Determining Impending Slip of Slop and Optimized Embankment Operation Volume of Earth Dams Using a Combination of Neural Networks and Genetic Algorithms (GA)

Document Type : Research Article

Authors

1 Tafresh University, Tafresh, Iran

2 Geotechnical Engineering Research Center, International Institute of Earthquake Engineering and Seismology

3 Afarinesh institution of higher education, Borujerd, Iran

Abstract

In this study, impending slip of slope and optimized embankment operation volume of earth dams have been determined using optimization benefiting from a combination of neural networks and genetic algorithms (GA). Further, coefficient of slope stability of earth dam have been determined using neural network and has been compared with outputs of finite element software PLAXIS. In order to training the neural network from derivative data, 150 models of earth dams have been used in finite element software PLAXIS.
Slope stability analysis has been done in order to determining the safety factor at desired sliding surface and the most probable fracture process and the least related safety factor. The determination of the most probable fracture process at the impending slip (determining the least safety factor) is the genetic algorithm application. Moreover, another application of genetic algorithm in this research is optimizing the embankment operation volume of earth dam in the manner that minimum of safety factor derived. In this research analysis has been done in order to simpler use of proposed dimensions for engineers using various properties of soil in embankment of earth dam for different heights. Results have been shown as figures and tables which optimal dimensions and volume of the dam without using the software can be derived from them.

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References

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Amirkabir Journal of Civil Engineering
Volume 50, Issue 4
November and December 2018
Pages 747-754

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