Volume 10 Issue 1
Jan.  2017
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Yan Xiang, Shu-yan Fu, Kai Zhu, Hui Yuan, Zhi-yuan Fang. 2017: Seepage safety monitoring model for an earth rock dam under influence of high-impact typhoons based on particle swarm optimization algorithm. Water Science and Engineering, 10(1): 70-77. doi: 10.1016/j.wse.2017.03.005
Citation: Yan Xiang, Shu-yan Fu, Kai Zhu, Hui Yuan, Zhi-yuan Fang. 2017: Seepage safety monitoring model for an earth rock dam under influence of high-impact typhoons based on particle swarm optimization algorithm. Water Science and Engineering, 10(1): 70-77. doi: 10.1016/j.wse.2017.03.005

Seepage safety monitoring model for an earth rock dam under influence of high-impact typhoons based on particle swarm optimization algorithm

doi: 10.1016/j.wse.2017.03.005
Funds:  
This work was supported by the National Natural Science Foundation of China (Grants No. 51179108 and 51679151), the Special Fund for the Public Welfare Industry of the Ministry of Water Resources of China (Grant No. 201501033), the National Key Research and Development Program (Grant No. 2016YFC0401603), and the Program Sponsored for Scientific Innovation Research of College Graduates in Jiangsu Province (Grant No. KYZZ15_0140).
More Information
  • Corresponding author: Yan Xiang
  • Received Date: 2016-09-02
  • Rev Recd Date: 2016-12-29
  • Extreme hydrological events induced by typhoons in reservoir areas have presented severe challenges to the safe operation of hydraulic structures. Based on analysis of the seepage characteristics of an earth rock dam, a novel seepage safety monitoring model was constructed in this study. The nonlinear influence processes of the antecedent reservoir water level and rainfall were assumed to follow normal distributions. The particle swarm optimization (PSO) algorithm was used to optimize the model parameters so as to raise the fitting accuracy. In addition, a mutation factor was introduced to simulate the sudden increase in the piezometric level induced by short-duration heavy rainfall and the possible historical extreme reservoir water level during a typhoon. In order to verify the efficacy of this model, the earth rock dam of the Siminghu Reservoir was used as an example. The piezometric level at the SW1-2 measuring point during Typhoon Fitow in 2013 was fitted with the present model, and a corresponding theoretical expression was established. Comparison of fitting results of the piezometric level obtained from the present statistical model and traditional statistical model with monitored values during the typhoon shows that the present model has a higher fitting accuracy and can simulate the uprush feature of the seepage pressure during the typhoon perfectly.

     

