Modelos analítico e numérico para simulação de ensaios de arrancamento de geotêxteis

• Autor(a) principal: Ferreira, Lúdma Heliodora Thomé
• Data de Publicação: 2009
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UERJ
• Texto Completo: http://www.bdtd.uerj.br/handle/1/11595
• topic: Pullout tests; Analytical model; Numerical simulation; Ensaios de arrancamento; Modelo analítico; Simulação numérica; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL

The internal stability analysis is a particular aspect in the design of reinforced soil with geotextiles. Internal failure may occur when the stresses transmitted to the reinforcing element exceeds the tensile strength or when it is pulled out, due to insufficient anchorage. The stress strain distribution along the embedded length of the reinforcement is not uniform, and this condition is not incorporated in the design. Thus, analytical and numerical models appear as alternatives to reduce uncertainties in the design of reinforced soil structures, allowing the adoption of less conservative solutions.The present research proposes an analytical model that reproduces load transfer mechanism and displacements along the length of geotextiles under pullout condiction, and also presents a numerical simulation of pullout tests, making use of Plaxis FEM program. Based on the results of an extensive program of pullout tests in instrumented samples of geotextiles (Espinoza, 2000), the analytical and numerical models were validated and discussed. The simulation of a hypothetical pullout test making use of both models is also presented.The results suggest that the analytical and numerical models are suitable to predict loads, strains and displacements along the geotextiles length, submitted to pullout. The analytical model provided a better fit for the experimental results, since it incorporates a non-linear behavior for the geotextile. The distribution of loads and displacements along the geotextiles is complex, and the good agreement between the models and the experimental results emphasizes the capability of the models for further use.