Preprints
https://doi.org/10.5194/wes-2025-263
https://doi.org/10.5194/wes-2025-263
21 Jan 2026
 | 21 Jan 2026
Status: this preprint is currently under review for the journal WES.

Aeroelastic Validation of ExaWind for the Pazy Wing Wind Tunnel Experiment

Neil Matula, Gopal Yalla, Bumseok Lee, Ganesh Vijayakumar, Nathaniel deVelder, Lawrence Cheung, Michael Sprague, and Paul Crozier

Abstract. This paper presents the results of a validation campaign of the fluid-structure interaction capability of the ExaWind software suite using the Pazy wing case, an aeroelastic benchmark featuring large nonlinear deformations of a very flexible wing under low-speed conditions. The simulations used the incompressible Reynolds-averaged Navier–Stokes equations equipped with a Shear-Stress Transport turbulence model for the fluid dynamics, together with a geometrically exact nonlinear beam model for the structural dynamics. The simulations yielded predictions of pre-flutter static deflections and flutter onset speeds that demonstrated strong agreement with both wind-tunnel data and the computational results contributed to the Large Deflection Working Group of the 3rd Aeroelastic Prediction Workshop.

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Neil Matula, Gopal Yalla, Bumseok Lee, Ganesh Vijayakumar, Nathaniel deVelder, Lawrence Cheung, Michael Sprague, and Paul Crozier

Status: open (until 18 Feb 2026)

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Neil Matula, Gopal Yalla, Bumseok Lee, Ganesh Vijayakumar, Nathaniel deVelder, Lawrence Cheung, Michael Sprague, and Paul Crozier
Neil Matula, Gopal Yalla, Bumseok Lee, Ganesh Vijayakumar, Nathaniel deVelder, Lawrence Cheung, Michael Sprague, and Paul Crozier
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Latest update: 21 Jan 2026
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This paper presents the results of a validation campaign of the fluid-structure interaction capability of the ExaWind software suite using the Pazy wing case, an aeroelastic benchmark featuring large nonlinear deformations of a very flexible wing under low-speed conditions.  The results show good agreement with the published experimental and simulation results for tip deflection and flutter onset speed, and provide credibility evidence for the predictive capability of the ExaWind suite.
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