Uncertainty quantification of the flow predictions around the NATO STO AVT-251 unmanned combat aerial vehicle
Uncertainty quantification of the flow predictions around the NATO STO AVT-251 unmanned combat aerial vehicle
Turbulence models based on Reynolds-averaged Navier-Stokes (RANS) equations remain the workhorse in the computation of high Reynolds-number wall-bounded flows. While these methods have been deployed to design the configuration developed within the NATO STO AVT-251 Task Group, their deficiencies in modelling complex flows are well-documented. However, an understanding of the sources of errors and uncertainties in RANS solvers, arising for example from different numerical schemes and flow modelling techniques, is missing to date. The aim of this work is to establish and quantify the impact that epistemic uncertainties within RANS solvers have on the flow predictions (shock wave locations, vortex breakdown, etc.). This will produce a range of all possible values of interest due to the inherent uncertainty of RANS solvers, which is expected to be highly dependent on the flow conditions and geometry configuration. This information, in turn, will be used to establish the robustness of the AVT-251 design and its performance metrics considering uncertain predictions of the dominant flow features. The benefits of this work will also extend to the structural design, whereby appropriate factors of safety can be integrated in the process.
American Institute of Aeronautics and Astronautics
Da Ronch, Andrea
a2f36b97-b881-44e9-8a78-dd76fdf82f1a
Drofelnik, Jernej
e785f695-61ef-4afc-bf0a-9dc7966f5516
Van Rooij, Michel P.C.
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Kok, Johan C.
43be06c1-dd8a-4b61-ab6d-0285b007144a
Panzeri, Marco
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D’Ippolito, Roberto
ac94d1e2-310e-41fc-ae5e-a6848dee9ae2
25 June 2018
Da Ronch, Andrea
a2f36b97-b881-44e9-8a78-dd76fdf82f1a
Drofelnik, Jernej
e785f695-61ef-4afc-bf0a-9dc7966f5516
Van Rooij, Michel P.C.
06c2d00d-d719-4cf5-8bf9-fe3e44486f6e
Kok, Johan C.
43be06c1-dd8a-4b61-ab6d-0285b007144a
Panzeri, Marco
e253f5de-c3e8-4777-a790-b82bdee6daba
D’Ippolito, Roberto
ac94d1e2-310e-41fc-ae5e-a6848dee9ae2
Da Ronch, Andrea, Drofelnik, Jernej, Van Rooij, Michel P.C., Kok, Johan C., Panzeri, Marco and D’Ippolito, Roberto
(2018)
Uncertainty quantification of the flow predictions around the NATO STO AVT-251 unmanned combat aerial vehicle.
In 2018 Applied Aerodynamics Conference.
American Institute of Aeronautics and Astronautics..
(doi:10.2514/6.2018-2997).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Turbulence models based on Reynolds-averaged Navier-Stokes (RANS) equations remain the workhorse in the computation of high Reynolds-number wall-bounded flows. While these methods have been deployed to design the configuration developed within the NATO STO AVT-251 Task Group, their deficiencies in modelling complex flows are well-documented. However, an understanding of the sources of errors and uncertainties in RANS solvers, arising for example from different numerical schemes and flow modelling techniques, is missing to date. The aim of this work is to establish and quantify the impact that epistemic uncertainties within RANS solvers have on the flow predictions (shock wave locations, vortex breakdown, etc.). This will produce a range of all possible values of interest due to the inherent uncertainty of RANS solvers, which is expected to be highly dependent on the flow conditions and geometry configuration. This information, in turn, will be used to establish the robustness of the AVT-251 design and its performance metrics considering uncertain predictions of the dominant flow features. The benefits of this work will also extend to the structural design, whereby appropriate factors of safety can be integrated in the process.
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e-pub ahead of print date: 24 June 2018
Published date: 25 June 2018
Venue - Dates:
36th AIAA Applied Aerodynamics Conference, 2018, , [state] GA, United States, 2018-06-25 - 2018-06-29
Identifiers
Local EPrints ID: 424441
URI: http://eprints.soton.ac.uk/id/eprint/424441
PURE UUID: feda3474-2acc-421c-befb-04aef61aa98b
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Date deposited: 05 Oct 2018 11:37
Last modified: 18 Mar 2024 03:25
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Contributors
Author:
Jernej Drofelnik
Author:
Michel P.C. Van Rooij
Author:
Johan C. Kok
Author:
Marco Panzeri
Author:
Roberto D’Ippolito
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