Modeling Long-Term Reliability of Vertical Barriers

Abstract

The concept of containment is often employed at existing and planned landfills, at sites contaminated with dense nonaqueous phase liquids (DNAPLs) and at sites where a physical barrier is required. A vertical cutoff wall is one of the critical elements of the containment system. This physical barrier can provide hydraulic control and prevent migration of contaminants from the area of impacts. Several types of vertical cutoff walls are currently available and include steel or plastic sheet pile walls, geomembrane walls, slurry walls, deep soil mixing type walls or grouted walls. The other components of the containment system include surface water control and capping or liners. Ideally, a properly designed, constructed and operated containment system would create a totally impervious site encapsulation. Realistically, since the design, construction and operation are performed under conditions of uncertainty, containment system performance should be measured in terms of probability. Whether the containment system is in the design phase or in operation, the reliability of the vertical barrier should be assessed. The reliability of the vertical cutoff wall is a function of several variables. These variables are associated with uncertainties and are evaluated through a probabilistic analysis. The performance function is intended as a means to evaluate a component's dependence on design and control variables. These variables are selected based on engineering design principles, historical field data collected by the authors and data published by others. Assessment of long-term reliability of steel sheet pile wall with sealant is presented and a design equation is derived based on probability and field data. Similarly, reliability of each containment system component can be evaluated. The proposed model provides a means for comparison between different technologies and at the same time allows assessment of the reliability of multi-component systems. Additionally, this model can provide important information that can be used in risk analyses.