http://hdl.handle.net/10174/37668 Fri, 10 Apr 2026 16:44:18 GMT 2026-04-10T16:44:18Z http://hdl.handle.net/10174/41686 Title: Estimativa do conteúdo de humidade da vegetação através da modelação numérica Authors: Santos, Filippe L. M.; Couto, Flavio Tiago; Monteiro, Maria José; Ribeiro, Nuno Almeida; Le Moigne, Patrick; Salgado, Rui Abstract: In recent years, Portugal suffered several devastating wildfires, such as in 2003, 2005, and 2017. Wildfires are related to fuel load, climate, and ignition factors. Currently, land use and occupation management is a way to reduce wildfires. The work’s objective is to improve the fuel moisture content (FMC) representation across mainland Portugal, through numerical modelling and machine learning. Initially, numerical simulations were performed using the Applications of Research to Operations at MEsoscale (AROME), a limited-area non-hydrostatic operational atmospheric model, creating forcing files to initialize the SURFEX surface model. SURFEX output variables were used as predictors to estimate the FMC through a machine learning-based classifier. These results are useful for understanding the FMC spatiotemporal variability in Portugal and important to identify high-fuel load areas which is crucial for integrated fire management. This work was funded by the Foundation for Science and Technology, I.P., under the PyroC.pt project (Ref. PCIF/MPG/0175/2019) and PhD Grant (2022.11960.BD). Mon, 24 Mar 2025 00:00:00 GMT http://hdl.handle.net/10174/41686 2025-03-24T00:00:00Z http://hdl.handle.net/10174/41683 Title: Modelação da piro-convecção durante mega incêndios em Portugal Authors: Couto, Flavio Tiago; Campos, Cátia; Filippi, Jean-Baptiste; Baggio, Roberta; Purificação, Carolina; Santos, Filippe L. M.; Salgado, Rui Abstract: In 2017, Portugal was affected by several wildfires that exhibited extreme behaviour. To investigate the pyro-convective activity in two megafires that occurred in 2017, two numerical simulations were carried out with the Meso-NH atmospheric model coupled to the ForeFire fire propagation model. The experiments were configured for three nested domains of horizontal resolution of 2000 m, 400 m, and 80 m. The vertical grid is composed of 50 height-based terrain-following levels. Heat and water vapour fluxes were emitted into the atmosphere and carried out by ForeFire, which allows the fire front temporal evolution calculation, considering the terrain slope, atmospheric properties, and fuel characteristics. The simulations were performed in a one-way coupling, i.e., the fire front evolution is directly imposed from a pre-defined map obtained from official reports. The simulations showed that coupling the atmospheric model with the fire propagation model allows exploring the fire impacts on the atmosphere, namely the clouds formation inside the smoke plume. In the Quiaios megafire, the simulation indicated the formation of a pyroCu cloud, while for Pedrógão Grande it was possible to verify that the pyro-convective column produced a pyroCb cloud. Mon, 30 Jun 2025 23:00:00 GMT http://hdl.handle.net/10174/41683 2025-06-30T23:00:00Z http://hdl.handle.net/10174/38996 Title: IoT based Real-time Photovoltaic panel’s Behavior Analysis at the Operation Phase compare with standard condition Authors: Rashel, Masud Rana; Akhund, T. M. N. U.; Ahmed, Md Tofael; Faisal, Fahad; Tlemçani, Mouhaydine Abstract: Photovoltaics panel’s behaviors analysis is important to get internal information about a specific PV panel. Existing instrument, those are used to get the behavior information, mainly named as I-V tracer. The I-V tracer is costly and on the other hand not flexible to use. In this work is proposed to build an IoT based PV analyzer using cheaper technology, and the components those are available in market. All the extracted information is logged at central server to access from remote place.It is considered internet of things (IoT) for accessing the information form any part of the world. The data from the system, aid to understand PV panel internal and external behavior under different variable conditions. It graft for analyzing the PV panels in standard environment condition and at the same time it serves as getting data from real-time during PV panels´ operation phase. The PV analyzer incessantly acquire the value of I-V values and panel temperature and more over the value of ambient environmental parameters. All these information under operational phase are used to understand the behavior of the panel and also use them to compare with the standard condition’s one. This data is used to analyze the behavior at the process phase. Data from PV panel assistance to create I-V curve and P-V curve. Using them, the maximum power point is obtained. All these data from PV panel and the ambient environmental has significant importance to understand the behavior of PV under different condition. Curves give visual instant awareness about the system. This internet of things (IoT) device is identical cheaper in worth than existing I-V tracer and moreover flexible to use. Sat, 01 Feb 2020 00:00:00 GMT http://hdl.handle.net/10174/38996 2020-02-01T00:00:00Z http://hdl.handle.net/10174/38995 Title: Analysis of Single and Double Diode PV Cell Model Using Newton-Raphson Method Authors: Faisal, Fahad; Rashel, Masud Rana; Ahmed, Md Tofael; Tlemçani, Mouhaydine Abstract: In this paper, the single and double diode model is compared to study the characteristics of monocrystalline of PV cell using Newton Raphson method. Due to non-linear behaviour of PV cell’s equation this method is used. This work result clearly showed that, both single and double diode performs vary depending on their different ideality factors. Depending on the ideality factor value the cell behaviour is also changing. Using different values of this parameter of PV cell gives different IV or P-V curves. These curves are important to identify the sensitivity of ideality factor with respect to the model. The curves give the clear idea about the models’ performance with the real time PV. This work is focus to improve the understanding of PV cell characteristics through equivalent PV cell circuit model emphasis on the parameter ideality factor. Understanding PV cell’s characteristics is important to estimate the PV power. Better understanding gives better knowledge about the system. Sat, 01 Feb 2020 00:00:00 GMT http://hdl.handle.net/10174/38995 2020-02-01T00:00:00Z