http://hdl.handle.net/10366/138151 Fri, 24 Apr 2026 02:12:56 GMT 2026-04-24T02:12:56Z 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 Unfortunately, these maps may be outdated, with areas where vegetation is either not documented or inaccurately portrayed.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/10366/138202 [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/10366/138197 [EN]Solar radiation numerical models need the implementation of an accurate method for determining cast shadows on the terrain or on solar collectors. The aim of this work is the development of a new methodology to detect the shadows on a particular terrain. The paper addresses the detection of self and cast shadows produced by the orography as well as those caused by clouds. The paper presents important enhancements on the methodology proposed by the authors in previous works, to detect the shadows caused by the orography. The domain is the terrain surface discretised using an adaptive mesh of triangles. A triangle of terrain will be under cast shadows when, looking at the mesh from the Sun, you can find another triangle that covers all or partially the first one. For each time step, all the triangles should be checked to see if there are cast or self shadows on it. The computational cost of this procedure eventually resulted unaffordable when dealing with complex topography such as that in Canary Islands thus, a new methodology was developed. This one includes a filtering system to identify which triangles are those likely to be shadowed. If there are no self shadowed triangles, the entire mesh will be illuminated and there will not be any shadows. Only triangles that have their backs towards the Sun will be able to cast shadows on other triangles. Detection of shadows generated by clouds is achieved by a shadow algorithm using satellite images. In this paper, Landsat 8 images have been used. The code was done in python programming language. Finally, the outputs of both approaches, shadows generated by the topography and generated by clouds, can be combined in one map. The whole problem has been tested in Gran Canaria and Tenerife Island (Canary Islands – Spain), and in the Tatra Mountains (Poland and Slovakia). Tue, 07 Feb 2017 00:00:00 GMT http://hdl.handle.net/10366/138197 2017-02-07T00:00:00Z http://hdl.handle.net/10366/138169 We present a new AFEM for the Laplace–Beltrami operator with arbitrary polynomial degree on parametric surfaces, which are globally W1∞ and piecewise in a suitable Besov class embedded in C1,α with α∈(0,1]. The idea is to have the surface sufficiently well resolved in W∞1 relative to the current resolution of the PDE in H1. This gives rise to a conditional contraction property of the PDE module. We present a suitable approximation class and discuss its relation to Besov regularity of the surface, solution, and forcing. We prove optimal convergence rates for AFEM which are dictated by the worst decay rate of the surface error in W∞1 and PDE error in H1. Wed, 23 Nov 2016 00:00:00 GMT http://hdl.handle.net/10366/138169 2016-11-23T00:00:00Z http://hdl.handle.net/10366/138168 In this paper we present an application of the reduced basis method to a local high definition adjusted wind model. The model provides a precise description of the wind in 3D and takes into account topography and thermal gradients on the surface by solving only 2D linear equations; the buoyancy forces, slope effects, and mass conservation are also considered. The wind field is adjusted to the point measurements through an optimal control problem in which the wind flux acts as a control on the boundary. In order to use a reduced basis method, we consider an affine decomposition in terms of the parameter related to the friction coefficient and the wind measures at some given observation points. We also design an a posteriori error estimator that is needed to conduct our reduced basis process. Finally, two numerical examples are presented: a test problem and a real-data scenario, we corroborate the correct behavior of the method in both cases. Tue, 06 Sep 2016 00:00:00 GMT http://hdl.handle.net/10366/138168 2016-09-06T00:00:00Z http://hdl.handle.net/10366/138167 We propose a new augmented dual-mixed method for the Oseen problem based on the pseudostress–velocity formulation. The stabilized formulation is obtained by adding to the dual-mixed approach suitable least squares terms that arise from the constitutive and equilibrium equations. We prove that for appropriate values of the stabilization parameters, the new variational formulation and the corresponding Galerkin scheme are well-posed, and a Céa estimate holds for any finite element subspaces. We also provide the rate of convergence when each row of the pseudostress is approximated by Raviart–Thomas or Brezzi–Douglas–Marini elements and the velocity is approximated by continuous piecewise polynomials. Moreover, we derive a simple a posteriori error estimator of residual type that consists of two residual terms and prove that it is reliable and locally