Abstract
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 parametersK,Rf, andφ0as well asGare more sensitive to the deformation of the rockfill body. The inversion analysis for these four parameters andη2,E2, andAas well asBin 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.
Highlights
Concrete face rockfill dam (CFRD) is one of the most extensively constructed dams due to its strong topographic adaptability, economical engineering plan, and simple construction technology. e safe operation of concrete face slab, the most important water-retaining and antiseepage structure in CFRD, is closely related to the deformation behavior of the rockfill body
Calculated displacement from the coupled model may show higher dependence on certain parameters, i.e., subtle change of these parameters will lead to dramatic variation of calculated displacement, while other parameters present indistinctive effect on displacement, which can be determined by experimental results. erefore, it is necessary to conduct sensitivity analysis before parametric inversion to Advances in Civil Engineering eliminate insensitive parameter and promote computational efficiency. e modified Morris method [10,11,12] is adopted to identify the parameters of high sensitivity for parametric inversion of the coupled E-ν and Burgers model
A brief introduction of coupled E-ν and Burgers model is given in Section 2; the sensitivity analysis is conducted with the modified Morris method in Section 3; in Section 4, the detailed principles and procedures of Cuckoo Search (CS)-back-propagation neutral network (BPNN) are illustrated and a verification example is presented for this method; parametric inversion and numerical simulation of Langyashan CFRD was conducted in the last section to validate the proposed method and it is concluded that the CS-BPNN is feasible in the inversion analysis of rockfill materials
Summary
Concrete face rockfill dam (CFRD) is one of the most extensively constructed dams due to its strong topographic adaptability, economical engineering plan, and simple construction technology. e safe operation of concrete face slab, the most important water-retaining and antiseepage structure in CFRD, is closely related to the deformation behavior of the rockfill body. Zhou et al [21] modified the genetic algorithm to solve the high-dimension multimodal and nonlinear optimal parameters inversion problem and validated this method in parametric analysis of E-B and Merchant creep model. A brief introduction of coupled E-ν and Burgers model is given in Section 2; the sensitivity analysis is conducted with the modified Morris method in Section 3; in Section 4, the detailed principles and procedures of CS-BPNN are illustrated and a verification example is presented for this method; parametric inversion and numerical simulation of Langyashan CFRD was conducted in the last section to validate the proposed method and it is concluded that the CS-BPNN is feasible in the inversion analysis of rockfill materials
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