Parameter Sensitivity and Inversion Analysis for a Concrete Face Rockfill Dam Based on CS-BPNN
Auteur(s): |
Yue Chen
Chongshi Gu Chenfei Shao Xiangnan Qin |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Advances in Civil Engineering, 2019, v. 2019 |
Page(s): | 1-17 |
DOI: | 10.1155/2019/9742961 |
Abstrait: |
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 coupledE-νand 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 coupledE-νand 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, and φ0as well asGare more sensitive to the deformation of the rockfill body. The inversion analysis for these four parameters andη |
Copyright: | © 2019 Yue Chen et al. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10377030 - Publié(e) le:
24.10.2019 - Modifié(e) le:
02.06.2021