Volume 16 Issue 4
Dec.  2023
Turn off MathJax
Article Contents
Ming-qiang Zhan, Bo Chen, Zhong-ru Wu. 2023: Deformation warning index for reinforced concrete dam based on structural health monitoring data and numerical simulation. Water Science and Engineering, 16(4): 408-418. doi: 10.1016/j.wse.2023.09.002
Citation: Ming-qiang Zhan, Bo Chen, Zhong-ru Wu. 2023: Deformation warning index for reinforced concrete dam based on structural health monitoring data and numerical simulation. Water Science and Engineering, 16(4): 408-418. doi: 10.1016/j.wse.2023.09.002

Deformation warning index for reinforced concrete dam based on structural health monitoring data and numerical simulation

doi: 10.1016/j.wse.2023.09.002

This work was supported by the National Natural Science Foundation of China (Grants No. 52079049, U2243223, 51609074, 51739003, and 51579086).

  • Received Date: 2022-03-31
  • Accepted Date: 2023-08-04
  • Available Online: 2023-12-14
  • The material mechanical parameters of the dam body and foundation will change when a dam is reinforced during the aging process. This causes significant changes in the structural state of the project and makes it difficult to ensure its structural safety. In this study, a new deformation warning index for reinforced concrete dams was developed according to the prototype monitoring data, statistical models, three-dimensional finite element model (FEM) numerical simulation, and the critical conditions of the dam structure. A statistical model was established to separate the water pressure component. Then, a three-dimensional FEM of the reinforced concrete dam was constructed to simulate the water pressure component. Furthermore, the deformation components that affected the mechanical parameters of the dam under the same amount of reservoir water level change were separated and quantified accurately. In addition, the method for inversion of comprehensive mechanical parameters after dam reinforcement was used. The influence mechanisms of the deformation behavior of concrete dams under the reservoir water level and temperature changes were investigated. A new deformation warning index was developed by combining the forward-simulated critical water pressure component and temperature component in the period of extreme temperature decrease with the aging component separated by the statistical model. The new deformation warning index considers the structural state of the dam before and after reinforcement and links the structural strength criterion and the deformation evolution mechanisms. It provides a theoretical foundation and decision support for long-term service and operation management of reinforced dams.


  • loading
  • [1]
    Bonaldi, P., Fanelli, M., Giuseppetti, G., 1977. Displacement forecasting for concrete dams. Int. Water Power Dam Constr. 29(9), 42-50.
    Chen, B., Huang, Z.S., Bao, T.F., Zhu, Z., 2021. Deformation early-warning index for heightened gravity dam during impoundment period. Water Science and Engineering 14(1), 54-64. https://doi.org/10.1016/j.wse.2021.03.001.
    Dai, B., Gu, C.S., Zhao, E.F., Qin, X.N., 2018. Statistical model optimized random forest regression model for concrete dam deformation monitoring. Structural Control & Health Monitoring 25(6), e2170. https://doi.org/10.1002/stc.2170.
    De Sortis, A., Paoliani, P., 2007. Statistical analysis and structural identification in concrete dam monitoring. Engineering Structures 29(1), 110-120. https://doi.org/10.1016/j.engstruct.2006.04.022.
    Dou, S.Q., Li, J.J., Kang, F., 2019. Health diagnosis of concrete dams using hybrid FWA with RBF-based surrogate model. Water Science and Engineering 12(3), 188-195. https://doi.org/10.1016/j.wse.2019.09.002.
    Fanelli, M., 1975. Control of dam displacements. Energia Elettrica 52, 125-139.
    Gu, C.S., Fu, X., Shao, C.F., Shi, Z.W., Su, H.Z., 2020. Application of spatiotemporal hybrid model of deformation in safety monitoring of high arch dams: A case study. International Journal of Environmental Research and Public Health 17(1), 319. https://doi.org/10.3390/ijerph17010319.
    Gu, H., Yang, M., Gu, G., Huang, X., 2021. A factor mining model with optimized random forest for concrete dam deformation monitoring. Water Science and Engineering 14(4), 330-336. https://doi.org/10.1016/j.wse.2021.10.004.
    Jiang, Z., Chen, H., 2022. A new early warning method for dam displacement behavior based on non-normal distribution function. Water Science and Engineering 15(2), 170-178. https://doi.org/10.1016/j.wse.2022.04.001.
    Kang, F., Liu, J., Li, J.J., Li, S.J., 2017. Concrete dam deformation prediction model for health monitoring based on extreme learning machine. Structural Control & Health Monitoring 24(10), e1997. https://doi.org/10.1002/stc.1997.
    Kao, C.Y., Loh, C.H., 2013. Monitoring of long-term static deformation data of Fei-Tsui arch dam using artificial neural network-based approaches. Structural Control & Health Monitoring 20(3), 282-303. https://doi.org/10.1002/stc.492.
    Li, Y.T., Bao, T.F., Gao, Z.X., Shu, X.S., Zhang, K., Xie, L.C., Zhang, Z.T., 2022. A new dam structural response estimation paradigm powered by deep learning and transfer learning techniques. Structural Health Monitoring 21(3), 770-778. https://doi.org/10.1177/14759217211009780.
    Salazar, F., Moran, R., Toledo, M.A., Onate, E., 2017. Data-based models for the prediction of dam behaviour: A review and some methodological considerations. Archives of Computational Methods in Engineering 24(1), 1-21. https://doi.org/10.1007/s11831-015-9157-9.
    Sevim, B., Altunisik, A.C., Bayraktar, A., Akkose, M., Adanur, S., 2012. Estimation of elasticity modulus of a prototype arch dam using experimental methods. Journal of Materials in Civil Engineering 24(4), 321-329. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000361.
    Su, H.Z., Wen, Z.P., Sun, X.R., Yang, M., 2015. Time-varying identification model for dam behavior considering structural reinforcement. Structural Safety 57, 1-7. https://doi.org/10.1016/j.strusafe.2015.07.002.
    Wu, B.B., Niu, J.T., Su, H.Z., Yang, M., Wu, Z.R., Cui, X.B., 2019. An approach for deformation modulus mechanism of super-high arch dams. Structural Engineering and Mechanics 69(5), 557-566. https://doi.org/10.12989/sem.2019.69.5.557.
    Yang, L.F., Su, H.Z., Wen, Z.P., 2019. Improved PLS and PSO methods-based back analysis for elastic modulus of dam. Advances in Engineering Software 131, 205-216. https://doi.org/10.1016/j.advengsoft.2019.02.005.
    Zhang, J., Yang, Z., Jiang, J., 2017. An analysis on laws of reservoir dam defects and breaches in China. Scientia Sinica Technologica 47(12), 1313-1320. https://doi.org/10.1360/N092016-00295.
    Zhou, W., Li, S.L., Ma, G., Chang, X.L., Ma, X., Zhang, C., 2016. Parameters inversion of high central core rockfill dams based on a novel genetic algorithm. Science China Technological Sciences 59, 783-794. https://doi.org/10.1007/s11431-016-6017-2.
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索


    Article Metrics

    Article views (16) PDF downloads(0) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint