Carlsson, Magnus (2022) Towards Improved Scale-Resolving Modeling and Simulations of Turbulent Flows. Dissertation, CHALMERS UNIVERSITY OF TECHNOLOGY.
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Abstract
Scale-resolving simulations are viewed as powerful means for predicting complex turbulent flows, as often encountered in aeronautical applications. However, since turbulent scales span over a considerable range from the smallest Kolmogorov scales to the largest of equivalence to configuration size, scale-resolving computations are often demanding on computational resources and, furthermore, on the underlying numerical methods used in the simulations. Nonetheless, hybrid RANS (Reynolds-Averaged Navier-Stokes)-LES (Large-Eddy Simulation) techniques are considered computationally accurate and affordable for aeronautical industry applications. This thesis explores and develops numerical methods suitable for hybrid RANS-LES. These methods are implemented in the Computational Fluid Dynamics (CFD) solver M-Edge.
Item URL in elib: | https://elib.dlr.de/192108/ | ||||||||
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Document Type: | Thesis (Dissertation) | ||||||||
Title: | Towards Improved Scale-Resolving Modeling and Simulations of Turbulent Flows | ||||||||
Authors: |
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Date: | December 2022 | ||||||||
Refereed publication: | Yes | ||||||||
Open Access: | Yes | ||||||||
Number of Pages: | 80 | ||||||||
Status: | Published | ||||||||
Keywords: | Numerical methods, High-order gradient reconstruction, Scale-resolving simulation, Turbulence modelling, Hybrid RANS-LES, Synthetic Turbulence, Compressible flow | ||||||||
Institution: | CHALMERS UNIVERSITY OF TECHNOLOGY | ||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||
HGF - Program: | Aeronautics | ||||||||
HGF - Program Themes: | Efficient Vehicle | ||||||||
DLR - Research area: | Aeronautics | ||||||||
DLR - Program: | L EV - Efficient Vehicle | ||||||||
DLR - Research theme (Project): | L - Digital Technologies | ||||||||
Location: | Göttingen | ||||||||
Institutes and Institutions: | Institute for Aerodynamics and Flow Technology > CASE, GO | ||||||||
Deposited By: | Probst, Axel | ||||||||
Deposited On: | 14 Dec 2022 11:25 | ||||||||
Last Modified: | 14 Dec 2022 11:25 |
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