Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method

Real-time monitoring of the actual elastic modulus is essential and necessary to ensure the safe operation of arch dams. The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravit...

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Main Authors: Bo Chen, Xiao Fu, Xuyuan Guo, Chongshi Gu, Chenfei Shao, Xiangnan Qin
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Advances in Civil Engineering
Online Access:http://dx.doi.org/10.1155/2019/7936513
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spelling doaj-e2746d0214b54ed79391e4fde72a95b02020-11-25T01:59:25ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942019-01-01201910.1155/2019/79365137936513Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM MethodBo Chen0Xiao Fu1Xuyuan Guo2Chongshi Gu3Chenfei Shao4Xiangnan Qin5State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaYalong River Hydropower Development Company, Ltd., Chengdu 610051, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaReal-time monitoring of the actual elastic modulus is essential and necessary to ensure the safe operation of arch dams. The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravitation search algorithm for support vector machine (PSOGSA-SVM) method. Firstly, the measured data of multipoints with a pendulum are separated to construct the initial sample training set; then, an optimal inversion model is established to reflect the complex nonlinear relationship between the mechanical parameters of the high arch dam and the deformation of measured points; finally, the PSOGSA-SVM method is used to train and dynamically update the training set so as to realize the optimization solution of the inversion model. The proposed inversion method is successfully applied to a high arch dam in China to verify its feasibility and validity. The results show that the actual elastic modulus of the dam body is much larger than the initial elastic modulus, which is beneficial to structural stability.http://dx.doi.org/10.1155/2019/7936513
collection DOAJ
language English
format Article
sources DOAJ
author Bo Chen
Xiao Fu
Xuyuan Guo
Chongshi Gu
Chenfei Shao
Xiangnan Qin
spellingShingle Bo Chen
Xiao Fu
Xuyuan Guo
Chongshi Gu
Chenfei Shao
Xiangnan Qin
Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method
Advances in Civil Engineering
author_facet Bo Chen
Xiao Fu
Xuyuan Guo
Chongshi Gu
Chenfei Shao
Xiangnan Qin
author_sort Bo Chen
title Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method
title_short Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method
title_full Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method
title_fullStr Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method
title_full_unstemmed Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method
title_sort zoning elastic modulus inversion for high arch dams based on the psogsa-svm method
publisher Hindawi Limited
series Advances in Civil Engineering
issn 1687-8086
1687-8094
publishDate 2019-01-01
description Real-time monitoring of the actual elastic modulus is essential and necessary to ensure the safe operation of arch dams. The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravitation search algorithm for support vector machine (PSOGSA-SVM) method. Firstly, the measured data of multipoints with a pendulum are separated to construct the initial sample training set; then, an optimal inversion model is established to reflect the complex nonlinear relationship between the mechanical parameters of the high arch dam and the deformation of measured points; finally, the PSOGSA-SVM method is used to train and dynamically update the training set so as to realize the optimization solution of the inversion model. The proposed inversion method is successfully applied to a high arch dam in China to verify its feasibility and validity. The results show that the actual elastic modulus of the dam body is much larger than the initial elastic modulus, which is beneficial to structural stability.
url http://dx.doi.org/10.1155/2019/7936513
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