http://hdl.handle.net/10366/138150 Thu, 30 Apr 2026 19:46:33 GMT 2026-04-30T19:46:33Z http://hdl.handle.net/10366/154171 [EN]The PhyFire simplified physical wildfire spread model developed by the research group on Numerical Simulation and Scientific Computation at the University of Salamanca has been integrated into an online GIS interface in order to facilitate its use, automate the data input process, thereby reducing error and improving efficiency, and upgrade the graphical display of simulation results. The main features of the PhyFire model are presented: model equations, numerical solution and GIS integration. A description is provided of new advances in the PhyFire model related to the addition of random phenomena, such as fire-spotting. A real wildfire simulation with fire-spotting is also presented. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/10366/154171 2021-01-01T00:00:00Z http://hdl.handle.net/10366/154170 [EN]This article presents the design and implementation of a new visualization system for mobile platforms for the PhyFire-HDWind fire simulation model, called AppPhyFire. It proposes a mobile computing infrastructure, based on ArcGIS Server and REST architecture, which improves the user experience in actions associated with the fire simulation process. The PhyFire-HDWind model, of which the system presented here forms part, is a forest fire propagation simulation tool developed by the SINUMCC research group of the University of Salamanca, based on two own simplified physical models, the PhyFire physical fire propagation model, and the HDWind high definition wind field model, resolved using efficient numerical and computational tools and parallel computing, allowing simulation times shorter than the real time fire propagation, integrated into a Geographical Information System, and accessible through a server by the AppPhyFire. The system presented in this article allows a quick visualization of simulations results in mobile devices. This work presents the detailed operation of the system and its phases of operation. Wed, 01 Jan 2020 00:00:00 GMT http://hdl.handle.net/10366/154170 2020-01-01T00:00:00Z http://hdl.handle.net/10366/154167 [EN]A major limitation in the simulation of forest fires involves the proper characterization of the surface vegetation over the study area, based on land cover maps. Unfortunately, these maps may be outdated, with areas where vegetation is either not documented or inaccurately portrayed. These limitations may impair the predictions of wildfire simulators or the design of risk maps and prevention plans. This study proposes a complete procedure for fuel type classification using satellite imagery and fully-connected neural networks. Specifically, our work is based on pixel-based processing cells, generating high-resolution maps. The field study is located in the Northeast of Castilla y León, a central Spanish region, and the Rothermel criteria was followed for the fuel classification. The results record an accuracy of close to 78% on the test sets for the two studied settings, improving on the results reported in previous studies and ratifying the robustness of our approach. Additionally, the confusion matrix analysis and the per-class statistics computed confirm good reliability for all fuel types in a cross-validation framework. The predicted maps can be used on wildfire simulators through GIS tools. Sat, 01 Jan 2022 00:00:00 GMT http://hdl.handle.net/10366/154167 2022-01-01T00:00:00Z http://hdl.handle.net/10366/154163 [EN]A new global sensitivity analysis has been conducted of fuel-type-dependent input variables of the simplified physical fire spread model (PhyFire) to understand how the use of spatial averages, that is, fuel models, influences the results of PhyFire with a view to enhancing its understanding and improving its design. The model’s simplicity, the numerical techniques used, and a recent code optimisation, allow undertaking the analysis with very competitive computational times. The fuel data used correspond to grasslands, shrublands and forest in the Spanish region of Galicia. The analysis results validate the flame length sub-model proposed in the paper, which significantly improves the model’s efficiency. Wed, 01 Jan 2020 00:00:00 GMT http://hdl.handle.net/10366/154163 2020-01-01T00:00:00Z http://hdl.handle.net/10366/154160 [EN]Fuel moisture content (FMC) plays a significant role in wildfire behavior and rate of spread (ROS). In addition, FMC is a highly dynamic factor and very vulnerable to climate variations. Understanding the effect of FMC on the behavior of fire spread models is crucial, and detailed analysis of specific aspects of complex models is a very effective way to improve them. The simplified physical fire spread model PhyFire considers the effect of FMC in a novel way, involving a multivalued maximal monotone operator. Several numerical experiments have been carried out to confirm that the behavior of the ROS simulated with PhyFire involving FMC is as expected in the reviewed literature: an exponential decrease in fire ROS compared to FMC, for different scenarios, considering different fuel types, terrain slopes and wind speeds. PhyFire performs very accurately, proving that the multivalued operator used is suitable and consistent. Sun, 01 Jan 2023 00:00:00 GMT http://hdl.handle.net/10366/154160 2023-01-01T00:00:00Z http://hdl.handle.net/10366/154122 [EN] A historical review is conducted of PhyFire, a simplified physical