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  • Ahmed, A.A., 2009. Stochastic analysis of free surface flow through earth dams. Computers and Geotechnics 36(7), 1186−1190. http://dx.doi.org/10.1016/j.compgeo.2009.05.005.
    Bocchiola, D., Rosso, R., 2014. Safety of Italian dams in the face of flood hazard. Advances in Water Resources 71, 23−31. http://dx.doi.org/10.1016/j.advwatres.2014.05.006.
    Chen, S.H., Xue, L.L., Xu, G.S., Shahrour, I., 2010. Composite element method for the seepage analysis of rock masses containing fractures and drainage holes. International Journal of Rock Mechanics and Mining Sciences 47(5), 762−770. http://dx.doi.org/10.1016/j.ijrmms.2010.03.011.
    Chigira, M., Tsou, C., Matsushi Y., 2013. Topographic precursors and geological structures of deep-seated catastrophic landslides caused by Typhoon Talas. Geomorphology 201(4), 479−493. http://dx.doi.org/10.1016/j.geomorph.2013.07.020.
    Cho, S.E., 2012. Probabilistic analysis of seepage that considers the spatial variability of permeability for an embankment on soil foundation. Engineering Geology 133−134(3), 30−39. http://dx.doi.org/10.1016/j.enggeo.2012.02.013.
    Eberhart, R., Kennedy, J., 1995. A new optimizer using particle swarm theory. In: International Symposium on MICRO Machine and Human Science, pp. 39−43.
    Feng, L., Luo, G., 2009. Analysis on fuzzy risk of landfall typhoon in Zhejiang Province of China. Mathematics and Computers in Simulation 79(11), 3258−3266. http://dx.doi.org/10.1016/j.matcom.2008.12.022.
    Fu, Z., Xiang, Y., Liu, C., 2011. Resilience of hydraulic structures under significant impact of typhoons. Water Science and Engineering 4(3), 284−293. http://dx.doi.org/10.3882/j.issn.1674-2370.2011.03.005
    Gu, C.S., Wu, Z.G., 2006. The Safety Monitoring Theory and Its application in the Dam-foundation System. Hohai University Press, Nanjing (in Chinese).
    Hashemi, M.R., Hatam, F., 2011. Unsteady seepage analysis using local radial basis function-based differential quadrature method. Applied Mathematical Modelling 35(10), 4934−4950. http://dx.doi.org/10.1016/j.apm.2011.04.002.
    Hossain, F., Jeyachandran, I., Pielke, R., 2010. Dam safety effects due to human alteration of extreme precipitation. Water Resources Research 46(3). http://dx.doi.org/10.1029/2009WR007704.
    Jiang, Q.H., Deng, S.S., Zhou, C.B., Lu, W.B., 2010. Modeling unconfined seepage flow using three-dimensional numerical manifold method. Journal of Hydrodynamics Ser. B 22(4), 554−561. http://dx.doi.org/10.1016/S1001-6058(09)60088-3.
    Kazemzadeh-Parsi, M.J., Daneshmand, F., 2012. Unconfined seepage analysis in earth dams using smoothed fixed grid finite element method. International Journal for Numerical and Analytical Methods in Geomechanics 36(6), 780-797. http://dx.doi.org/10.1002/nag.1029.
    Kiani, M., Pourtakdoust, S.H., 2015. State estimation of nonlinear dynamic systems using weighted variance-based adaptive particle swarm optimization. Applied Soft Computing 34, 1−17. http://dx.doi.org/10.1016/j.asoc.2015.04.029.
    Li, G.X., Ge, J.H., Jie, Y., 2003. Free surface seepage analysis based on the element-free method. Mechanics Research Communications 30(1), 9−19. http://dx.doi.org/10.1016/S0093-6413(02)00310-5.
    Lin, M.L., Jeng, F.S., 2000. Characteristics of hazards induced by extremely heavy rainfall in central Taiwan:Typhoon Herb. Engineering Geology 58(2), 191−207. http://dx.doi.org/10.1016/S0013-7952(00)00058-2.
    Lubchenco, J., Karl, T.R., 2012. Predicting and managing extreme weather events. Physics Today 65(41), 31−37. http://dx.doi.org/10.1063/PT.3.1475.
    Rada-Vilela, J., Johnston, M., Zhang, M., 2014. Population statistics for particle swarm optimization: Resampling methods in noisy optimization problems. Swarm and Evolutionary Computation 17, 37−59. http://dx.doi.org/10.1016/j.swevo.2014.02.004.
    Su, H.Z., Sun, X.R., 2013. Comprehensive evaluation and tendency prediction model for concrete dam seepage behavior. Yangtze River 44(22), 95−99 (in Chinese).
    Tang, L., Zhan, J., Chen, Y., 2011. Typhoon process and its impact on the surface circulation in the northern South China Sea. Journal of Hydrodynamics Ser. B. 23(1), 95−104. http://dx.doi.org/10.1016/S1001-6058(10)60093-5
    Wu, Z.R., 2006. Safety Monitoring of Dams and Dam Foundations: Theories and Methods and Their Application. Hohai University Press, Nanjing (in Chinese).
    Xiang, Y., Yuan, H., Wang, Z. J., Li, Z.Y., Guan, Y.J., 2012. Effect of typical extreme environments on concrete dam. In: The Workshop on Thirteenth ASCE Aerospace Division Conference on Engineering. ASCE, Pasadena, pp. 828−839.
    Xiao, Y.F., Duan, Z.D., Xiao, Y.Q., 2011. Typhoon wind hazard analysis for southeast China coastal regions. Structural Safety 33(4–5), 286−295. http://dx.doi.org/10.1016/j.strusafe.2011.04.003.
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