Yao Yafeng, Zhu Yan, Li Yongheng, Wang Wei, Zhang Zhemei
School of Construction Engineering, Nantong Vocational University, Nantong, 226001, China.
AI and BIM Integrated Intelligent Construction Engineering Technology Research and Development Center, Nantong Vocational University, Nantong, 226007, China.
Sci Rep. 2024 Jul 6;14(1):15584. doi: 10.1038/s41598-024-65914-4.
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.
为解决传统可靠性理论在表征深部地下结构稳定性方面的不足，对先进的可靠性一阶二次矩进行改进以获得模糊随机可靠性，使其更符合工作条件。利用模糊随机优化对传统灵敏度分析模型进行优化，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改善模糊随机变量的数字特征。运用模糊随机灵敏度优化模型确定了混凝土抗压强度、厚径比、配筋率、计算模型不确定系数以及土层深度对深厚冲积土中钢筋混凝土双层井筒整体结构可靠性的影响。通过数值计算发现，这些特性是主要影响因素。此外，土层深度呈负相关，而其他影响因素均与整体可靠性呈正相关。本研究为未来深部地下结构的安全施工提供了有效参考。
