黄土
润湿
固体力学
保水曲线
土壤科学
岩土工程
土壤水分
保水性
堆积密度
含水量
环境科学
材料科学
地质学
复合材料
地貌学
作者
Kangze Yuan,Wankui Ni,Gabriele Della Vecchia,Xiang‐fei Lü,Haiman Wang,Yongpeng Nie
出处
期刊:Acta Geotechnica
[Springer Nature]
日期:2024-06-18
卷期号:19 (12): 8111-8128
被引量:3
标识
DOI:10.1007/s11440-024-02354-4
摘要
Abstract In this paper, the EC-5 water sensor and the MPS-6 water potential sensor were used to measure water content and suction, respectively, to investigate the evolution of soil–water retention properties of compacted loess samples prepared at different dry densities and subjected to different numbers of wetting–drying cycles. The water retention data were integrated with a detailed microstructural investigation, including morphological analysis (by scanning electron microscopy) and pore size distribution determination (by nuclear magnetic resonance). The microstructural information obtained shed light on the double porosity nature of compacted loess, allowing the identification of the effects of compaction dry density and wetting–drying cycles at both intra- and inter-aggregate levels. The information obtained at the microstructural scale was used to provide a solid physical basis for the development of a simplified version of the water retention model presented in Della Vecchia et al. (Int J Numer Anal Meth Geomech 39: 702–723, 2015). The model, adapted for engineering application to compacted loess, requires only five parameters to capture the water retention properties of samples characterized by different compaction dry densities and subjected to different numbers of wetting–drying cycles. The comparison between numerical simulations and experimental results, both original and from the literature, shows that only one set of parameters is needed to reproduce the effects of dry density variation, while the variation of only one parameter allows the reproduction of the effects of wetting and drying cycles. With respect to the approaches presented in the literature, where ad hoc calibrations are often used to fit density and wetting–drying cycle effects, the model presented here shows a good compromise between simplicity and predictive capabilities, making it suitable for practical engineering applications.
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