Prediction Time Assessment in a DDDAS for Natural Hazard Management: Forest Fire Study Case ✩

This work faces the problem of quality and prediction time assessment in a Dynamic Data Driven Application System (DDDAS) for predicting natural hazard evolution. In particular, we used forest fire spread prediction as a case study to show the applicability of the methodology. The improvement on the prediction quality when using a two-stage DDDAS prediction framework has been widely proved. The two-stages DDDAS has a first phase where an adjustment of the input data is performed in order to be applied in the second phase, the prediction. This paper is focused on defining a new methodology for prediction time assessment under this kind of prediction environments by evaluating, in advance, how a certain combination of simulator, computational resources, adjustment strategy, and frequency of data acquisition will perform, in terms of prediction time. Since the time incurred in the hazard simulation is a crucial part of the whole prediction time, we have defined a methodology to classify the simulator’s execution time using Artificial Intelligence techniques allowing us to determine upper bounds for the DDDAS prediction time depending on the particular input parameter setting. This methodology can be extrapolated to any DDDAS for predicting natural hazards evolution, which uses the two-stage prediction scheme as a working framework. Keywords

Scalability of a multi-physics system for forest fire spread prediction in multi-core platforms

Advances in high-performance computing have led to an improvement in modeling multi-physics systems because of the capacity to solve complex numerical systems in a reasonable time. WRF-SFIRE is a multi-physics system that couples the atmospheric model WRF and the forest fire spread model called SFIRE with the objective of considering the atmosphere-fire interactions. In systems like WRF-SFIRE, the trade-off between result accuracy and time required to deliver that result is crucial. So, in this work, we analyze the influence of WRF-SFIRE settings (grid resolutions) into the forecasts accuracy and into the execution times on multi-core platforms using OpenMP and MPI parallel programming paradigms

Applying probability theory for the quality assessment of a wildfire spread prediction framework based on genetic algorithms

This work presents a framework for assessing how the existing constraints at the time of attending an ongoing forest fire affect simulation results, both in terms of quality (accuracy) obtained and the time needed to make a decision. In the wildfire spread simulation and prediction area, it is essential to properly exploit the computational power offered by new computing advances. For this purpose, we rely on a two-stage prediction process to enhance the quality of traditional predictions, taking advantage of parallel computing. This strategy is based on an adjustment stage which is carried out by a well-known evolutionary technique: Genetic Algorithms. The core of this framework is evaluated according to the probability theory principles. Thus, a strong statistical study is presented and oriented towards the characterization of such an adjustment technique in order to help the operation managers deal with the two aspects previously mentioned: time and quality. The experimental work in this paper is based on a region in Spain which is one of the most prone to forest fires: El Cap de Creus

Forest fire propagation prediction based on overlapping DDDAS forecasts

International Conference on Computational Science, ICCS 2015 – Computational Science at the Gates of NatureForest fire devastate every year thousand of hectares of forest around the world. Fire behavior prediction is a useful tool to aid coordination and management of human and mitigation resources when fighting against these kind of hazards. Any fire spread forecast system requires to be fitted with different kind of data with a high degree of uncertainty, such as for example, me- teorological data and vegetation map among others. The dynamics of this kind of phenomena requires to develop a forecast system with the ability to adapt to changing conditions. In this work two different fire spread forecast systems based on the Dynamic Data Driven Application paradigm are applied and an alternative approach based on the combination of both predictions is presented. This new method uses the computational power provided by high performance computing systems to deliver the predictions under strict real time constraints.This research has been supported by the Ministerio de Economía y Competitividad (MECSpain) under contract TIN2011-28689-C02-01 and the Catalan government under grant 2014- SGR-576

Optimització de la simulació de camps de vents

El vent és un fenomen ambiental natural que pot afavorir positivament en molts àmbits, però a la vegada pot provocar catàstrofes en les quals es veuen perjudicades tant la naturalesa com l'ésser humà. Per aquest motiu la simulació dels camps de vents està prenent més força, ja que aquesta predicció del comportament del vent en funció del terreny, la vegetació, la direcció i velocitat del mateix pot ser decisiva a l'hora de prevenir l'extensió incontrolada d'incendis forestals. WindNinja és un programa que permet realitzar aquesta simulació. Aquest projecte tracta de l'optimització de les execucions per a obtenir la simulació, així com, l'estudi dels diferents paràmetres d'entrada que poden influir en el rendiment.Wind is a natural environmental phenomenon that can have a positive effect on many areas, but at the same time, it can cause catastrophes in which both nature and humans are harmed. For this reason, the simulation of wind field is gaining momentum, as this prediction of wind behaviors based on terrain, vegetation, wind direction and speed can be crucial in preventing the uncontrolled spread of forest fires. WindNinja is a program that allows this simulation. This project deals with the optimization of the executions to obtain the simulation, as well as the study of the different input parameters that can influence the performance.El viento es un fenómeno ambiental natural que puede favorecer positivamente en muchos ámbitos, pero a su vez puede provocar catástrofes en las que se ven perjudicadas tanto la naturaleza como el ser humano. De ahí que la simulación de los campos de vientos esté tomando más fuerza, ya que esta predicción del comportamiento del viento en función del terreno, la vegetación, la dirección y velocidad de este puede ser decisiva a la hora de prevenir la extensión incontrolada de incendios forestales. WindNinja es un programa que permite realizar esta simulación. Este proyecto trata de la optimización de las ejecuciones para obtener la simulación, así como el estudio de los distintos parámetros de entrada que pueden influir en el rendimiento

Gestor d'expedients per l'Institut Municipal d'Hisenda

El projecte recull el treball portat a càrrec per l'anàlisi, disseny i implementació d'una eina per l'Institut Municipal D'Hisenda de l'Ajuntament de Barcelona que compleixi les necessitats d'un sistema d'informació capaç de gestionar els expedients que genera una sèrie de tributs, les sancions que comporten així com la documentació necessària per la comunicació amb el ciutadà. Per realitzar l'aplicació s'han utilitzat tecnologies que ens permeten treballar en l'entorn web, un nucli programat en llenguatge Java sobre la plataforma MVC de Struts, tot sobre un servidor d'aplicacions WebSphere i un motor de base de dades Oracle. El proyecto recoge la labor llevada a cabo para el análisis, diseño e implementación de una herramienta para el Instituto Municipal de Hacienda del Ayuntamiento de Barcelona que cumpla las necesidades de un sistema de la información capaz de gestionar los expedientes que genera una serie de tributos, las sanciones que comportan así como la documentación necesaria para la comunicación con el ciudadano. Para realizar la aplicación se han utilizado tecnologías que nos permiten trabajar en el entorno web, un núcleo programado en lenguaje Java sobre la plataforma MVC de Struts, ejecutándolo en un servidor de aplicaciones WebSphere i un motor de base de datos Oracle.The project gathers the work carried out by the analysis, design and implementation of a tool for the "Institut Municipal d'Hisenda" of the Barcelona city council, that fulfils the necessity of an information system able to manage the files generated by a set of taxes, the sanctions, as well as the documentation necessary for the communication to the citizen. To implement the application different technologies has been used technologies that allow us to work in a web environment, a kernel programmed in Java Language on the platform Struts MVC, all over an application server Websphere and an Oracle database