Probabilistic aeroelastic analysis of high-fidelity composite aircraft wings with manufacturing variability
Probabilistic aeroelastic analysis of high-fidelity composite aircraft wings with manufacturing variability
Safety margins of aerospace structures can be improved through altering the laminate parameters of composite materials to increase flutter and divergence velocities. \textcolor{red}{Existing work demonstrates the impact of material uncertainties on low-fidelity structural models that are not sufficient to represent realistic aircraft designs.} A gap exists in quantifying laminate parameter uncertainties on aeroelasticity for high-fidelity three-dimensional composite structures in realistic tailored designs. This paper puts forward an efficient methodology for uncertainty quantification on the aeroelastic characteristics of three-dimensional composite structures using FE-based parametric composite models and advanced Kriging surrogate models. The methodology is tested on both \textcolor{red}{low and high fidelity} case studies to represent the composite wing structure. Similarities between the case studies are observed in the coefficient of variance of all hard flutter modes being within 0.15-1.4\% of each other. The difference was found for divergence and soft flutter velocities where the coefficient of variance could be over ten times higher in the \textcolor{red}{high fidelity} case. Global sensitivity results revealed similar physical behaviour cases can be produced from both studies at early design stages.
McGurk, Michael
ff8abe6b-24b8-4d53-8af2-c735ddf26d4f
Yuan, Jie
4bcf9ce8-3af4-4009-9cd0-067521894797
Stodieck, Olivia
72138d22-f477-4e31-a478-8fa2b3ffe8bd
McGurk, Michael
ff8abe6b-24b8-4d53-8af2-c735ddf26d4f
Yuan, Jie
4bcf9ce8-3af4-4009-9cd0-067521894797
Stodieck, Olivia
72138d22-f477-4e31-a478-8fa2b3ffe8bd
McGurk, Michael, Yuan, Jie and Stodieck, Olivia
(2023)
Probabilistic aeroelastic analysis of high-fidelity composite aircraft wings with manufacturing variability.
Composite Structures.
(In Press)
Abstract
Safety margins of aerospace structures can be improved through altering the laminate parameters of composite materials to increase flutter and divergence velocities. \textcolor{red}{Existing work demonstrates the impact of material uncertainties on low-fidelity structural models that are not sufficient to represent realistic aircraft designs.} A gap exists in quantifying laminate parameter uncertainties on aeroelasticity for high-fidelity three-dimensional composite structures in realistic tailored designs. This paper puts forward an efficient methodology for uncertainty quantification on the aeroelastic characteristics of three-dimensional composite structures using FE-based parametric composite models and advanced Kriging surrogate models. The methodology is tested on both \textcolor{red}{low and high fidelity} case studies to represent the composite wing structure. Similarities between the case studies are observed in the coefficient of variance of all hard flutter modes being within 0.15-1.4\% of each other. The difference was found for divergence and soft flutter velocities where the coefficient of variance could be over ten times higher in the \textcolor{red}{high fidelity} case. Global sensitivity results revealed similar physical behaviour cases can be produced from both studies at early design stages.
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Submitted date: July 2023
Accepted/In Press date: 4 December 2023
Additional Information:
Funding Information:
The authors acknowledge the support of the EPSRC Impact Acceleration Account project through the University of Strathclyde, and the technical support
from Dapta Ltd. Michael McGurk acknowledges the funding support of the EPSRC Doctoral Training Partnership (DTP) studentship for his PhD study at the
University of Strathclyde. The authors are also grateful for the valuable feedback from Dr Liu Yang at the University of Strathclyde.
Identifiers
Local EPrints ID: 483011
URI: http://eprints.soton.ac.uk/id/eprint/483011
ISSN: 0263-8223
PURE UUID: 7b3a207e-4975-44e7-aad1-0d90ffe23854
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Date deposited: 19 Oct 2023 16:38
Last modified: 18 Mar 2024 04:12
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Author:
Michael McGurk
Author:
Jie Yuan
Author:
Olivia Stodieck
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