http://hdl.handle.net/10174/37664 2026-05-06T06:21:06Z http://hdl.handle.net/10174/41952 Title: ANÁLISE EXPLORATÓRIA DO USO DA MODELAGEM ATMOSFÉRICA SOBRE OS INCÊNDIOS FLORESTAIS NO PANTANAL Authors: Couto, Flavio Tiago; Santos, Filippe L. M.; Campos, Cátia; Purificação, Carolina; Andrade, Nuno; López-Vega, Juan Manuel; Lacroix, Matthieu Abstract: O estudo discute de forma exploratória as condições atmosféricas favoráveis à evolução dos incêndios florestais no Pantanal em 12 de novembro de 2023. Esses episódios foram marcados por dois períodos de rápida expansão do fogo, primeiro no início da tarde e outro à noite. O estudo usa um conjunto de observações de satélite e estações meteorológicas, as quais ajudaram a identificar o fogo e algumas condições meteorológicas na superfície. Além disso, o Fire Weather Index (FWI) no Pantanal foi analisado para um período de 44 anos. No entanto, esse conjunto de dados não foi suficiente para explicar completamente o comportamento do fogo naquele dia. Nesse contexto, a modelagem atmosférica foi aplicada para encontrar as possíveis causas do comportamento do fogo em dois períodos. O modelo Meso-NH foi configurado com dois domínios aninhados e resoluções horizontais de 2500 m e 500 m. Os resultados mostraram uma tendência positiva do FWI nas últimas décadas, bem como uma clara sazonalidade para os valores máximos no ano de 2023. A simulação indicou condições favoráveis à ignição do fogo, e o campo de rajadas de vento mostrou ventos moderados em ambos os períodos, mas causados por diferentes forçantes. No início da tarde, a circulação em grande escala favoreceu a propagação do fogo, enquanto à noite uma frente de rajada foi observada. O estudo destaca o papel das condições meteorológicas na escala sub-diária, em particular para mudanças repentinas do vento à superfície ao longo do dia. Esse resultado deve ser considerado ao examinar o perigo de fogo e o planejamento das ações de combate aos incêndios na região. 2025-08-19T23:00:00Z http://hdl.handle.net/10174/41951 Title: Detection and Classification of Aircraft Structural Defects for Database Creation and Findings Identification Authors: Chabane, Souhila; Mesbahi, Oumaima; Pereira Santos, Nuno; Tlemcani, Mouhydine; Lourenco de Saude, Jose Abstract: In aviation, maintaining structural integrity [1] It is crucial to maintain aviation safety and operational security. Surface wear, corrosion, and cracks are [2], [3], [4] typical structural defects that can seriously compromise components for aircraft. Employing innovative image processing techniques [5]This study provides a comprehensive approach to support the creation of systems that enable the automatic recognition and classification of these findings. The primary objective is to develop a verified image-based database that improves maintenance processes and inspection performance. The process basis is a structured finding catalogue that was created after an extensive examination of scientific and industrial sources. This catalogue standardises terminology and makes it easier to manually annotate and classify defects consistently. A rigorous pipeline that includes image collection from various sources, data augmentation to improve generalisation, manual annotation based on the catalogue, and expert validation to guarantee accuracy and consistency is used to build the dataset. A crucial component of this initiative is the Aircraft Inspection [6], [7], [8] Repository. By acting as a centralised platform that improves data accessibility, expedites maintenance workflows, and guarantees regulatory compliance, it is intended to address the challenges of gathering, monitoring, and analysing inspection data. The repository greatly improves maintenance planning and decision-making by arranging inspection records across various aircraft models, providing dynamic data analysis tools, and enabling collaborative access to findings. 2025-10-21T23:00:00Z http://hdl.handle.net/10174/41699 Title: Coupled Fire-Atmosphere modelling: Some Findings and current challenges based on Portuguese case studies Authors: Salgado, Rui; Couto, Flavio Tiago; Campos, Cátia; Santos, Filippe L. M.; Baggio, Roberta; Filippi, Jean-Baptiste Abstract: High-resolution atmospheric models and their coupling with fire propagation models are powerful tools for better understanding the behaviour of rural fires and their effects on the atmosphere. Portugal is one of the European countries with most burned area and numerous ignitions. In 2017, Portugal was affected by several megafires with burned areas larger than 10 000 hectares, some of which led to the formation of convective clouds: pyro-cumulus (pyroCu) and pyro-cumulonimbus (pyroCb). These phenomena can significantly influence the evolution of fire fronts by altering surface winds and raising spread rates, creating extra difficulties for firefighting and increasing burned areas. These rural fires of 2017 were the starting point for studying the atmospheric environment that favours ignitions and fire spread and the effects of fires on the atmosphere, particularly the generation of pyroconvection. In this study, Pedrogão Grande (June 17) and the Quiaios (October 15) mega-fires are chosen as case studies for numerical simulations with the MesoNH atmospheric model coupled with the ForeFire fire propagation model. The simulations show the development of pyroCu and pyroCb clouds produced by intense convective updrafts due the heat fluxes generated generated during combustion. The simulations have improved our understanding of the evolution of the fire environment and the role played by downbursts originating from pyroCb clouds and provided insights about numerical modelling of pyroconvective clouds using Meso-NH/ForeFire simulations. Finally, we use the results obtained in this work to illustrate the current state-of-the art of coupled fire-atmosphere modelling, its limitations and challenges. 2025-05-18T23:00:00Z http://hdl.handle.net/10174/41697 Title: Live fuel moisture content estimation using remote sensing and numerical modelling approach Authors: Santos, Filippe L. M.; Couto, Flavio Tiago; Monteiro, Maria José; Ribeiro, Nuno Almeida; Le Moigne, Patrick; Salgado, Rui Abstract: Climate change has led to an increase in wildfires, particularly on the Iberian Peninsula. In recent years, Portugal suffered several devastating wildfires, such as in 2003, 2005, and 2017. In 2024, the situation repeated itself, with several large-scale wildfires occurring in the Central region during September. Wildfires are directly related to the availability of combustible material, weather conditions, and ignition factors. Currently, land use and occupation management is a way to reduce wildfires. Identifying areas with higher fuel availability is essential for wildfire prevention in this context. This work aims to improve the live fuel moisture content (LFMC) representation across mainland Portugal, using remote sensing and numerical modelling through a machine learning approach. First, a product was developed to estimate LFMC for Portugal based on remote sensing, through satellite imagery, and machine learning (LFMC-RS). Next, numerical simulations were performed with the MESO-NH (research) and AROME (operational) models, non-hydrostatic mesoscale atmospheric models, producing forcing files to initialize the SURFEX surface model. All output variables from the SURFEX model were utilized as predictors in a machine learning classifier to estimate the LFMC (LFMC-SFX). These results are useful for understanding the FMC spatiotemporal variability in Portugal The research received financial support from the Foundation for Science and Technology, I.P. (FCT) through the PyroC.pt initiative (Ref. PCIF/MPG/0175/2019) along with a PhD Grant (2022.11960.BD). This work also was cofounded by the European Union through the European Regional Development Fund (FEDER) in the framework of the Interreg VI-A España-Portugal (POCTEP) 2021–2027, FIREPOCTEP+ (0139_FIREPOCTEP_MAS_6_E). 2025-05-18T23:00:00Z