Geomechanics and Engineering

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Assessment of the crest cracks of the Pubugou rockfill dam based on parameters back analysis

  • Zhou, Wei (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University) ;
  • Li, Shao-Lin (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University) ;
  • Ma, Gang (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University) ;
  • Chang, Xiao-Lin (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University) ;
  • Cheng, Yong-Gang (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University) ;
  • Ma, Xing (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University)
  • Received : 2015.05.20
  • Accepted : 2016.06.06
  • Published : 2016.10.25
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Abstract

The crest of the Pubugou central core rockfill dam (CCRD) cracked in the first and second impounding periods. To evaluate the safety of the Pubugou CCRD, an inversion analysis of the constitutive model parameters for rockfill materials is performed based on the in situ deformation monitoring data. The aim of this work is to truly reflect the deformation state of the Pubugou CCRD and determine the causes of the dam crest cracks. A novel real-coded genetic algorithm based upon the differences in gene fragments (DGFX) is proposed. It is used in combination with the radial based function neural network (RBFNN) to perform the parameters back analysis. The simulated settlements show good agreements with the monitoring data, illustrating that the back analysis is reasonable and accurate. Furthermore, the deformation gradient of the dam crest has been analysed. The dam crest has a great possibility of cracking due to the uncoordinated deformation, which agrees well with the field investigation. The deformation gradient decreases to the value lower than the critical one and reaches a stable state after the second full reservoir.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

References

  1. Dowsland, K.A. and Thompson, J.M. (2012), Simulated Annealing, Springer, Berlin, Germany.
  2. Duncan, J.M., Wong, K.S. and Mabry, P. (1980), "Strength, stress-strain and bulk modulus parameters for finite element analyses of stresses and movements in soil masses", Geotechnical Engineering, University of California, CA, USA.
  3. Eberhart, R.C. and Kennedy, J. (1995), "A new optimizer using particle swarm theory", Proceedings of the sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, October.
  4. Gikas, V. and Sakellariou, M. (2008), "Settlement analysis of the Mornos earth dam (Greece): Evidence from numerical modeling and geodetic monitoring", Eng. Struct., 30(11), 3074-3081. https://doi.org/10.1016/j.engstruct.2008.03.019
  5. Holland, J.H. (1975), "Adaptation in natural and artificial systems", University of Michigan, MI, USA
  6. Hua, J.J., Zhou, W., Chang, X.L. and Zhou, C.B. (2010), "Study of scale effect on stress and deformation of rockfill", Chinese J. Rock Mech. Eng., 29(2), 328-335.
  7. John, H. (1992), Holland, Adaptation in Natural and Artificial Systems.
  8. Li, G.Y., Mi, Z.K., Fu, H. and Fang, W.F. (2004), "Experimental studies on rheological behaviors for rockfills in concrete faced rockfill dam", Chinese J. Rock Soil Mech., 25(11), 1712-1716.
  9. Ma, G., Zhou, W. and Chang, X.L. (2012), "A novel particle swarm optimization algorithm based on particle migration", Appl. Math. Comput., 218(11), 6620-6626. https://doi.org/10.1016/j.amc.2011.12.032
  10. Michalewicz, Z. (1996), Genetic Algorithms + Data Structures = Evolution Programs, Springer Science & Business Media.
  11. Morris, M.D. (1991), "Factorial sampling plans for preliminary computational experiments", Technometrics, 33(2), 161-174. https://doi.org/10.1080/00401706.1991.10484804
  12. Peng, Y., Zhang, Z.L., Zhang, B.Y. and Yuan, Y.R. (2013), "Deformation gradient finite element method for analyzing cracking in high earth-rack dam and its application", Chinese J. Rock Soil Mech., 34(5), 1453-1458.
  13. Szostak-Chrzanowski, A. and Massiera, M. (2006), "Relation between monitoring and design aspects of large earth dams", Proceedings of the 3rd IAG Symposium on Geodesy for Geotechnical and Structural Engineering and 12-th FIG Symposium on Deformation Measurements, Baden, Austria, May.
  14. Szostak-Chrzanowski, A., Chrzanowski, A. and Massiera, M. (2005), "Use of deformation monitoring results in solving geomechanical problems - Case studies", Eng. Geol., 79(1-2), 3-12. https://doi.org/10.1016/j.enggeo.2004.10.014
  15. Thakur, M. (2014), "A new genetic algorithm for global optimization of multimodal continuous functions", J. Computat. Sci., 5(2), 298-311. https://doi.org/10.1016/j.jocs.2013.05.005
  16. Tomlin, A.S. (2006), "The use of global uncertainty methods for the evaluation of combustion mechanisms", Reliab. Eng. Syst. Safe, 91(10-11), 1219-1231. https://doi.org/10.1016/j.ress.2005.11.026
  17. Van Laarhoven, P.J. and Aarts, E.H. (1987), Simulated Annealing, Springer, Netherlands.
  18. Wright, A.H. (1990), "Genetic algorithms for real parameter optimization", Found. Genetic Algorithms, 1, 205-218
  19. Yu, Y., Zhang, B. and Yuan, H. (2007), "An intelligent displacement back-analysis method for earth-rockfill dams", Comput. Geotech., 34(6), 423-434. https://doi.org/10.1016/j.compgeo.2007.03.002
  20. Zhang, B.Y., Zhang, M.C. and Sun, X. (2008), "Centrifugal modeling of transverse cracking in earth core dams", Chinese J. Rock Soil Mech., 29(5), 1254-1258.
  21. Zhou, W., Hua, J., Chang, X. and Zhou, C. (2011), "Settlement analysis of the Shuibuya concrete-face rockfill dam", Comput. Geotech., 38(2), 269-280. https://doi.org/10.1016/j.compgeo.2010.10.004

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