Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Stochastic Finite-Element Analysis of Earth–Rockfill Dams Considering the Spatial Variability of Soil Parameters
https://orcid.org/0000-0002-1919-7742
The spatial variability of soil parameters notably influences the accuracy of numerical analyses of earth–rockfill dams. This research establishes a stochastic finite-element method (FEM) considering the spatial variability of soil parameters. The autocorrelation distance and distribution function of the soil dry density are determined according to the monitoring values in situ. The regression functions between the dry density and Duncan E-B model parameters are developed using the triaxial test results. According to the dry densities distribution function and these regression functions, the cumulative distribution functions of E-B model parameter are determined, and the soil parameters random field are established using the isoprobabilistic transformation method. The Guanyinyan composite dam was taken as an example, and the convergence of the stochastic FEM, the effect of random field element size, and the sensitivity of E-B model parameters were discussed. The stochastic FEM analysis of Guanyinyan composite dam showed that the mean value of maximum settlements considering the spatial variability of soil parameters is close to the calculation of inversion parameters. The mean value of maximum settlements began converging in the region when stochastic FEM analysis calculations exceeded 400 times. The influence of the random field element size of the soil parameters on the stochastic FEM calculation is less than that on the FEM calculation. Kb has the largest impact on the stochastic FEM calculation, and Rf has the least influence.
Stochastic Finite-Element Analysis of Earth–Rockfill Dams Considering the Spatial Variability of Soil Parameters
https://orcid.org/0000-0002-1919-7742
The spatial variability of soil parameters notably influences the accuracy of numerical analyses of earth–rockfill dams. This research establishes a stochastic finite-element method (FEM) considering the spatial variability of soil parameters. The autocorrelation distance and distribution function of the soil dry density are determined according to the monitoring values in situ. The regression functions between the dry density and Duncan E-B model parameters are developed using the triaxial test results. According to the dry densities distribution function and these regression functions, the cumulative distribution functions of E-B model parameter are determined, and the soil parameters random field are established using the isoprobabilistic transformation method. The Guanyinyan composite dam was taken as an example, and the convergence of the stochastic FEM, the effect of random field element size, and the sensitivity of E-B model parameters were discussed. The stochastic FEM analysis of Guanyinyan composite dam showed that the mean value of maximum settlements considering the spatial variability of soil parameters is close to the calculation of inversion parameters. The mean value of maximum settlements began converging in the region when stochastic FEM analysis calculations exceeded 400 times. The influence of the random field element size of the soil parameters on the stochastic FEM calculation is less than that on the FEM calculation. Kb has the largest impact on the stochastic FEM calculation, and Rf has the least influence.
Stochastic Finite-Element Analysis of Earth–Rockfill Dams Considering the Spatial Variability of Soil Parameters
https://orcid.org/0000-0002-1919-7742
The spatial variability of soil parameters notably influences the accuracy of numerical analyses of earth–rockfill dams. This research establishes a stochastic finite-element method (FEM) considering the spatial variability of soil parameters. The autocorrelation distance and distribution function of the soil dry density are determined according to the monitoring values in situ. The regression functions between the dry density and Duncan E-B model parameters are developed using the triaxial test results. According to the dry densities distribution function and these regression functions, the cumulative distribution functions of E-B model parameter are determined, and the soil parameters random field are established using the isoprobabilistic transformation method. The Guanyinyan composite dam was taken as an example, and the convergence of the stochastic FEM, the effect of random field element size, and the sensitivity of E-B model parameters were discussed. The stochastic FEM analysis of Guanyinyan composite dam showed that the mean value of maximum settlements considering the spatial variability of soil parameters is close to the calculation of inversion parameters. The mean value of maximum settlements began converging in the region when stochastic FEM analysis calculations exceeded 400 times. The influence of the random field element size of the soil parameters on the stochastic FEM calculation is less than that on the FEM calculation. Kb has the largest impact on the stochastic FEM calculation, and Rf has the least influence.
Stochastic Finite-Element Analysis of Earth–Rockfill Dams Considering the Spatial Variability of Soil Parameters
Int. J. Geomech.
Chi, Shichun (Autor:in) / Feng, Wenquan (Autor:in) / Jia, Yufeng (Autor:in) / Zhang, Zongliang (Autor:in)
01.12.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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