Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm
The physical and mechanical parameters of hydraulic structures in complicated operating conditions often change over time. Updating these parameters in a timely manner is important to comprehend the operating behaviors and monitor the safety of hydraulic structures. Conventional inverse analysis met...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/9842140 |
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| author | Yantao Zhu Xinqiang Niu Jimin Wang Chongshi Gu Erfeng Zhao Lixian Huang |
| author_facet | Yantao Zhu Xinqiang Niu Jimin Wang Chongshi Gu Erfeng Zhao Lixian Huang |
| author_sort | Yantao Zhu |
| collection | DOAJ |
| description | The physical and mechanical parameters of hydraulic structures in complicated operating conditions often change over time. Updating these parameters in a timely manner is important to comprehend the operating behaviors and monitor the safety of hydraulic structures. Conventional inverse analysis methods can only generate inversions on the comprehensive deformation modulus of concrete dam structures, which contradict practical conditions. Based on the researches on conventional reversion methods of the deformation modulus of the dam body, foundation, and reservoir basin, the objective fitness function is established in this paper according to engineering-measured data and finite element simulation results. The quantum genetic algorithm has high global search efficiency and population diversity. A mechanical parameter inversion of high-arch dams is built from the intelligent optimization of an established algorithm by applying the quantum genetic algorithm. The proposed algorithm is tested to be feasible and valid for practical engineering projects and therefore shows scientific and practical application values. |
| format | Article |
| id | doaj-art-1c9e1e3ef3bb45e7ac0904c66567c4f3 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-1c9e1e3ef3bb45e7ac0904c66567c4f32025-02-03T00:58:57ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/98421409842140Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic AlgorithmYantao Zhu0Xinqiang Niu1Jimin Wang2Chongshi Gu3Erfeng Zhao4Lixian Huang5State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, ChinaChangjiang Institute of Survey, Planning, Design and Research, Wuhan, Hubei 430010, ChinaYalong River Hydropower Development Company, LTD., Chengdu 610051, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, ChinaMaterials Science and Engineering Department, University of California Los Angeles, Los Angeles, CA 90095, USAThe physical and mechanical parameters of hydraulic structures in complicated operating conditions often change over time. Updating these parameters in a timely manner is important to comprehend the operating behaviors and monitor the safety of hydraulic structures. Conventional inverse analysis methods can only generate inversions on the comprehensive deformation modulus of concrete dam structures, which contradict practical conditions. Based on the researches on conventional reversion methods of the deformation modulus of the dam body, foundation, and reservoir basin, the objective fitness function is established in this paper according to engineering-measured data and finite element simulation results. The quantum genetic algorithm has high global search efficiency and population diversity. A mechanical parameter inversion of high-arch dams is built from the intelligent optimization of an established algorithm by applying the quantum genetic algorithm. The proposed algorithm is tested to be feasible and valid for practical engineering projects and therefore shows scientific and practical application values.http://dx.doi.org/10.1155/2020/9842140 |
| spellingShingle | Yantao Zhu Xinqiang Niu Jimin Wang Chongshi Gu Erfeng Zhao Lixian Huang Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm Advances in Civil Engineering |
| title | Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm |
| title_full | Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm |
| title_fullStr | Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm |
| title_full_unstemmed | Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm |
| title_short | Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm |
| title_sort | inverse analysis of the partitioning deformation modulusof high arch dams based on quantum genetic algorithm |
| url | http://dx.doi.org/10.1155/2020/9842140 |
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