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Financement de l’UE (1 498 151 €) : Protocole pour la génération, la validation et l’utilisation de collecteurs pilotés par les données dans les simulations de combustion haute fidélité Hor11/09/2025 Programme de recherche et d'innovation de l'UE « Horizon »
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Protocole pour la génération, la validation et l’utilisation de collecteurs pilotés par les données dans les simulations de combustion haute fidélité
For a clean energy future, combustion technologies require profound innovation as they remain essential for providing industrial heat, powering aviation and maritime shipping, supporting heavy-duty applications, and enabling long-term energy storage. To support and accelerate these sectors' transition to carbon-neutral and zero-carbon fuels (such as H2 and NH3), advanced numerical simulations of reacting flows are expected to play an important role. These simulations provide unique insights into the dynamics of turbulent flames in novel gas turbines or industrial furnaces - essential technological devices for the energy transition. However, high-fidelity simulations of turbulent reacting flows demand extensive computing resources, specialized software, and expert knowledge. Due to the multi-scale nature of combustion, even large research institutions face a trade-off between strong simplifications and extensive simulation runtimes, limiting their simulations' applicability for design processes. Manifold-based models offer a promising solution to reduce computational costs without compromising accuracy. By exploiting the self-similarity inherent to reacting flows, these models enable pre-tabulation of thermochemical states instead of repeated recalculations, resulting in significant simulation speed-ups by factors of 10 up to 1,000. Despite this extraordinary potential, there does not exist a straightforward approach to construct these manifolds for general conditions and current methods remain largely heuristic. ProtoMan seeks to unlock the potential of manifold-based models leveraging the synergy between recent advances in 2D flamelet theory and machine learning techniques. Implementing a systematic protocol for data-driven manifold generation, assessment, and utilization, the project aims to make these highly efficient models more accessible, contributing to advancements in energy systems, environmental protection, fire safety, and modern industrial processes.
| Technische Universitat Darmstadt | 1 498 151 € |
https://cordis.europa.eu/project/id/101221866
Cette annonce se réfère à une date antérieure et ne reflète pas nécessairement l’état actuel. L’état actuel est présenté à la page suivante : Technische Universität Darmstadt, Darmstadt, Allemagne.
