Reinforced Fill Structure with Alternative Fill Materials: An Application of Geogrid Creep Strain Analysis Using Numerical Modeling

采用新型填料的加筋填料结构:基于数值模拟的土工格栅蠕变应变分析的应用

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Abstract

For many years, granular fill has been the preferred fill material in reinforced fill structures (RFSs) due to its high strength and drainage properties. However, the global scarcity of granular fill has necessitated the exploration of alternative fill materials. This study aims to evaluate the performance of three different alternative fill materials: (i) weak onsite fill (fill 1), (ii) lime-stabilized onsite fill (fill 2), and (iii) recycled construction and demolition (C & D) waste (fill 3). A finite element analysis (FEA) was conducted to assess the stability and horizontal displacement of an RFS and the long-term creep deformation of geogrid using viscoelastic (time-dependent) model in Plaxis. This RFS comprised a combination of wire mesh and geogrids, serving as primary and secondary reinforcement materials, respectively. The results indicate that fill 1, with low shear strength and stiffness, induces excessive lateral displacement and was unstable, making it unsuitable for RFS applications. In contrast, Fill 2 and Fill 3 achieve Eurocode-based safety factors of 1.12 and 1.19, respectively, while significantly reducing horizontal displacement. The long-term creep deformation analysis of geogrid in the case of fill 1 exceeds the prescribed serviceability strain limit threshold, while in the cases of fill 2 and fill 3, it conforms to the serviceability strain limit, which indicates effective mobilization of tensile resistance without excessive elongation. Finally, an analysis was conducted to optimize the geogrid length and to see its impact on cost and performance. The results revealed up to a 29% cost reduction while ensuring performance criteria. These findings validate lime-stabilized onsite fill and recycled C&D waste as viable, cost-effective alternatives to conventional granular backfill, ensuring not only stability and serviceability but also the long-term performance of geogrids in RFSs.

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