HU Wei, ZHU Li-feng, SUN Ping-ping, CHENG Xiu-juan, XUE Qiang, JIA Jun. 2013: An analysis of the time-dependent properties of loess in the formation of landslides at Heifangtai area, Yongjing County, Gansu Province. Geological Bulletin of China, 32(6): 910-918.
Citation:
HU Wei, ZHU Li-feng, SUN Ping-ping, CHENG Xiu-juan, XUE Qiang, JIA Jun. 2013: An analysis of the time-dependent properties of loess in the formation of landslides at Heifangtai area, Yongjing County, Gansu Province. Geological Bulletin of China, 32(6): 910-918.
HU Wei, ZHU Li-feng, SUN Ping-ping, CHENG Xiu-juan, XUE Qiang, JIA Jun. 2013: An analysis of the time-dependent properties of loess in the formation of landslides at Heifangtai area, Yongjing County, Gansu Province. Geological Bulletin of China, 32(6): 910-918.
Citation:
HU Wei, ZHU Li-feng, SUN Ping-ping, CHENG Xiu-juan, XUE Qiang, JIA Jun. 2013: An analysis of the time-dependent properties of loess in the formation of landslides at Heifangtai area, Yongjing County, Gansu Province. Geological Bulletin of China, 32(6): 910-918.
Heifangtai area of Gansu Province is the hotspot for landslide prediction research and application. Tests of the time-dependent properties of loess are the basis of landslide prediction. Taking undisturbed loess in Heifangtai as the study object, the authors conducted consolidated and drained trixial creep tests of loess under the conditions of two water content values, four confining pressures and eight levels of axial stresses. With these tests, the visco-elastic plastic deformation and failure laws of loess in Heifangtai were studied. The creep test results demonstrate that, under the same water content and compression pressure, creep deformation increases as axial stress increases. When compression pressure and axial stress are stable, creep deformation increases as water content increases. Loess is characterized by obvious non-linear visco-elastic plastic deformation. The analyses show that Heifangtai loess generally shows stable and progressive deformation characteristics, suggesting that there exist scientific foundations for landslide prediction. Based on test data, the authors adopted both power and logarithmic functions to get fitting creep models of loess. It is recommended that logarithmic empirical function be used to carry out the analysis of long term stability of loess slopes and the prediction of landslides.
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