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运用学生 t 分布和蒙特卡罗模拟方法研究裂隙岩石的闭合应力和裂纹起裂应力。

Investigating the closure stress and crack initiation stress in fractured rocks using the student t distribution and Monte Carlo simulation method.

机构信息

Department of Civil Engineering, Chongqing Three Gorges University, Wanzhou, Chongqing, China.

出版信息

PLoS One. 2024 Aug 7;19(8):e0307804. doi: 10.1371/journal.pone.0307804. eCollection 2024.

Abstract

Traditional method of determining closure and initiation stress of fractured rocks by analyzing the stress-strain curve has problems such as strong subjectivity and large errors. This study utilized the rock closure stress values and onset stress values determined by three traditional methods, namely, axial strain method, fracture volume method and empirical value taking method, as the base database. The Student t distribution theory was used to obtain a confidence interval based on its overall distribution of values and to achieve a combination of the advantages of multiple methods. Within confidence interval, the Monte Carlo stochastic simulation was used to determine the convergence interval of the second stage to further improve the accuracy. Finally, mean value of the randomly sampled values after reaching the convergence stage was taken as the probability value of rock closure and crack initiation stress. The results showed that the 3 traditional methods for calculating rock closure and initiation stresses are significantly different. In contrast, the proposed method biases more towards multi-numerical distribution intervals and also considers the preference effects of different calculation methods. In addition, this method does not show any extreme values that deviate from the confidence intervals, and it has strong accuracy and stability compared to other methods.

摘要

传统的通过分析应力-应变曲线来确定断裂岩石闭合和起始应力的方法存在主观性强、误差大等问题。本研究利用轴向应变法、体积断裂法和经验取值法这三种传统方法确定的岩石闭合应力值和起始应力值作为基础数据库。利用学生 t 分布理论,根据其整体分布值获得置信区间,实现多种方法的优势组合。在置信区间内,采用蒙特卡罗随机模拟确定第二阶段的收敛区间,进一步提高精度。最后,在达到收敛阶段后,对随机抽样值的平均值进行取值作为岩石闭合和裂缝起始应力的概率值。结果表明,3 种传统的计算岩石闭合和起始应力的方法存在显著差异。相比之下,提出的方法更偏向于多数值分布区间,同时考虑了不同计算方法的偏好效应。此外,该方法没有出现任何偏离置信区间的极端值,与其他方法相比,具有较强的准确性和稳定性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a35a/11305555/312455f7437d/pone.0307804.g001.jpg

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