Global sensitivity analysis of parameters based on sPCE: The case study of a concrete face rockfill dam in northwest China

• Published in: PloS one 2023-08, Vol.18 (8), p.e0290665-e0290665
• Main Authors: Ran, Li, Yang, Jie, Ma, Chunhui, Cheng, Lin, Zhou, Mingjuan
• Format: Article
• Language: English
• Subjects: Accuracy; Analysis; Basis functions; Case reports; Case studies; Concrete; Concrete dams; Dams; Decomposition; Design and construction; Earth Sciences; Efficiency; Finite element method; Hypercubes; Latin hypercube sampling; Matched pursuit; Mathematical functions; Mathematical models; Mechanical properties; Methods; Optimization; Parameter identification; Parameter sensitivity; Physical Sciences; Polynomials; Probability distribution; Random variables; Regression analysis; Research and Analysis Methods; Rockfill dams; Sampling methods; Sensitivity analysis; Sparsity; Spatial distribution; Spatial variability; Uncertainty analysis
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0290665

To effectively identify the key material parameters of different zones of concrete face rockfill dams and improve the efficiency of parameter optimization, a global sensitivity analysis method of parameters based on sparse polynomial chaotic expansion (sPCE) is proposed in this paper. The latin hypercube sampling method is used to select multiple groups of material parameters, and then finite element method is used to calculate the displacement of dam characteristic nodes in dam body. On this basis, the displacement is expanded by sPCE, and the polynomial basis function is reconstructed by orthogonal matching pursuit to improve the construction and analysis efficiency of the proxy model. According to the chaos coefficients, Sobol’ indices are calculated to evaluate the influence of the material parameters and their interaction on different displacements of the dam. The results show that the sPCE model can accurately simulate dam displacement and its statistical characteristics with a relatively small sample size. The sensitivity of the same parameter has spatial variability, and under the influence of parameter levels and spatial distribution of different materials, the parameter sensitivity ranking of different zones has certain differences. The proposed method provides a new reference to sensitivity analysis and uncertainty analysis for practical engineering.