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Abstract：
To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.
摘要：
针对传统可靠度理论在表征深层地下结构稳定性方面的不足,改进了可靠度的先进一阶二阶矩，以获得模糊随机可靠度，这更符合工作条件。传统的灵敏度分析模型采用模糊随机优化,并建立了模糊随机可靠性灵敏度均值和标准差的解析计算模型。采用大数据隐马尔可夫模型和期望最大化算法来改善模糊随机变量的数字特性。采用模糊随机敏感性优化模型来确定混凝土抗压强度的影响,厚直径比，配筋率,计算模型的不确定性系数，和土层深度对深层冲积土中钢筋混凝土双层井筒整体结构可靠性的影响。通过数值计算,这些特征被认为是主要的影响因素。此外，而土壤深度呈负相关，其他影响因素均与总体信度呈正相关。该研究为今后深层地下结构的安全施工提供了有效的参考。
