并使用时空和碎形维度预测不稳定性.
科学领域:
- 岩石机械学 岩石机械学
- 地质物理学 地质物理学
- 材料科学 材料科学 材料科学
背景情况:
- 岩石质量中的裂演变对于理解质量行为和不稳定性至关重要.
- 声波发射 (AE) 技术为裂传播机制提供了洞察力.
研究的目的:
- 为了研究在单轴压缩下煤炭中微裂纹的时空演变.
- 分析裂纹分布模式,时空 (H) 和碎形维度 (D) 之间的关系.
- 为了确定煤样本不稳定性的前体信息.
主要方法:
- 在煤样品上进行单轴压缩试验.
- 同时定位和监控声波排放.
- 集群理论的应用来分析微裂分布.
- 计算和分析时空 (H) 和碎形维度 (D).
- 机器学习用于裂识别.
主要成果:
- 微裂呈现出统计平衡分布,符合高斯模型.
- 分形维度 (D) 与3D圆裂的空间特征相关.
- 低维的集群裂容易发展成宏观的裂.
- 时空 (H) 的变化与裂形成过程有关.
结论:
- 时空 (H) 的异常变化可以作为煤样本不稳定的前体.
- 该研究提出了一种分析裂分布和形成的新方法.
- 拟议的方法在评估煤炭损害状态方面表现出有效性.
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