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Avanços na Avaliação de Pavimentos Aeroportuários. Classificação estrutural e avaliação das potencialidades da monitorização remota
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Os pavimentos aeroportuários constituem elementos estruturais críticos para a
segurança e eficiência das operações aéreas, estando sujeitos a solicitações intensas e a um
processo contínuo de degradação. A sua avaliação estrutural assume, por isso, uma relevância
estratégica, tanto para assegurar a integridade das infraestruturas como para otimizar os
planos de manutenção e prolongar a sua vida útil. Tradicionalmente, este processo tem-se
apoiado no método Aircraft Classification Number/Pavement Classification Number (ACN/PCN),
entretanto substituído pelo sistema Aircraft Classification Rating/Pavement Classification Rating
(ACR/PCR) que introduz critérios mecanicistas e assegura maior rigor na análise da interação
entre aeronaves e pavimentos.
A presente dissertação centra-se no estudo da avaliação estrutural de pavimentos
aeroportuários, explorando, por um lado, a aplicação do software FAA Rigid and Flexible
Iterative Elastic Layered Design (FAARFIELD) como ferramenta de cálculo de PCR e de
simulação da evolução estrutural, e, por outro, o potencial de tecnologias avançadas de
monitorização remota. O primeiro caso de estudo incidiu sobre a pista principal de um
aeroporto internacional, comparando o seu comportamento estrutural entre os anos de 2000 e
2024 através da integração de ensaios não destrutivos, do modelo linear elástico Bitumen Stress
Analysis in Roads (BISAR) e de simulações no FAARFIELD. No segundo caso de estudo, foram
testadas metodologias inovadoras de monitorização remota, como interferometria por radar
de abertura sintética (InSAR), Light Detection and Ranging (LiDAR), veículos aéreos não
tripulados (drones) e georadar, aplicadas em ambiente rodoviário, com o objetivo de
demonstrar a sua possível transposição para o contexto aeroportuário.
Os resultados obtidos para o primeiro caso de estudo, confirmam que o FAARFIELD
constitui uma ferramenta robusta e coerente para a avaliação e dimensionamento de
pavimentos aeroportuários, alinhada com as práticas internacionais. Em paralelo, o segundo
caso de estudo mostra que a integração de metodologias de monitorização remota, no futuro,
poderá contribuir para diagnósticos mais precisos e obtidos em tempo útil, suportando uma
gestão mais sustentável das infraestruturas, reduzindo custos de manutenção e reforçando os níveis de segurança operacional.
Airport pavements are critical structural elements for the safety and efficiency of air op- erations, being subject to intense stress and a continuous process of degradation. Therefore, their structural assessment is of strategic importance, both to ensure the integrity of the infra- structure and to optimize maintenance plans and extend their useful life. Traditionally, this process has been based on the Aircraft Classification Number/Pavement Classification Num- ber (ACN/PCN) method, but this has now been replaced by the Aircraft Classification Rat- ing/Pavement Classification Rating (ACR/PCR) system, which introduces mechanistic criteria ensuring greater accuracy in the analysis of the interaction between aircraft and pavements. This dissertation focuses on the structural assessment of airport pavements, exploring, on the one hand, the application of FAA Rigid and Flexible Iterative Elastic Layered Design (FAARFIELD) software as a tool for calculating PCR and simulating structural evolution and, on the other hand, the potential of advanced remote monitoring technologies. The first case study examined the main runway of an international airport and compared its structural be- havior between 2000 and 2024 by integrating non-destructive tests, the Bitumen Stress Analy- sis in Roads (BISAR) linear elastic model, and FAARFIELD simulations. The second case study tested innovative remote sensing methodologies, such as Interferometric Synthetic Aperture Radar (InSAR), Light Detection and Ranging (LiDAR), Unmanned Aerial Vehicles or drones (UAV) and GeoRadar, in a road environment, with the aim of demonstrating their possible application to the airport context. The results of the first case study confirmed that FAARFIELD is a robust and consistent tool for assessing and designing airport pavements, in line with international practices. The second case study showed that the integration of remote monitoring methodologies, in the future, could provide more accurate and timely diagnostics, thus supporting more sustainable infrastructure management, reducing maintenance costs, and enhancing operational safety levels.
Airport pavements are critical structural elements for the safety and efficiency of air op- erations, being subject to intense stress and a continuous process of degradation. Therefore, their structural assessment is of strategic importance, both to ensure the integrity of the infra- structure and to optimize maintenance plans and extend their useful life. Traditionally, this process has been based on the Aircraft Classification Number/Pavement Classification Num- ber (ACN/PCN) method, but this has now been replaced by the Aircraft Classification Rat- ing/Pavement Classification Rating (ACR/PCR) system, which introduces mechanistic criteria ensuring greater accuracy in the analysis of the interaction between aircraft and pavements. This dissertation focuses on the structural assessment of airport pavements, exploring, on the one hand, the application of FAA Rigid and Flexible Iterative Elastic Layered Design (FAARFIELD) software as a tool for calculating PCR and simulating structural evolution and, on the other hand, the potential of advanced remote monitoring technologies. The first case study examined the main runway of an international airport and compared its structural be- havior between 2000 and 2024 by integrating non-destructive tests, the Bitumen Stress Analy- sis in Roads (BISAR) linear elastic model, and FAARFIELD simulations. The second case study tested innovative remote sensing methodologies, such as Interferometric Synthetic Aperture Radar (InSAR), Light Detection and Ranging (LiDAR), Unmanned Aerial Vehicles or drones (UAV) and GeoRadar, in a road environment, with the aim of demonstrating their possible application to the airport context. The results of the first case study confirmed that FAARFIELD is a robust and consistent tool for assessing and designing airport pavements, in line with international practices. The second case study showed that the integration of remote monitoring methodologies, in the future, could provide more accurate and timely diagnostics, thus supporting more sustainable infrastructure management, reducing maintenance costs, and enhancing operational safety levels.
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Palavras-chave
Avaliação estrutural Pavimentos aeroportuários ACN/PCN ACR/PCR FAARFIELD Monitorização remota