Detalhes bibliográficos
Ano de defesa: |
2023 |
Autor(a) principal: |
Sales, Renata de Souza |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Não Informado pela instituição
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
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Link de acesso: |
http://repositorio.ufc.br/handle/riufc/75511
|
Resumo: |
The increase in the number of passengers carried in Brazil influences the safety of landing and takeoff operations. In this context, the classification of this safety can enable airport operations management effectively, especially when supported by computational tools. The tire-pavement adhesion parameters are important information directly related to skid resistance, which impairs the safety of landing and takeoff operations. In Brazil, the operational classification of safety is carried out in a segmented manner considering specific aspects of airline operations and airport infrastructure. This makes it difficult to identify risk areas that could contribute to aircraft accidents. This paper aims to classify the operational safety of asphalt pavements on Brazilian runways. To this end, the modeling technique Multilayer Perceptron (MLP) was applied using the software MatLab. The data used in the modeling comes from two Brazilian runways, with Asphalt Concrete and Porous Friction Course (PFC). The information is for the period between 2014 and 2018 and includes data on macrotexture depth, friction coefficient, and removal of rubber buildup from the pavement surface. The results indicate that the type of pavement surface should be distinguished in modeling and that PFC can provide restrictions on the safety of landing and takeoff operations, considering its use with performance credit. Furthermore, it was observed that the friction coefficient is the decisive parameter in the classification of operational safety. It was concluded that the model derived from data set 2 provides an effective way of determining which sections of the runway require maintenance measures to improve the operational safety of landings and take-offs. It is hoped that this work can contribute to future studies and the improvement of the analysis process of the safety of landings and takeoffs in the national territory. |