forest fire spread model developed by the research group on Numerical Simulation and Scientific Computation (SINUMCC) at the University of Salamanca. The review ranges from the first version of the model to the current one now integrated into GIS, considering all the mathematical problems and numerical methods involved throughout its development: finite differences, mixed, classical and adaptive finite elements, data assimilation, sensitivity analysis, parameter adjustment, and parallel computation, among others. The simulation of processes as complex as forest fires involves a multidisciplinary effort that is constantly being enhanced, while posing interesting challenges from a mathematical, numerical, and computational perspective, without losing sight of the overriding aim of developing an efficient, effective, and useful simulation tool. Sun, 01 Jan 2023 00:00:00 GMT http://hdl.handle.net/10366/154122 2023-01-01T00:00:00Z http://hdl.handle.net/10366/149831 [EN] Wind speed forecasts obtained by Numerical Weather Prediction models are limited for fine interpretation in heterogeneous terrain, in which different roughnesses and orographies occur. This limitation is derived from the use of low-resolution and grid-box averaged data. In this paper a dynamical downscaling method is presented to increase the local accuracy of wind speed forecasts. The proposed method divides the wind speed forecasting into two steps. In the first one, the mesoscale model WRF (Weather Research and Forecasting) is used for getting wind speed forecasts at specific points of the study domain. On a second stage, these values are used for feeding the HDWind microscale model. HDWind is a local model that provides both a high-resolution wind field that covers the entire study domain and values of wind speed and direction at very located points. As an example of use of the proposed method, we calculate a high-resolution wind field in an urban-interface area from Badajoz, a South-West Spanish city located near the Portugal border. The results obtained are compared with the values read by a weathervane tower of the Spanish State Meteorological Agency (AEMET) in order to prove that the microscale model improves the forecasts obtained by the mesoscale model. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/10366/149831 2021-01-01T00:00:00Z http://hdl.handle.net/10366/138213 [EN]In this paper, an adaptive solar radiation numerical model for complex terrains is described. Fri, 01 Jun 2018 00:00:00 GMT http://hdl.handle.net/10366/138213 2018-06-01T00:00:00Z http://hdl.handle.net/10366/138212 [EN]A mass consistent wind model is improved by introducing three items: the new 3-D mesh generator MECCANO applied to complex terrains, the current atmospheric stability definition by Zilitinkevich including new wind profiles, and a specific preconditioner for the linear systems arising in a wind model. Fri, 01 Jun 2018 00:00:00 GMT http://hdl.handle.net/10366/138212 2018-06-01T00:00:00Z http://hdl.handle.net/10366/138207 Wed, 01 Jun 2016 00:00:00 GMT http://hdl.handle.net/10366/138207 2016-06-01T00:00:00Z http://hdl.handle.net/10366/138206 [en]In this work we propose to apply ensemble methods to a local scale adaptive wind forecasting model. Wed, 01 Jun 2016 00:00:00 GMT http://hdl.handle.net/10366/138206 2016-06-01T00:00:00Z http://hdl.handle.net/10366/138205 Wed, 01 Jun 2016 00:00:00 GMT http://hdl.handle.net/10366/138205 2016-06-01T00:00:00Z http://hdl.handle.net/10366/138204 [ES]En esta conferencia se introducen ideas básicas sobre la simulación numérica, mediante el método de los elementos finitos (MEF), de problemas medioambientales que han sido abordados por nuestro grupo en diversos proyectos de investigación sobre simulación de campos de viento, radiación solar, contaminación atmosférica y la modelización de yacimientos de petróleo. Wed, 01 Feb 2017 00:00:00 GMT http://hdl.handle.net/10366/138204 2017-02-01T00:00:00Z http://hdl.handle.net/10366/138203 [EN]We present a new strategy for construction spline spaces over hierarchical T-meshes with quad- and octree subdivision scheme. Sat, 01 Apr 2017 00:00:00 GMT http://hdl.handle.net/10366/138203 2017-04-01T00:00:00Z http://hdl.handle.net/10366/138202 [EN]In this paper we summarize some aspects of the simplified physical wild fire spread model developed by the authors and of the Geographical Information System tool specially developed to provide a real usable wild fire spread tool based on this model. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10366/138202 2018-01-01T00:00:00Z http://hdl.handle.net/10366/138200 [EN]Solar maps are very interesting tools to describe the characteristics of a region from the solar radiation point of view, and can be applied in atmospheric sciences and for energy engineering. To make them possible, a solar radiation numerical model is proposed. This one allows us to estimate radiation values on any point on earth. The model takes into account the terrain surface conditions and the cast shadows. The procedure uses 2-D adaptive triangles meshes built refining according to surface and albedo characteristics. Solar irradiance values are obtained for clear sky conditions. Using clear sky index as a conversion factor, real sky values are computed in terms of irradiance or irradiation with a desired time step. Finally, the solar radiation maps are obtained for all the domain. Wed, 25 Apr 2018 00:00:00 GMT http://hdl.handle.net/10366/138200 2018-04-25T00:00:00Z