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Hysteresis of Dam Slope Safety Factor under Water Level Fluctuations Based on the LEM Coupled with FEM Method

Guodong Liu1,2,*, Zhijun Zhou1, Shiqiang Xu1, Wenjing Mi2

1 School of Highway, Chang’an University, Xi’an, 710046, China
2 College of Urban, Rural Planning and Architectural Engineering, Shangluo University, Shangluo, 726000, China

* Corresponding Author: Guodong Liu. Email: email

(This article belongs to this Special Issue: Computer Modelling in Disaster Prevention and Mitigation for Engineering Structures)

Computer Modeling in Engineering & Sciences 2022, 133(2), 351-375. https://doi.org/10.32604/cmes.2022.020335

Abstract

Water level variations have caused numerous dam slope collapse disasters around the world, illustrating the large influence of water level fluctuations on dam slopes. The required indoor tests were conducted and a numerical model of an actual earth-filled dam was constructed to investigate the influences of the water level fluctuation rate and the hysteresis of the soil–water characteristic curve (SWCC) on the stability of the upstream dam slope. The results revealed that the free surface in the dam body for the desorption SWCC during water level fluctuations was higher than that for the adsorption SWCC, which would be more evident at higher water levels. The safety factor of the upstream dam slope initially decreased and then increased for the most dangerous water level as the water level rose and fell. The water level fluctuation rate mainly influenced the initial section of the safety factor variation curve, while the SWCC hysteresis mainly affected the minimum safety factor of the water level fluctuations. The desorption SWCC is suggested for engineering design. Furthermore, a quick prediction method is proposed to estimate the safety factor of upstream dam slopes with identical structures.

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Cite This Article

Liu, G., Zhou, Z., Xu, S., Mi, W. (2022). Hysteresis of Dam Slope Safety Factor under Water Level Fluctuations Based on the LEM Coupled with FEM Method. CMES-Computer Modeling in Engineering & Sciences, 133(2), 351–375.



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