Be a Better digital Fire-Fighter
Wildfires are an emergency and our communities cope, year after year, with record-breaking events all over the world and, unfortunately, the Iberic peninsula is among those areas that are more affected by fatalities. Therefore, it is evident the necessity for aiming a definitively enhancement in wildfire understanding and management, from prevention, prediction and protection to political policies. The key tool for prevention and suppression of forest fires, as well as for reduction of losses, is an efficient Decision Support System (DSS). DSSs are integrated web-based information systems that incorporate state-of-the-art structural functions as forest-fire simulators. The goal of the present project is the improvement of DSSs through the implementation in the wildfire simulator PROPAGATOR of the consistent statistical methods of ensemble forecasting and of the physically-based fire-spotting model derived within the projects Ensemble Forecasting for Predicting Wildfire Propagation (PID2019-107685RB-I00, 20202023) and Novel Method for Modelling Interface Propagation with Environmental and Engineering Applications (MTM2016-76016-R, 20172019). Actually, both the ensemble forecasting procedure and the fire-spotting modelling are not included yet in PROPAGATOR and, in general, they are widely not implemented yet in operative software tools. The exploitation of these results is in the form of products, services and other applications that are beneficial to Forest and Civil Protection agencies for wildfire managements, such that forest services could Be Better digital Fire-Fighters. In particular, PROPAGATOR is an operational cellular-automata based software code for simulating forest fires that is in daily use by some forest services and research staffs in Europe and, in the actual setting, it is at EU-TRL 9 (Technology Readiness Levels) - successful mission operations. The deliverable of the present proposal will be an updated fire-simulator PROPAGATOR such that the same users of PROPAGATOR are going to be the potential end-users of the achievements of this project. Beside the improvement of PROPAGATOR for its standard uses, the prediction systems for wildfire propagation will benefit of the probabilistic knowledge obtained by applying the ensemble forecast procedure for real-time estimation of wildfire perimeters when this estimation is based on crowdsourcing, e.g., through web-blog, twitter, WhatsApp .... In fact, the inaccuracy of such real-time data can be dealt in the same manner as the uncertainty is dealt by the ensemble forecasting. This improved tool will be exploited for studying scenarios, too. Scenarios are different from forecast: scenarios are actor-specific, which makes them commonly used in planning, in opposition to forecasting that is indeed for anyone. But scenarios can be used also as a scholarly research methodology to challenge assumptions and to identify novel lines of inquiry. Thus, beside fire-management planning, the use of the reliable and updated PROPAGATOR allows for the study of scenarios for future modelling improvement. Only an improved fire-management can help us to understand that, in most ecosystems, wildfires are indeed a natural process that provide a variety of benefits to humankind and then we can finally learn the lesson that it is time to re-establish the archetypical role of fire in our communities.
Measuring ideals in a singularity
This proposal concerns singularities arising in the solution spaces of systems of polynomial equations.
MATH4SPORTS - Modelización matemática para la industria deportiva: salud y rendimiento
MATH4SPORTS seeks to transfer applied mathematics as a driving technology to the field of the sports industry, with a high potential for technology transfer to start-ups, professional clubs, researchers and other agents in the innovative environment of Bizkaia.
Chemistry informed machine learning in emulsion polymerization processes and products
Spectral theory and PDE: Real and Fourier Analysis