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...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/9742961 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832564578089697280 |
|---|---|
| author | Yue Chen Chongshi Gu Chenfei Shao Xiangnan Qin |
| author_facet | Yue Chen Chongshi Gu Chenfei Shao Xiangnan Qin |
| author_sort | Yue Chen |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ecab9717ab9143548a408e87a1f4d213 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-ecab9717ab9143548a408e87a1f4d2132025-02-03T01:10:47ZengWileyAdvances in Civil Engineering1687-80861687-80942019-01-01201910.1155/2019/97429619742961Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNNYue Chen0Chongshi Gu1Chenfei Shao2Xiangnan Qin3College of Water Conservancy & Hydropower Engineering, Hohai University, 210098 Nanjing, ChinaCollege of Water Conservancy & Hydropower Engineering, Hohai University, 210098 Nanjing, ChinaCollege of Water Conservancy & Hydropower Engineering, Hohai University, 210098 Nanjing, ChinaCollege of Water Conservancy & Hydropower Engineering, Hohai University, 210098 Nanjing, ChinaThe 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.http://dx.doi.org/10.1155/2019/9742961 |
| spellingShingle | Yue Chen Chongshi Gu Chenfei Shao Xiangnan Qin Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN Advances in Civil Engineering |
| title | Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN |
| title_full | Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN |
| title_fullStr | Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN |
| title_full_unstemmed | Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN |
| title_short | Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN |
| title_sort | parameter sensitivity and inversion analysis for a concrete face rockfill dam based on cs bpnn |
| url | http://dx.doi.org/10.1155/2019/9742961 |
| work_keys_str_mv | AT yuechen parametersensitivityandinversionanalysisforaconcretefacerockfilldambasedoncsbpnn AT chongshigu parametersensitivityandinversionanalysisforaconcretefacerockfilldambasedoncsbpnn AT chenfeishao parametersensitivityandinversionanalysisforaconcretefacerockfilldambasedoncsbpnn AT xiangnanqin parametersensitivityandinversionanalysisforaconcretefacerockfilldambasedoncsbpnn |