BibTex RIS Kaynak Göster
Yıl 2011, Cilt: 3 Sayı: 3, 23 - 32, 01.09.2011

Öz

Kaynakça

  • [1] Plizzari, G.A., On the influence of uplift pressure in concrete gravity dams, Eng. Fract. Mech., 59 (3), 253-267, 1998.
  • [2] Liu, X., Wang, S. and Wang, E., A study on the uplift mechanism of Tongjiezi dam using a coupled hydro-mechanical model, Eng. Geol., 117 (1-2), 134-150, 2011.
  • [3] Rochon-Cyr, M. and Léger. P., Shake table sliding response of a gravity dam model including water uplift pressure, Eng. Struct., 31 (8), 1625-1633, 2009.
  • [4] Javanmardi, F., Léger, p. and Tinawi, R., Seismic structural stability of concrete gravity dams considering transient uplift pressures in cracks, Eng. Struct., 27 (4), 616-628, 2005.
  • [5] Wei, Z., Xiaolin, C., Chuangbing, Z. and Xinghong. L., Failure analysis of high-concrete gravity dam based on strength reserve factor method, Comput. Geotech., 35 (4), 627-636, 2008.
  • [6] Yan, F., Xinbin, T. and Li, G., The uplift mechanism of the rock masses around the Jiangya dam after reservoir inundation, China. Eng. Geol., 117 (1-2), 134-150, 2011.
  • [7] Hasebe, M. and Nagayama, Y., Reservoir operation using the neural network and fuzzy systems for dam control and operation support, Adv. Eng. Softw., 33 (5), 245-260, 2002.
  • [8] Kim, Y.S. and Kim, B.T., Prediction of relative crest settlement of concrete-faced rockfill dams analyzed using an artificial neural network model, Comput. Geotech., 35 (3), 303-322, 2008.
  • [9] Wang, B.S. and He, Z.C., Crack detection of arch dam using statistical neural network based on the reductions of natural frequencies, J. Sound. Vib., 302 (4-5), 1037-1047, 2007.
  • [10] Mata, J., Interpretation of concrete dam behaviour with artificial neural network and multiple linear regression models, Eng. Struct., 33 (3), 903-910, 2011.
  • [11] Rumelhart, D.E. and Mcclelland, J.L., Parallel distributed processing: explorations in the microstructure of cognition, volume 1, MIT Press, 1986.
  • [12] Holland, J.H. Adaptation in natural and artificial systems, University of Michigan Press, 1975.

Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm

Yıl 2011, Cilt: 3 Sayı: 3, 23 - 32, 01.09.2011

Öz

This paper proposed a procedure for prediction of uplift pressure under a diversion dam using Artificial Neural Network (ANN) and Genetic Algorithm (GA). In this study, firstly the continuity Laplace equation is solved for a diversion dam and piezometric head and uplift pressure are computed under the diversion dam. Then two similar ANNs are trained based on GA and Back-Error Propagation (BEP) technique for uplift pressure prediction in different points of considered diversion dam and their test results are compared with each other and with actual data. The inputs and outputs of ANNs are coordinates of different points under the dam and corresponding uplift pressures, respectively. The test results show that the uplift pressure is predicted with good accuracy using this procedure in different locations

Kaynakça

  • [1] Plizzari, G.A., On the influence of uplift pressure in concrete gravity dams, Eng. Fract. Mech., 59 (3), 253-267, 1998.
  • [2] Liu, X., Wang, S. and Wang, E., A study on the uplift mechanism of Tongjiezi dam using a coupled hydro-mechanical model, Eng. Geol., 117 (1-2), 134-150, 2011.
  • [3] Rochon-Cyr, M. and Léger. P., Shake table sliding response of a gravity dam model including water uplift pressure, Eng. Struct., 31 (8), 1625-1633, 2009.
  • [4] Javanmardi, F., Léger, p. and Tinawi, R., Seismic structural stability of concrete gravity dams considering transient uplift pressures in cracks, Eng. Struct., 27 (4), 616-628, 2005.
  • [5] Wei, Z., Xiaolin, C., Chuangbing, Z. and Xinghong. L., Failure analysis of high-concrete gravity dam based on strength reserve factor method, Comput. Geotech., 35 (4), 627-636, 2008.
  • [6] Yan, F., Xinbin, T. and Li, G., The uplift mechanism of the rock masses around the Jiangya dam after reservoir inundation, China. Eng. Geol., 117 (1-2), 134-150, 2011.
  • [7] Hasebe, M. and Nagayama, Y., Reservoir operation using the neural network and fuzzy systems for dam control and operation support, Adv. Eng. Softw., 33 (5), 245-260, 2002.
  • [8] Kim, Y.S. and Kim, B.T., Prediction of relative crest settlement of concrete-faced rockfill dams analyzed using an artificial neural network model, Comput. Geotech., 35 (3), 303-322, 2008.
  • [9] Wang, B.S. and He, Z.C., Crack detection of arch dam using statistical neural network based on the reductions of natural frequencies, J. Sound. Vib., 302 (4-5), 1037-1047, 2007.
  • [10] Mata, J., Interpretation of concrete dam behaviour with artificial neural network and multiple linear regression models, Eng. Struct., 33 (3), 903-910, 2011.
  • [11] Rumelhart, D.E. and Mcclelland, J.L., Parallel distributed processing: explorations in the microstructure of cognition, volume 1, MIT Press, 1986.
  • [12] Holland, J.H. Adaptation in natural and artificial systems, University of Michigan Press, 1975.
Toplam 12 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA65ZD76CD
Bölüm Makaleler
Yazarlar

S. Baghalian Bu kişi benim

F. Nazari Bu kişi benim

Yayımlanma Tarihi 1 Eylül 2011
Yayımlandığı Sayı Yıl 2011 Cilt: 3 Sayı: 3

Kaynak Göster

APA Baghalian, S., & Nazari, F. (2011). Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm. International Journal of Engineering and Applied Sciences, 3(3), 23-32.
AMA Baghalian S, Nazari F. Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm. IJEAS. Eylül 2011;3(3):23-32.
Chicago Baghalian, S., ve F. Nazari. “Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm”. International Journal of Engineering and Applied Sciences 3, sy. 3 (Eylül 2011): 23-32.
EndNote Baghalian S, Nazari F (01 Eylül 2011) Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm. International Journal of Engineering and Applied Sciences 3 3 23–32.
IEEE S. Baghalian ve F. Nazari, “Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm”, IJEAS, c. 3, sy. 3, ss. 23–32, 2011.
ISNAD Baghalian, S. - Nazari, F. “Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm”. International Journal of Engineering and Applied Sciences 3/3 (Eylül 2011), 23-32.
JAMA Baghalian S, Nazari F. Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm. IJEAS. 2011;3:23–32.
MLA Baghalian, S. ve F. Nazari. “Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm”. International Journal of Engineering and Applied Sciences, c. 3, sy. 3, 2011, ss. 23-32.
Vancouver Baghalian S, Nazari F. Prediction of Uplift Pressure under the Diversion Dam Using Artificial Neural Network and Genetic Algorithm. IJEAS. 2011;3(3):23-32.

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