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Title: Large-Eddy Simulation and Challenges for Projection-based Reduced-Order Modeling of a Gas Turbine Model Combustor
Computationally efficient modeling of gas turbine combustion is challenging due to the chaotic multi-scale physics and the complex non-linear interactions between acoustic, hydrodynamic, and chemical processes. A large-eddy simulation (LES) is conducted for the model combustor of Meier et al. (1) using an unstructured mesh finite volume method with turbulent combustion effects modeled using a flamelet-based method. The flow field is validated via comparison to averaged and unsteady high-frequency particle image velocimetry (PIV) fields. A high degree of correlation is noted with the experiment in terms of flow field snapshots and via modal analysis. The dynamics of the precessing vortex core (PVC) is quantitatively characterized using dynamic mode decomposition. The validated FOM dataset is used to construct projection-based ROMs, which aim to reduce the system dimension by projecting the state onto a reduced dimensional linear manifold. The use of a structure-preserving least squares formulation (SP-LSVT) guarantees stability of the ROM, compared to traditional model reduction techniques. The SP-LSVT ROM provides accurate reconstruction of the combustion dynamics within the training region, but faces a significant challenge in future state predictions. This limitation is mainly due to the increased projection error, which in turn is a direct consequence of the highly chaotic nature of the flow field, involving a wide range of disperse coherent more » structures. Formal projection-based ROMs have not been applied to a problem of this scale and complexity, and achieving accurate and efficient ROMs is a grand challenge problem. Further advances in non-linear manifold projections or adaptive basis projections have the potential to improve the predictive capability of this class of ROMs. « less
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Symposium on Thermoacoustics in Combustion: Industry meets Academia (SoTiC 2021)
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National Science Foundation
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