Reliability analysis of landfill cover slopes

A methodology for evaluating the reliability of geosynthetic landfill cover slopes was introduced in this dissertation. Several tasks were performed in this research. The field performances of five landfill cover slopes were collected and analyzed as the bases of this study. An analytical approach is developed to study the stress redistribution on a strain-softening interface. It reveals the stress redistribution is too complicated to be modeled by simple models. The sources and magnitudes of variability in the geosynthetic interface shear strength and in the fluid pressure are studied through a series of laboratory shear testing, and hydrological simulations. The results of geosynthetic interface shear strength testing indicate that the testing conditions and testing apparatus are the important sources of the variability of interface shear strength. The c.o.v. of shear strength in the field can be greater than 20%. The analysis of fluid pressure within landfill cover slopes indicates that the magnitude and spatial distribution of the fluid pressure are influenced mainly by the statistical properties of hydraulic conductivity in the drainage layer. The c.o.v. of magnitude of fluid pressures can be greater than 200%. A one-dimensional numerical simulation model (RALCS) is developed to evaluate the stability performance of landfill cover slopes. This model can provide advantages, such as the modeling of the heterogeneous field conditions, and the ability to recognize local unstable portions, over conventional limit equilibrium methods. This model is put into a probabilistic frame to provide information about failure probability, expected failure length, and failure size. A series of systematic reliability analyses indicate that the mean values of interfacial peak shear strength, fluid pressure, slope angle, and end resistance are significant in affecting the reliability of landfill cover slopes. The RALCS model can be extended to estimate temporal and two-dimensional spatial reliability by incorporating the spatial and temporal variance of fluid pressures.