Stochastic finite element analysis of rockfill dam considering spatial variability of dam material porosity. Issue 9 (9th October 2019)

• Record Type: Journal Article
• Authors: Chen, Hui; Liu, Donghai
• Is Part Of: Engineering computations. Volume 36:Issue 9(2019)
• Page Start: 2929
• Page End: 2959
• Publication Date: 2019-10-09
• Subjects: Constraint random field -- Construction quality -- Rockfill dam -- Spatial variability -- Stochastic finite element analysis; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-06-2018-0266
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: The purpose of this study is to develop a stochastic finite element method (FEM) to solve the calculation precision deficiency caused by spatial variability of dam compaction quality. Design/methodology/approach: The Choleski decomposition method was applied to generate constraint random field of porosity. Large-scale laboratory triaxial tests were conducted to determine the quantitative relationship between the dam compaction quality and Duncan–Chang constitutive model parameters. Based on this developed relationship, the constraint random fields of the mechanical parameters were generated. The stochastic FEM could be conducted. Findings: When the fully random field was simulated without the restriction effect of experimental data on test pits, the spatial variabilities of both displacement and stress results were all overestimated; however, when the stochastic FEM was performed disregarding the correlation between mechanical parameters, the variabilities of vertical displacement and stress results were underestimated and variation pattern for horizontal displacement also changed. In addition, the method could produce results that are closer to the actual situation. Practical implications: Although only concrete-faced rockfill dam was tested in the numerical examples, the proposed method is applicable for arbitrary types of rockfill dams. Originality/value: The value of this study is that the proposed method allowed for the spatial variability of constitutive model parameters and that the applicability was confirmed by the actual project.