title: Displacement-based back-analysis of the model parameters of the Nuozhadu high earth-rockfill dam.
abstract: The parameters of the constitutive model, the creep model, and the wetting model of materials of the Nuozhadu high earth-rockfill dam were back-analyzed together based on field monitoring displacement data by employing an intelligent back-analysis method. In this method, an artificial neural network is used as a substitute for time-consuming finite element analysis, and an evolutionary algorithm is applied for both network training and parameter optimization. To avoid simultaneous back-analysis of many parameters, the model parameters of the three main dam materials are decoupled and back-analyzed separately in a particular order. Displacement back-analyses were performed at different stages of the construction period, with and without considering the creep and wetting deformations. Good agreement between the numerical results and the monitoring data was obtained for most observation points, which implies that the back-analysis method and decoupling method are effective for solving complex problems with multiple models and parameters. The comparison of calculation results based on different sets of back-analyzed model parameters indicates the necessity of taking the effects of creep and wetting into consideration in the numerical analyses of high earth-rockfill dams. With the resulting model parameters, the stress and deformation distributions at completion are predicted and analyzed.
authors.affiliation: State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Yongkang
authors.identifier: 0000-0002-0745-2961
authors.initials: Y
authors.lastname: Wu
authors.affiliation: State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Huina
authors.identifier: 0000-0002-3370-2952
authors.initials: H
authors.lastname: Yuan
authors.affiliation: State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Bingyin
authors.identifier: 0000-0003-1298-3457
authors.initials: B
authors.lastname: Zhang
authors.affiliation: HydroChina Kunming Engineering Corporation, Kunming 650051, China.
authors.forename: Zongliang
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Yuzhen
authors.initials: Y
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D002681:China; D008422:Materials Testing / Q000379:methods*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D055883:Structure Collapse / Q000517:prevention & control*; D014867:Water
chemical_list: D014867:Water