Dynamical p-adaptivity for LES of compressible flows in a high order DG framework
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作者:
Abba, Antonella
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Politecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, ItalyPolitecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, Italy
Abba, Antonella
[1
]
Recanati, Alessandro
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Politecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, ItalyPolitecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, Italy
Recanati, Alessandro
[1
]
Tugnoli, Matteo
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Politecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, ItalyPolitecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, Italy
Tugnoli, Matteo
[1
]
Bonaventura, Luca
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Politecn Milan, MOX Modelling & Sci Comp, Dipartimento Matemat, Piazza Leonardo da Vinci, I-20133 Milan, ItalyPolitecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, Italy
Bonaventura, Luca
[2
]
机构:
[1] Politecn Milan, Dipartimento Sci & Tecnol Aerosp, Via La Masa 34, I-20156 Milan, Italy
[2] Politecn Milan, MOX Modelling & Sci Comp, Dipartimento Matemat, Piazza Leonardo da Vinci, I-20133 Milan, Italy
We investigate the possibility of reducing the computational burden of LES configurations by employing locally and dynamically adaptive polynomial degrees in the framework of a high order DG method. A degree adaptation technique especially featured to be effective for LES applications, that was previously developed by the authors and tested in the statically adaptive case, is applied here in a dynamically adaptive fashion. In this first study, no dynamic load balancing was carried out. Two significant benchmarks are considered, comparing the results of adaptive and non-adaptive simulations. The proposed dynamically adaptive approach allows for a significant reduction of the computational cost of representative LES computation, while allowing to maintain the level of accuracy guaranteed by LES carried out with constant, maximum polynomial degree values. (C) 2020 Elsevier Inc. All rights reserved.