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Engineering with Computers

, Volume 33, Issue 4, pp 1027–1043 | Cite as

Prototype monitoring data-based analysis of time-varying material parameters of dams and their foundation with structural reinforcement

  • Huaizhi SuEmail author
  • Shuai Zhang
  • Zhiping Wen
  • Hao Li
Original Article

Abstract

Considering structural reinforcement, a method is studied to implement the back-analysis for the evolution process of dam material property. From a material point of view, the long-term effect of dam reinforcement can be diagnosed using the proposed method. Firstly, the partial least squares algorithm is introduced to obtain the water level component in the prototype observations of dam safety. Secondly, according to all observations and numerical simulation results on dam behavior before and after dam reinforcement, the time-varying characteristics of dam material parameter are back-analyzed. Based on the subsection back-analysis thought, the improved support vector machine is used to implement the back-analysis of dam material parameter and its evolution process. The procedure and algorithm realizing the above goal are proposed. The material parameter evolution model is built. Lastly, the proposed method and model are applied to evaluate the reinforcement validity and long-term effect of one actual concrete gravity dam which has undergone several dangerous treatments. The numerical simulation is implemented to analyze the structural behavior of the typical dam section. The whole sequences of prototype observations and numerically calculated results are divided into several subsequences and then used to back-analyze the elastic modulus and the evolution process of dam body and its foundation. The evolution model of elastic modulus is established to assess the long-term effect improving the dam material performance by dam reinforcement.

Keywords

Dangerous dam Reinforcement Long-term effect evaluation Material properties Dynamic back-analysis 

Notes

Acknowledgements

This research has been partially supported by the National Natural Science Foundation of China (SN: 51579083, 51479054, 41323001), the Doctoral Program of Higher Education of China (SN: 20130094110010), the National Key Research and Development Program of China (SN: 2016YFC0401601), the Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (SN: 20165042112, 20145027612), and the Fundamental Research Funds for the Central Universities (Grant No. 2015B25414).

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Copyright information

© Springer-Verlag London 2017

Authors and Affiliations

  1. 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringHohai UniversityNanjingChina
  2. 2.College of Water Conservancy and Hydropower EngineeringHohai UniversityNanjingChina
  3. 3.Department of Computer EngineeringNanjing Institute of TechnologyNanjingChina
  4. 4.National Engineering Research Center of Water Resources Efficient Utilization and Engineering SafetyHohai UniversityNanjingChina

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