基于随机场理论的隧道开挖后地表及隧道变形分析OA北大核心CSTPCD
Analysis on surface and tunnel deformation after tunnel excavation based on random field theory
天然土体由于受到多因素的影响,土体参数存在着内在的不确定性.为了更好地反映实际土体参数的分布情况,基于随机场理论,在考虑黏聚力和内摩擦角空间变异性的情况下,利用乔列斯基分解和随机有限元模型相结合的方法,对地表和隧道变形进行分析.研究结果表明:地表沉降曲线簇的波动范围随着黏聚力和内摩擦角相关距离的增大而增大,其竖直相关距离对地表沉降变形的影响更明显;黏聚力和内摩擦角的变异系数对地表沉降变形的影响强于其相关距离对地表沉降变形的影响;隧道变形值的分布随着黏聚力和内摩擦角变异系数的增大而逐渐离散,其中内摩擦角变异系数对隧道变形值分布的影响更明显;不考虑黏聚力和内摩擦角的空间变异性将偏小地预测地表沉降和隧道变形,使设计偏于危险.
Natural soil has inherent uncertainties due to the influence of multiple factors.In order to better reflect the distribu-tion of actual soil parameters,a combination of Cholesky decomposition and stochastic finite element model was utilized to analyze the surface and tunnel deformation based on random field theory,in which the spatial variability of cohesion and internal friction angle were taken into account.The results indicated that the fluctuation range of the surface settlement curves cluster expanded with the increasing of related distance of cohesion and internal friction angle,and the effect of vertical related distance on surface settlement deformation was more significant.Furthermore,the influence of the cohesion variation coefficient and internal friction angle on surface settlement deformation was stronger than the effect of related distance.In addition,the distribution of the tunnel deformation values scattered with the increasing of the coefficient of variation of cohesion and internal friction angle,in which the coefficient of variation of internal friction had much influences.Neglecting the spatial variability of cohesion and internal friction angle could result in underestimating the predicted surface settlement and tunnel deformation,making the design more risky.
王勤;阎龙;张海莹;刘利骄;柳艳杰
黑龙江大学 建筑工程学院,黑龙江 哈尔滨 150080
交通运输
隧道开挖地表沉降曲线簇随机场空间变异性相关距离随机有限元模型
tunnel excavationground surface settlement curverandom fieldspatial variabilitycorrelation distancesto-chastic finite element model
《人民长江》 2024 (007)
229-239,253 / 12
国家自然科学基金项目(41071049);中国地震局工程力学研究所基本科研业务费专项资助项目(2021D13);黑龙江省自然科学基金项目(LH2023D022)
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