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Effect of waste settlement and seismic loading on the integrity of geomembrane barrier systems

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The objective of the research is to develop guidelines for identifying when settlement or seismic loading presents a threat to the integrity of geosynthetic elements for both side slope and cover systems in landfills, and advance further investigation for parameters which influence the strains in the barrier systems. A numerical…

The objective of the research is to develop guidelines for identifying when settlement or seismic loading presents a threat to the integrity of geosynthetic elements for both side slope and cover systems in landfills, and advance further investigation for parameters which influence the strains in the barrier systems. A numerical model of landfill with different side slope inclinations are developed by the two-dimensional explicit finite difference program FLAC 7.0, beam elements with a hyperbolic stress-strain relationship, zero moment of inertia, and interface elements on both sides were used to model the geosynthetic barrier systems. The resulting numerical model demonstrates the load-displacement behavior of geosynthetic interfaces, including whole liner systems and dynamic shear response. It is also through the different results in strains from the influences of slope angle and interface friction of geosynthetic liners to develop implications for engineering practice and recommendations for static and seismic design of waste containment systems.
ContributorsWu, Xuan (Author) / Kavazanjian, Edward (Thesis advisor) / Zapata, Claudia (Committee member) / Houston, Sandra (Committee member) / Arizona State University (Publisher)
Created2013
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Optimal sampling for linear function approximation and high-order finite difference methods over complex regions

Description
I focus on algorithms that generate good sampling points for function approximation. In 1D, it is well known that polynomial interpolation using equispaced points is unstable. On the other hand, using Chebyshev nodes provides both stable and highly accurate points for polynomial interpolation. In higher dimensional complex regions, optimal sampling…

I focus on algorithms that generate good sampling points for function approximation. In 1D, it is well known that polynomial interpolation using equispaced points is unstable. On the other hand, using Chebyshev nodes provides both stable and highly accurate points for polynomial interpolation. In higher dimensional complex regions, optimal sampling points are not known explicitly. This work presents robust algorithms that find good sampling points in complex regions for polynomial interpolation, least-squares, and radial basis function (RBF) methods. The quality of these nodes is measured using the Lebesgue constant. I will also consider optimal sampling for constrained optimization, used to solve PDEs, where boundary conditions must be imposed. Furthermore, I extend the scope of the problem to include finding near-optimal sampling points for high-order finite difference methods. These high-order finite difference methods can be implemented using either piecewise polynomials or RBFs.
ContributorsLiu, Tony (Author) / Platte, Rodrigo B (Thesis advisor) / Renaut, Rosemary (Committee member) / Kaspar, David (Committee member) / Moustaoui, Mohamed (Committee member) / Motsch, Sebastien (Committee member) / Arizona State University (Publisher)
Created2019