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An improved analytical model for rainfall infiltration in embankment slope constructed with red-bed solid waste
Highlights: An improved rainfall infiltration model for embankment slope constructed with red-bed solid waste is proposed. The improved model embeds the effects of rock block fragments on the rainfall infiltration of red-bed solid waste slope. The improved model performs well to predict the rainfall infiltration process of red-bed solid waste slope. The dynamic infiltration characteristics of red-bed solid waste slope with rainfall process is revealed.
Abstract Rainfall infiltration is one of the key triggering factors of landslide in embankment slope constructed with red-bed solid waste, so rainfall infiltration analytical model plays a critical role in the landslide prediction. However, the complexity of the red-bed solid waste slope’s components has not be considered by the conventional Green-Ampt infiltration model, which has also ignored the influence of the dynamic variation of unsaturated section in the wetted zone of slope under rainfall infiltration. This study proposed an improved rainfall infiltration analytical model for red-bed solid waste slope considering the properties of rock fragments and the dynamic development of saturated–unsaturated proportion in the wetted zone, and developed a solution program for the improved model. The proposed model was validated by comparing the rainfall infiltration experiment, finite element numerical simulation, and traditional Green-Ampt method. The proposed model was then applied to parameter sensitivity analyses to reveal the rainfall infiltration characteristics of red-bed solid waste slope. The results indicate that the rainfall infiltration model proposed in this work perform better to predict the rainfall infiltration process of red-bed solid waste slope, and it will lay the groundwork for more reliably utilizing the red-bed solid waste in transportation geotechnics.
An improved analytical model for rainfall infiltration in embankment slope constructed with red-bed solid waste
Highlights: An improved rainfall infiltration model for embankment slope constructed with red-bed solid waste is proposed. The improved model embeds the effects of rock block fragments on the rainfall infiltration of red-bed solid waste slope. The improved model performs well to predict the rainfall infiltration process of red-bed solid waste slope. The dynamic infiltration characteristics of red-bed solid waste slope with rainfall process is revealed.
Abstract Rainfall infiltration is one of the key triggering factors of landslide in embankment slope constructed with red-bed solid waste, so rainfall infiltration analytical model plays a critical role in the landslide prediction. However, the complexity of the red-bed solid waste slope’s components has not be considered by the conventional Green-Ampt infiltration model, which has also ignored the influence of the dynamic variation of unsaturated section in the wetted zone of slope under rainfall infiltration. This study proposed an improved rainfall infiltration analytical model for red-bed solid waste slope considering the properties of rock fragments and the dynamic development of saturated–unsaturated proportion in the wetted zone, and developed a solution program for the improved model. The proposed model was validated by comparing the rainfall infiltration experiment, finite element numerical simulation, and traditional Green-Ampt method. The proposed model was then applied to parameter sensitivity analyses to reveal the rainfall infiltration characteristics of red-bed solid waste slope. The results indicate that the rainfall infiltration model proposed in this work perform better to predict the rainfall infiltration process of red-bed solid waste slope, and it will lay the groundwork for more reliably utilizing the red-bed solid waste in transportation geotechnics.
An improved analytical model for rainfall infiltration in embankment slope constructed with red-bed solid waste
Jiang, Jianqing (author) / Luo, Shilin (author) / Chang, Jin (author) / Zhang, Rui (author)
2024-02-07
Article (Journal)
Electronic Resource
English
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