Abstract: To address the challenges of severe soil sampling disturbance and the inability of traditional empirical values to reflect the true mechanical behaviors of the Modified Cam-Clay (MCC) model parameters for Wenzhou soft soil, an intelligent inversion method combining an Improved Latin Hypercube Sparrow Search Algorithm (ILHSSA) and finite element software was proposed. First, based on a typical deep foundation pit project in Wenzhou soft soil, the prior parameter inversion intervals were delineated using geological investigation reports. Through local sensitivity analysis via a 3D finite element model, dimensionality reduction was conducted, and a four-dimensional inversion hyperplane was established with M, λ,κ,and e? as variables. Second, to overcome the limitation of fitting errors commonly introduced by static surrogate models, a dynamic co-simulation framework interacting between MATLAB and ABAQUS was constructed. The Root Mean Square Error (ERMS) between the measured and calculated displacements was defined as the fitness function, and Latin Hypercube Sampling (LHS) was introduced to reconstruct the initial population solution space. Finally, the proposed co-simulation framework was employed to perform global iterative inversion of the MCC model parameters for the soft soil in the Wenzhou area. The research results demonstrated that the forward-calculated lateral displacement curve of the retaining structure, utilizing the optimally inverted parameters, agreed well with the field-measured data. This effectively circumvented the subjectivity and limitations associated with conventional empirical parameter selection from geological surveys. Furthermore, considering the harsh field monitoring environment, the impact of environmental noise interference under varying signal-to-noise ratios on the parameter inversion deviation rate was analyzed, which verified the anti-noise robustness of the proposed inversion mechanism. These findings offered a theoretical basis and practical guidance for deformation prediction and parameter inversion in deep foundation pit engineering within similar soft soil geological conditions.
宋来福, 尹项涛, 陈佳楠, 汪一村, 胡家庆. 一种改进的麻雀搜索算法用于MCC本构模型参数的反演研究[J]. 隧道与地下工程灾害防治, .
Song Laifu, Yin Xiangtao, Chen Jianan, Wang Yicun, Hu Jiaqing. Parameter inversion of modified cam-clay constitutive model based on an improved sparrow search algorithm. Hazard Control in Tunnelling and Underground Engineering, 0, (): 1-18.
