Dynamic Inversion Method for Concrete Gravity Dam on Soft Rock Foundation

被引:0
作者
Yin, Guanglin [1 ,2 ]
Lin, Chaoning [1 ]
Sheng, Taozhen [3 ]
Xue, Wenbo [1 ]
Li, Tongchun [1 ]
Chen, Siyu [4 ,5 ]
机构
[1] Hohai Univ, Coll Water Conservancy & Hydropower Engn, Nanjing 210024, Peoples R China
[2] NanJing Hohai Nanzi Hydropower Automat Co Ltd, Nanjing 210032, Peoples R China
[3] Nanjing Hydraul Res Inst, Ctr Big Data & Smart Water, Nanjing 210029, Peoples R China
[4] Nanjing Hydraul Res Inst, Dam Safety Management Dept, Nanjing 210029, Peoples R China
[5] Minist Water Resources, Dam Safety Management Ctr, Nanjing 210029, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2025年 / 15卷 / 09期
基金
中国国家自然科学基金;
关键词
dynamic inversion; concrete gravity dam; soft rock foundation; particle swarm algorithm; dam displacement;
D O I
10.3390/app15094750
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Featured Application This study provides a novel approach for assessing the long-term safety of the concrete gravity dam on a soft rock foundation. The proposed dynamic inversion method, based on an improved particle swarm optimization algorithm, enables accurate identification of time-dependent parameter deterioration in dam foundations. The proposed method provides practical solutions for real-time dam health monitoring, stability assessment, and maintenance optimization, enabling more reliable safety evaluations and informed engineering decisions.Abstract This study presents a dynamic inversion method for the concrete gravity dam on a soft rock foundation, aiming to accurately characterize the time-dependent trend of the dam's mechanical properties. Conventional static inversion methods often overlook temporal variations in material behavior, particularly the long-term weakening of soft rock foundations under environmental influences. To address this limitation, an improved particle swarm optimization (PSO) algorithm is developed for dynamic parameter inversion, combining real-time monitoring data with finite element modeling to evaluate the time-varying elastic modulus of the foundation. The results reveal an exponential decay in the foundation's elastic modulus (from 4.67 GPa to approximately 3.83 GPa), while the dam body maintains a stable modulus of 20.74 GPa. Comparative analyses demonstrate that the dynamic inversion approach, which accounts for time-dependent parameter degradation, significantly improves the displacement prediction accuracy of the dam. The results highlight the critical importance of incorporating temporal mechanical property variations in inversion analyses to ensure reliable structural assessments and enhance long-term dam safety management.
引用
收藏
页数:14
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