Análise probabilística de estabilidade de falésias no litoral do RN

The coastline of the State of Rio Grande do Norte is a dynamic region. This area, which is composed of sandy beaches and alive cliffs of Barreiras Formation, has natural beauties that motivate occupation. Urbanization increases the rate of mass movements and sea cliff retreat. This process is an...

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Autor principal: Silva, Breno Marques Ferreira da
Outros Autores: Freitas Neto, Osvaldo de
Formato: Dissertação
Idioma:pt_BR
Publicado em: Brasil
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Endereço do item:https://repositorio.ufrn.br/jspui/handle/123456789/28024
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Resumo:The coastline of the State of Rio Grande do Norte is a dynamic region. This area, which is composed of sandy beaches and alive cliffs of Barreiras Formation, has natural beauties that motivate occupation. Urbanization increases the rate of mass movements and sea cliff retreat. This process is an important socioeconomic issue, involving loss of land and risks to the population. Previous research on this topic has performed slope stability analysis through deterministic methods of assessment of mass movements risks. However, conventional slope stability analysis does not account for uncertainty in soil properties. In light of this fact, this study performs probabilistic and deterministic methods to assess directly the state of the cliffs of Barra de Tabatinga beach, in the city of Nísia Floresta/RN. Field survey and computational analysis was carried out. The probabilistic analysis performs using the software Rocscience - Slide 7.0. This research used search methods for circular and non-circular slip surfaces to search effectively failure types identified in the area. Moreover, in order to identify the significant geotechnical parameters affecting the factor of safety was perform sensitivity analysis. The results of probability of failure are high for most of the analyzed cases. In addition, the probability of failure increases with the evolution of the front saturation of the cliff top. The back analysis results in probability of failure between 42% and 99%.