基于深基坑监测数据的土体小应变刚度参数优化分析

Optimization analysis of the soil small strain stiffness parameters based on deep foundation pit monitoring data

考虑土体小应变特性的HSS模型在深基坑的数值分析中得到较多的应用,但受试验条件的限制,其刚度参数往往不易获得。为对HSS模型的初始剪切模量G_0^(ref)、小应变参数r_(0.7)、三轴实验割线模量E_(50)^(ref)等三个刚度参数进行优化分析,以厦门市某一地铁深基坑工程为依托,基于施工过程的实测数据,提出一套简便易行的刚度参数优化方法。基于地表沉降和围护墙水平变形的实测数据,以修正后的极差和标准差为收敛指标,对深基坑的浅部开挖工况进行弹塑性位移反分析;然后对深部开挖工况继续进行优化分析,通过不同工况、不同断面的实测数据进行若干次参数优化,可将收敛误差控制到较小范围内;最后得出厦门地区代表性土层淤泥质土、粉质粘土、残积砂质粘性土的刚度优化参数,积累了土工参数的地区经验值。该方法不仅可用于刚度优化分析,也可用来预测深基坑开挖引起的周边环境风险。

HSS model with the consideration of the soil small strain characteristics has been largely applied in the numerical analysis of the deep foundation pit. However, restricted to the experimental conditions, the stiffness parameters are not easy to be obtained. In order to apply optimization analysis for the three stiffness parameters of HSS model, which are initial shear modulus, small strain parameters and triaxial experimental secant modulus, a simple and applicable stiffness parameter optimization method is introduced based on the field measurements from a subway deep foundation pit project in Xiamen. Based on the measured data of the surface subsidence and horizontal deformation of the enclosure wall, the elastic-plastic displacement caused by shallow excavation of the deep foundation pit is firstly back analyzed in conjunction with the modified range and standard deviation being taken as the convergence criteria, and then displacement resulted from next excavation is analyzed on the basis of the former optimized parameters which would be further optimized according to relevant measurements. Results show that, with very few repetitions of the above analyses for different sections and various conditions, errors between the predictions and measurements would fall into a small enough range, and the optimizations can be completed. Through this study, the optimal stiffness parameters of the representative soils in Xiamen area, including silty soil, silt clay and residual sandy soil, are obtained, which would enrich the regional experience in parameter choices in future geotechnical analysis. Moreover, the proposed method can not only be used for stiffness optimization analysis, but also be applied for the prediction of the risk of the surrounding environment caused by excavation.