Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN

The deformation behavior of rockfill is significant to the normal operation of concrete face rockfill dam. Considering both the nonlinear mechanical behavior and long-term rheological deformation, the E-ν model and modified Burgers model are coupled to describe the deformation behavior of the rockfi...

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Bibliographic Details
Published in:Advances in civil engineering 2019, Vol.2019 (2019), p.1-17
Main Authors: Qin, Xiangnan, Shao, Chenfei, Gu, Chongshi, Chen, Yue
Format: Article
Language:English
Subjects:
Artificial neural networks
Civil engineering
Concrete
Concrete dams
Deformation
Demand analysis
Engineering
Genetic algorithms
Mathematical models
Mathematical problems
Mechanical properties
Neural networks
Parameter modification
Parameter sensitivity
Rheological properties
Rheology
Rockfill dams
Search algorithms
Sensitivity analysis
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Summary:The deformation behavior of rockfill is significant to the normal operation of concrete face rockfill dam. Considering both the nonlinear mechanical behavior and long-term rheological deformation, the E-ν model and modified Burgers model are coupled to describe the deformation behavior of the rockfill materials. The coupled E-ν and Burgers model contains numerous parameters with complex relationship, and an efficient and accurate inversion analysis is in demand. The sensitivity of the parameters in the coupled E-ν and modified Burgers is analyzed using the modified Morris method initially. Then, a new approach of parameter back analysis is proposed by combining back-propagation neutral network (BPNN) and Cuckoo Search (CS) algorithm. The numerical example shows that parameters K, Rf, and φ0 as well as G are more sensitive to the deformation of the rockfill body. The inversion analysis for these four parameters and η2, E2, and A as well as B in modified Burgers model is performed by the CS-BPNN algorithm. The numerical results demonstrate that the parameters obtained with the proposed method are reasonable and its feasibility is validated.
ISSN:1687-8086
1687-8094
DOI:10.1155/2019/9742961