Análise de confiabilidade da fundação de um viaduto hiperestático: estudo de caso
Reliability analysis is an important tool for quantifying uncertainties involved in the design and construction of civil engineering structures. Appropriate failure probabilities and safety factors associated with the maximum allowed risk can be assessed from a reliability analysis. The purpose of t...
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| Tipo de documento: | Tesis de maestría |
| Estado: | Published version |
| Fecha de publicación: | 2022 |
| País: | Brasil |
| Institución: | UFRN |
| Repositorio: | Repositório Institucional da UFRN |
| Lenguaje: | Portugués |
| OAI Identifier: | oai:repositorio.ufrn.br:123456789/49985 |
| Acceso en línea: | https://repositorio.ufrn.br/handle/123456789/49985 |
| Nivel de acceso: | Acceso abierto |
| Palabra clave: | Fundações Estacas Análise de confiabilidade Probabilidade de ruína Simulação de Monte Carlo CNPQ::ENGENHARIAS::ENGENHARIA CIVIL |
| Sumario: | Reliability analysis is an important tool for quantifying uncertainties involved in the design and construction of civil engineering structures. Appropriate failure probabilities and safety factors associated with the maximum allowed risk can be assessed from a reliability analysis. The purpose of this research is to estimate the failure probability of the pile foundation of a hyperstatic viaduct. The foundation of the viaduct included 43 steel H-piles, driven with a hydraulic hammer. The reliability analysis was carried out using the method put forward by Cintra and Aoki (2010) and the Monte Carlo simulation. Mobilized vertical resistances on the piles were estimated using the dynamic formulations by Chellis (1951) and Smith (1960) modified by Aoki (1996). The input parameters required in these formulations are the pile embedded length, the set and the elastic rebound, and were obtained in the field during the driving of the piles. Vertical loads on the top of the piles were estimated following Brazilian standards NBR 7187/2003 and NBR 7188/2013, as well as the Engesser-Courbon method. The input parameters were fitted to normal distributions and were tested with the KolmogorovSmirnov hypothesis test. Cintra and Aoki’s (2010) method provided convergent results for both dynamic formulations, around 1/2000. On the other hand, the Monte Carlo method yielded divergent failure probabilities, equal to 1/196 and 1/10000, for the solutions by Chellis (1951) and Smith (1960) modified by Aoki (1996), respectively. |
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