基于SSA-MSVR的混凝土拱坝材料参数反演模型

doi:10.3880/j.issn.1006-7647.2023.05.008

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基于SSA-MSVR的混凝土拱坝材料参数反演模型

DOI:

10.3880/j.issn.1006-7647.2023.05.008

作者:

杨杰 ^{^1,2}
杨杰
西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安 710048;西安理工大学水利水电学院,陕西西安 710048
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刘智 ^{^1,2}
刘智
西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安 710048;西安理工大学水利水电学院,陕西西安 710048
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宋锦焘 ^{^1,2}
宋锦焘
西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安 710048;西安理工大学水利水电学院,陕西西安 710048
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程琳 ^{^1,2}
程琳
西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安 710048;西安理工大学水利水电学院,陕西西安 710048
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马春辉 ^{^1,2}
马春辉
西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安 710048;西安理工大学水利水电学院,陕西西安 710048
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冉蠡 ^{^1,2}
冉蠡
西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安 710048;西安理工大学水利水电学院,陕西西安 710048
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作者单位:

(1.西安理工大学省部共建西北旱区生态水利国家重点实验室,陕西西安 710048;2.西安理工大学水利水电学院,陕西西安 710048 )

作者简介:

杨杰(1971—),男,教授,博士,主要从事水工结构与大坝安全监测研究。E-mail:xautyangj@126.com

通讯作者:

中图分类号:

TV37

基金项目:

国家自然科学基金项目(52109166)

Inversion model of material parameters for concrete arch dams based on SSA-MSVR

Author:

YANG Jie ^{^1,2}
YANG Jie
State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China;Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an 710048, China
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LIU Zhi ^{^1,2}
LIU Zhi
State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China;Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an 710048, China
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SONG Jintao ^{^1,2}
SONG Jintao
State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China;Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an 710048, China
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CHENG Lin ^{^1,2}
CHENG Lin
State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China;Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an 710048, China
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MA Chunhui ^{^1,2}
MA Chunhui
State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China;Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an 710048, China
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RAN Li ^{^1,2}
RAN Li
State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China;Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an 710048, China
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Affiliation:

(1.State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China;2.Institute of Water Resources and Hydroelectric Engineering, Xi’an University of Technology, Xi’an 710048, China)

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摘要:

为进一步提高混凝土拱坝材料参数获取的准确性,构建了基于多输出支持向量回归(MSVR)和麻雀搜索算法(SSA)的混凝土拱坝材料参数反演模型。为了快速模拟坝体径向位移与材料参数的非线性关系,建立了高精度的MSVR模型代替有限元模型计算,并利用SSA对所需参数进行寻优反演。工程实例验证结果表明:构建的反演模型计算精度高,计算速度快,能快速反演坝体与坝基材料参数,可用于实际工程的材料参数反演分析。

关键词:拱坝;材料参数;麻雀搜索算法;多输出支持向量回归;参数反演

Abstract:

To further improve the accuracy of obtaining material parameters for concrete arch dams, a material parameter inversion model based on multi-output support vector regression (MSVR) and sparrow search algorithm (SSA) was constructed. To quickly simulate the nonlinear relationship between radial displacement of dam body and material parameters, a high-precision MSVR model was established instead of the finite element model calculation, and SSA was used to optimize and invert the required parameters.The verification results of engineering examples show that the constructed inversion model has high calculation accuracy and fast calculation speed, which can quickly invert the material parameters of the dam body and dam foundation, and can be used for the inversion analysis of material parameters in actual engineering.

Key words:arch dam; material parameters; sparrow search algorithm; multi-output support vector regression; parameter inversion

参考文献

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引用本文

杨杰,刘智,宋锦焘,等.基于SSA-MSVR的混凝土拱坝材料参数反演模型[J].水利水电科技进展,2023,43(5):53-57.(YANG Jie, LIU Zhi, SONG Jintao, et al. Inversion model of material parameters for concrete arch dams based on SSA-MSVR[J]. Advances in Science and Technology of Water Resources,2023,43(5):53-57.(in Chinese))

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收稿日期:2022-11-12
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在线发布日期: 2023-09-18
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