14 research outputs found
Asimilaci贸n de datos en un modelo de incendios forestales e integraci贸n en GIS
Trabajo de Fin de M谩ster del M谩ster en Geotecnolog铆as cartogr谩ficas en ingenier铆a y arquitectura, curso 2012-2013.Este trabajo se ha desarrollado dentro del contexto de la simulaci贸n num茅rica de incendios forestales llevada a cabo dentro del grupo de Simulaci贸n Num茅rica y C谩lculo Cient铆fico de la Universidad de Salamanca.
Con su realizaci贸n se ha pretendido dar respuesta a las l铆neas de investigaci贸n abiertas en la actividad del grupo tratando de aportar los conocimientos adquiridos a lo largo del m谩ster. De esta forma, este proyecto se divide en dos subproyectos.
Durante el primero se lleva a cabo una etapa de investigaci贸n sobre la aplicaci贸n de t茅cnicas de asimilaci贸n de datos basadas en el empleo del Filtro de Kalman para la identificaci贸n de par谩metros. En concreto, se valida el uso de estas t茅cnicas para el ajuste de par谩metros en un modelo de propagaci贸n de incendios unidimensional.
En una segunda parte se pretende investigar sobre los diferentes recursos de informaci贸n geogr谩fica disponibles y como pueden aprovecharse para construir un servicio de valor a帽adido.
A continuaci贸n, se seleccionan aquellos recursos que proporcionan la informaci贸n que puede servir, directamente o mediante adaptaci贸n, como datos de entrada a un modelo de propagaci贸n de incendios forestales, y se lleva a cabo la integraci贸n de este modelo en el entorno ArcGIS Desktop.
El objetivo final de este subproyecto es desarrollar una herramienta que permita automatizar la adquisici贸n y el procesamiento de la informaci贸n geogr谩fica de forma que se obtengan los datos necesarios para lanzar el modelo de propagaci贸n de incendios y llevar a cabo la simulaci贸n. Una vez procesados los datos de entrada, se deben representar los resultados sobre un mapa base f谩cilmente entendible por el usuario
Asimilaci贸n de datos, validaci贸n e integraci贸n en GIS de un modelo de simulaci贸n de incendios forestales
[ES]Esta tesis doctoral se ha desarrollado dentro del contexto de la investigaci贸n
de la simulaci贸n num茅rica de incendios forestales llevada a cabo dentro
del grupo de investigaci贸n reconocido SINUMCC (Simulaci贸n Num茅rica y
C谩lculo Cient铆fico) de la Universidad de Salamanca.
En t茅rminos generales, el trabajo aqu铆 recogido tiene por objeto continuar
el desarrollo del modelo de simulaci贸n de incendios forestales PhyFire (Physical
Forest Fire Spread) elaborado por el grupo de investigaci贸n mediante la
integraci贸n de nuevas herramientas que mejoren su eficiencia, aplicabilidad
y utilidad, a trav茅s de los siguientes objetivos:
1. Incorporaci贸n de t茅cnicas de asimilaci贸n de datos basadas en el empleo
del Filtro de Kalman. La asimilaci贸n de datos permite mejorar las
predicciones obtenidas por el modelo mediante la incorporaci贸n de datos
observados durante la evoluci贸n real del incendio, proporcionando
de este modo predicciones m谩s probables en los instantes siguientes.
2. Validaci贸n del modelo PhyFire mediante la simulaci贸n de fuegos experimentales
llevados a cabo bajo condiciones controladas y el uso de
t茅cnicas de an谩lisis de sensibilidad global. Estas t茅cnicas permiten
determinar los par谩metros y variables de entrada del modelo que
m谩s influencia tienen en las variables de salida, validando el modelo y
facilitando el dise帽o del procedimiento de ajuste de sus par谩metros.
3. Ajuste de par谩metros del modelo, mediante el uso de algoritmos de
optimizaci贸n iterativos en los que la funci贸n de coste compara la salida
del modelo con medidas realizadas sobre fuegos experimentales.
4. Integraci贸n en SIG (Sistemas de Informaci贸n Geogr谩fica) de
los modelos PhyFire y HDWind para mejorar su usabilidad y eficiencia
al disminuir el tiempo necesario para llevar a cabo la simulaci贸n de un
incendio real. Se ha creado una herramienta apta para la utilizaci贸n
por los potenciales usuarios, que incorpora toda la informaci贸n espacial
necesaria para llevar a cabo las simulaciones.
5. Simulaci贸n de incendios forestales reales, con el objetivo de validar
el trabajo realizado
Validating the effect of fuel moisture content by a multivalued operator in a simplified physical fire spread model
[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
Parallel implementation of a simplified semi-physical wildland re spread model using OpenMP
[EN]We present a parallel 2D version of a simplified semi-physical wildland fire spread model based on conservation equations, with convection and radiation as the main heat transfer mechanisms. This version includes some 3D effects. The OpenMP framework allows distributing the prediction operations among the available threads in a multicore architecture, thereby reducing the computational time and obtaining the prediction results much more quickly. The results from the experiments using data from a real fire in Galicia (Spain) confirm the benefits of using the parallel version.Junta of Castilla y Le贸
PhyFire & HDWind: from the initial ideas to the current tool
[EN]We present a historical review of PhyFire and HDWind, both
models developed by the research group on Numerical Simula-
tion and Scientific Computation founded by L. Ferragut at the
University of Salamanca.Junta de Castilla y Le贸n; Fondos FEDE
Neptuno ++: An Adaptive Finite Element Toolbox for Numerical Simulation of Environmental Problems
[EN]In this talk, we show some of the main features of Neptuno++, through several examples. Neptuno++ is a finite element toolbox mainly developed by L. Ferragut at SINUMCC (Group of Numerical Simulation and
Scientific Computation) and implemented in C++.Junta de Castilla y Le贸n; Fondos FEDE
GIS-integrated environmental models
[EN]In this paper, we present the integration of the mathematical models
Physical Forest Fire Spread
(PhFFS) and
High
Definition Wind Model
(HDWF), developed by the authors, into a GIS-based interface in order to supply to the end-user a func-
tional and efficient tool. The resulting tool automates data acquisition, pre-processes spatial data, launches the aforementioned
models, and displays the corresponding results in a unique environment. Our implementation uses the Python language and
Esri鈥檚 ArcPy library to extend the functionality of ArcMap 10.4. The PhFFS is a simplified 2D physical wildland fire spread
model based on conservation equations, with convection and radiation as heat transfer mechanisms. It also includes some 3D
effects. The HDWF arises from an asymptotic approximation of the Navier-Stokes equations, and provides a 3D wind velocity
field in an air layer above the terrain surface. Both models can be run in standalone or coupled mode. Finally, we confirm that
the developed tool is efficient and fully operational presenting some examples of its successful application.Departamento de Educaci贸n de la Junta de Castilla y Le贸n; Fondos FEDER; Fundaci贸n General de la Universidad de Salamanc
Local wind speed forecasting based on WRF-HDWind coupling
[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
An Historical Review of the Simplified Physical Fire Spread Model PhyFire: Model and Numerical Methods
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