efficient. Finally, we include several numerical experiments that support the theoretical results. Wed, 05 Oct 2016 00:00:00 GMT http://hdl.handle.net/10366/138167 2016-10-05T00:00:00Z http://hdl.handle.net/10366/138166 In this work, we study several strategies based on different objective functions for optimization of hexahedral meshes. We consider two approaches to construct objective functions. The first one is based on the decomposition of a hexahedron into tetrahedra. The second one is derived from the Jacobian matrix of the trilinear mapping between the reference and physical hexahedral element. A detailed description of all proposed strategies is given in the present work. Some computational experiments have been developed to test and compare the untangling capabilities of the considered objective functions. In the experiments, a sample of highly distorted hexahedral elements is optimized with the proposed objective functions, and the rate of success of each function is obtained. The results of these experiments are presented and analyzed. Thu, 12 May 2016 00:00:00 GMT http://hdl.handle.net/10366/138166 2016-05-12T00:00:00Z http://hdl.handle.net/10366/138165 [EN]We present a method to obtain high quality spline parameterization of 2D and 3D geometries for their use in isogeometric analysis. As input data, the proposed method demands a boundary representation of the domain, and it constructs automatically a spline transformation between the physical and parametric domains. Parameterization of the interior of the object is obtained by deforming isomorphically an adapted parametric T-mesh onto the physical domain by applying a T-mesh untangling and smoothing procedure, which is the key of the method. Mesh optimization is based on the mean ratio shape quality measure. The spline representation of the geometry is calculated by imposing interpolation conditions using the data provided by one-to-one correspondence between the meshes of the parametric and physical domains. We give a detailed description of the proposed technique and show some examples. Also, we present some examples of the application of isogeometric analysis in geometries parameterized with our method. Fri, 12 May 2017 00:00:00 GMT http://hdl.handle.net/10366/138165 2017-05-12T00:00:00Z http://hdl.handle.net/10366/138160 [EN]In this paper, we present a new method for inserting several triangulated surfaces into an existing tetrahedral mesh generated by the meccano method. The result is a conformal mesh where each inserted surface is approximated by a set of faces of the final tetrahedral mesh. First, the tetrahedral mesh is refined around the inserted surfaces to capture their geometric features. Second, each immersed surface is approximated by a set of faces from the tetrahedral mesh. Third, following a novel approach, the nodes of the approximated surfaces are mapped to the corresponding immersed surface. Fourth, we untangle and smooth the mesh by optimizing a regularized shape distortion measure for tetrahedral elements in which we move all the nodes of the mesh, restricting the movement of the edge and surface nodes along the corresponding entity they belong to. The refining process allows approximating the immersed surface for any initial meccano tetrahedral mesh. Moreover, the proposed projection method avoids computational expensive geometric projections. Finally, the applied simultaneous untangling and smoothing process delivers a high‐quality mesh and ensures that the immersed surfaces are interpolated. Several examples are presented to assess the properties of the proposed method. Fri, 06 Oct 2017 00:00:00 GMT http://hdl.handle.net/10366/138160 2017-10-06T00:00:00Z http://hdl.handle.net/10366/138159 [EN]The characterisation of the aerodynamic roughness length (z0) and the displacement height (d) is critical when modelling the wind field using the log vertical profile. It is known that the values of these parameters depend on land coverage and weather conditions. Thus, many authors have studied their relationship, providing typical values for each land cover. In this paper, we have performed a comprehensive literature review to collect the intervals of z0 and d values for each land coverage. Using these intervals, we estimate their values using an optimisation technique that improves the results of a downscaling wind model. The downscaling model is a 3D adaptive, mass-consistent finite element model (Wind3D) that takes values from the HARMONIE-AROME or ECMWF mesoscale numerical weather prediction models. The optimisation is carried out by a memetic algorithm that combines the Differential Evolution method, a rebirth operator and the L-BFGS-B algorithm. The fitness function to be minimised is the root mean square error (RMSE) against observed wind data. This fast procedure allows updating the aerodynamic parameters for any weather condition. Numerical experiments have been carried out to show the performance of the methodology. Thu, 01 Mar 2018 00:00:00 GMT http://hdl.handle.net/10366/138159 2018-03-01T00:00:00Z