The effect of variations in experimental and computational fidelity on data assimilation approaches
The effect of variations in experimental and computational fidelity on data assimilation approaches
We conduct a comprehensive analysis of two data assimilation methods: the first utilizes the discrete adjoint approach with a correction applied to the production term of the turbulence transport equation, preserving the Boussinesq approximation. The second is a state observer method that implements a correction in the momentum equations alongside a turbulence model, both applied to fluid dynamics simulations. We investigate the impact of varying computational mesh resolutions and experimental data resolutions on the performance of these methods within the context of a periodic hill test case. Our findings reveal the distinct strengths and limitations of both methods, which successfully assimilate data to improve the accuracy of a RANS simulation. The performance of the variational model correction method is independent of input data and computational mesh resolutions. The state observer method, on the other hand, is sensitive to the resolution of the input data and CFD mesh.
Data assimilation, Discrete adjoint, Separated flow, State observer, Turbulence modelling, Variational method
431-450
Thompson, Craig
f6a694f9-2c34-4baf-bd66-d8152432c277
Cadambi Padmanaban, Uttam
234ed0b7-6b0a-4582-b548-5fe9cf86c8fd
Ganapathisubramani, Bharath
5e69099f-2f39-4fdd-8a85-3ac906827052
Symon, Sean
2e1580c3-ba27-46e8-9736-531099f3d850
2 July 2024
Thompson, Craig
f6a694f9-2c34-4baf-bd66-d8152432c277
Cadambi Padmanaban, Uttam
234ed0b7-6b0a-4582-b548-5fe9cf86c8fd
Ganapathisubramani, Bharath
5e69099f-2f39-4fdd-8a85-3ac906827052
Symon, Sean
2e1580c3-ba27-46e8-9736-531099f3d850
Thompson, Craig, Cadambi Padmanaban, Uttam, Ganapathisubramani, Bharath and Symon, Sean
(2024)
The effect of variations in experimental and computational fidelity on data assimilation approaches.
Theoretical and Computational Fluid Dynamics, 38 (3), .
(doi:10.1007/s00162-024-00708-y).
Abstract
We conduct a comprehensive analysis of two data assimilation methods: the first utilizes the discrete adjoint approach with a correction applied to the production term of the turbulence transport equation, preserving the Boussinesq approximation. The second is a state observer method that implements a correction in the momentum equations alongside a turbulence model, both applied to fluid dynamics simulations. We investigate the impact of varying computational mesh resolutions and experimental data resolutions on the performance of these methods within the context of a periodic hill test case. Our findings reveal the distinct strengths and limitations of both methods, which successfully assimilate data to improve the accuracy of a RANS simulation. The performance of the variational model correction method is independent of input data and computational mesh resolutions. The state observer method, on the other hand, is sensitive to the resolution of the input data and CFD mesh.
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s00162-024-00708-y
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Accepted/In Press date: 4 June 2024
e-pub ahead of print date: 2 July 2024
Published date: 2 July 2024
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Publisher Copyright:
© The Author(s) 2024.
Keywords:
Data assimilation, Discrete adjoint, Separated flow, State observer, Turbulence modelling, Variational method
Identifiers
Local EPrints ID: 491853
URI: http://eprints.soton.ac.uk/id/eprint/491853
ISSN: 0935-4964
PURE UUID: 9545e043-b972-4711-90a9-1923b7243442
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Date deposited: 04 Jul 2024 17:18
Last modified: 08 Aug 2024 01:47
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Author:
Craig Thompson
Author:
Uttam Cadambi Padmanaban
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