Objective 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. Fields of science natural sciencescomputer and information sciencesdata sciencebig datanatural sciencesphysical sciencesclassical mechanicsfluid mechanicsfluid dynamicsnatural sciencescomputer and information sciencescomputational sciencemultiphysicsnatural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-ADG-2015 - ERC Advanced Grant Call for proposal ERC-2015-AdG See other projects for this call Funding Scheme ERC-ADG - Advanced Grant Coordinator RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN Net EU contribution € 2 499 884,00 Address Templergraben 55 52062 Aachen Germany See on map Region Nordrhein-Westfalen Köln Städteregion Aachen Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN Germany Net EU contribution € 2 499 884,00 Address Templergraben 55 52062 Aachen See on map Region Nordrhein-Westfalen Köln Städteregion Aachen Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
