High-Fidelity Aeroelastic Predictions of a Very Flexible Wing

Read full text
Authors: Michael J. Candon, Sitthichart Tohmuang, Arturo Delgado‐Gutiérrez, Pier Marzocca, Daniele Antonini, Giuliano Coppotelli, Marcello Righi
Cited by: 0
References: 17

Abstract

Air pollution and global warming are intensifying the need for lower-impact aviation technologies, motivating the development of highly flexible wings that offer significant potential for fuel-efficiency improvements. These configurations, however, present substantial aeroelastic challenges, as their structural dynamics and stability depend strongly on static deformation. CFD-based modeling of highly flexible wings such as the Pazy wing is therefore particularly relevant, as it captures nonlinear aerodynamic effects that lie beyond the fidelity of reduced-order or linearized formulations. As part of a broader collaboration between RMIT University and La Sapienza, the original Pazy wing experimental campaign is used here to validate PyFSI, a CFD-based aeroservoelastic simulation framework developed at RMIT University. This benchmarking study includes the prediction of (i) static deformations, (ii) modal characteristics, and (iii) time-marching CFD-based aeroelastic simulations to reproduce the hump-mode flutter mechanism and characterize the associated unsteady aerodynamics, particularly boundary-layer separation. The demonstrated agreement with experimental observations highlights the suitability of CFD-based aeroelastic modeling for analyzing next-generation ultra-flexible lifting surfaces. Although the present validation is performed at a moderate angle of attack of 5$^\circ$, the modeling framework is well suited to high-AOA conditions where large-scale separation and dynamic stall phenomena are expected to dominate the aeroelastic response, and extending the approach to these regimes is the subject of ongoing work.

Fields of Study & Subjects

Aeroelasticity and Vibration Control Computational Fluid Dynamics and Aerodynamics Fluid Dynamics and Vibration Analysis

Publication details

Journal / source
AIAA SciTech Forum
Publication date
8 January 2026
Language
EN