Objetivo Combustion is an extremely important field for our society. The development of new, step-change technologies is essential and greatly benefits from computational design. However, turbulent combustion physics are complex, highly non-linear, of multi-scale and multi-physics nature, and involve interactions at many time-scales. This makes modeling quite challenging such that accurate predictive models, especially for the formation of pollutants, are not available. Today, the two major challenges for developing predictive simulations of turbulent combustion are first to account for its multi-scale nature by considering the non-universal behavior of small-scale turbulence, which is known to be critically important for turbulence-chemistry interactions, and second, to provide data in sufficient detail for rigorous analysis of model deficiencies and unambiguous model development. These two issues are addressed in the proposed work. The main overall objectives are: 1) Establish a new multi-scale framework to analyze and model turbulent combustion phenomena based on a new way to describe turbulence using so-called dissipation elements, which are space-filling regions in a scalar field allowing to capture its small-scale morphology and non-universality. 2) Create new unprecedented datasets using direct numerical simulations (DNS) and provide new analysis methods to develop and validate combustion models; this will include automatically reducing and optimizing chemical kinetic mechanisms for use in DNS and developing an on-the-fly chemistry reduction technique. 3) Apply new modeling approaches to complex and highly non-linear modeling questions, such as pollutant formation in turbulent spray combustion. The successful outcome of the project will provide new and unprecedented datasets, a quantitative description of the impact of non-universality in small-scale turbulence on different aspects of turbulent combustion, and the basis for an entirely new multi-scale closure. Ámbito científico ciencias naturalesinformática y ciencias de la informaciónciencia de datosmacrodatosciencias naturalesciencias físicasmecánica clásicamecánica de fluidosdinámica de fluidosciencias naturalesinformática y ciencias de la informaciónciencias de la computaciónmultifísicaciencias naturalesinformática y ciencias de la informacióninteligencia artificialaprendizaje automáticociencias naturalesinformática y ciencias de la informacióninteligencia artificialinteligencia computacional Programa(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Tema(s) ERC-ADG-2015 - ERC Advanced Grant Convocatoria de propuestas ERC-2015-AdG Consulte otros proyectos de esta convocatoria Régimen de financiación ERC-ADG - Advanced Grant Coordinador RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN Aportación neta de la UEn € 2 499 884,00 Dirección Templergraben 55 52062 Aachen Alemania Ver en el mapa Región Nordrhein-Westfalen Köln Städteregion Aachen Tipo de actividad Higher or Secondary Education Establishments Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Participación en los programas de I+D de la UE Opens in new window Red de colaboración de HORIZON Opens in new window Otras fuentes de financiación € 0,00 Beneficiarios (1) Ordenar alfabéticamente Ordenar por aportación neta de la UE Ampliar todo Contraer todo RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN Alemania Aportación neta de la UEn € 2 499 884,00 Dirección Templergraben 55 52062 Aachen Ver en el mapa Región Nordrhein-Westfalen Köln Städteregion Aachen Tipo de actividad Higher or Secondary Education Establishments Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Participación en los programas de I+D de la UE Opens in new window Red de colaboración de HORIZON Opens in new window Otras fuentes de financiación € 0,00
