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中等、微风化岩Rc合并统计造成的偏差分析

Analysis of Deviation Caused by Rc Merging Statistics of Moderately and Slightly Weathered Rocks

  • 摘要: 准确评估中等风化岩和微风化岩的饱和单轴抗压强度(Rc)对于岩土工程设计和安全评估至关重要。然而,目前对于这两种岩石的抗压强度在合并统计时的统计偏差和失效概率变化尚不明确。本研究旨在通过广州市某工程实例,对中等风化岩和微风化岩的Rc进行统计分析,评估合并统计对数据分布特征和失效概率的影响。本研究分别对中等风化岩和微风化岩的Rc数据进行统计分析,计算常规统计量(如均值、标准差等)。将两种岩石的Rc数据合并后进行统计分析,计算常规统计量、数据集中区间、离散程度、密度函数的估计以及失效概率。对比分层统计和合并统计的结果,分析合并统计对数据分布特征和失效概率的影响。结果表明:合并统计后,常规统计量的代表性明显降低。合并统计后的数据分布偏离了统计基本假设,导致失效概率显著提高。合并统计并不保守,可能会低估工程风险。本研究方法具有较强的可操作性,是工程勘察领域的首次提出,具有一定的推广应用价值。

     

    Abstract: Accurate assessment of the saturated uniaxial compressive strength (Rc) of moderately weathered rock and slightly weathered rock is crucial for geotechnical engineering design and safety evaluation. However, the statistical deviations and variations in failure probabilities resulting from merging the Rc statistics of moderately and slightly weathered rocks remain unclear. This study aims to conduct a statistical analysis of Rc for moderately weathered rock and slightly weathered rock through an engineering case study in Guangzhou, evaluating the impact of merging statistics on data distribution characteristics and failure probabilities. This study separately analyzes the Rc data of moderately and slightly weathered rocks, calculating conventional statistics (e.g., mean, standard deviation, etc.). Subsequently, the Rc data of the two rock types were merged to calculate conventional statistics and estimate the central tendency range, degree of dispersion, density function, and failure probabilities of the data. By comparing the results of stratified statistical analysis and merged statistical analysis, the impact of Merging Statistics on data distribution characteristics and failure probabilities was analyzed. The results indicate that the representativeness of conventional statistical measures significantly decreases after merging statistical analysis. The merged Rc data distribution deviates from fundamental statistical assumptions, leading to a substantial increase in failure probabilities. Merged statistical analysis is not conservative and may underestimate engineering risks. The proposed methodology demonstrates strong practicality and represents the first proposal in the field of engineering investigation, possessing certain value for promotion and application.

     

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