Non-parameterized Numerical Analysis Using the Distinct Lattice Spring Model by Implementing the Duncan–Chang Model

Parameter selection is always a critical issue for the numerical modeling of many geotechnical problems. In this work, an idea of non-parameterized numerical analysis is demonstrated by incorporating tri-axial data as the input into the distinct lattice spring model (DLSM). An automatic parameter ac...

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Bibliographic Details
Published inRock mechanics and rock engineering Vol. 53; no. 5; pp. 2365 - 2380
Main Authors Zhao, Gao-Feng, Wei, Xin-Dong, Liu, Feng, Liu, Wei-Bao
Format Journal Article
LanguageEnglish
Published Vienna Springer Vienna 01.05.2020
Springer Nature B.V
Subjects
Algorithms
Civil Engineering
Earth and Environmental Science
Earth Sciences
Geophysics/Geodesy
Mathematical models
Modelling
Numerical analysis
Original Paper
Parameter modification
Parameterization
Rockfill
Rockfill dams
Spring
Distinct lattice spring model
Duncan–Chang model
Parameter selection
Rockfill dam
Fracturing
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Summary:Parameter selection is always a critical issue for the numerical modeling of many geotechnical problems. In this work, an idea of non-parameterized numerical analysis is demonstrated by incorporating tri-axial data as the input into the distinct lattice spring model (DLSM). An automatic parameter acquisition procedure is developed to determine the parameters of a modified Duncan–Chang (DC) model which is implemented in the DLSM through the further development of an incremental DLSM and a fabric stress calculation scheme. These newly developed algorithms are verified against available numerical results and experimental counterparts. Then, the discrete feature of the DC-DLSM is explored and discussed through the numerical modeling of large-scale tri-axial tests and a fracturing test. Finally, a real rockfill dam project is analyzed by using the DC-DLSM with the available tri-axial data as the input, and a reasonable fitting is obtained, which shows the possibility for the numerical modeling of the DLSM with no parameter selection burden.
ISSN:0723-2632
1434-453X
DOI:10.1007/s00603-020-02047-w