Cluster-based estimation and control of turbulent aeroelastic flows
Abstract
The proposed research aims to advance aeroelastic modeling by predicting the dynamics resulting from the interaction of aerodynamic flows with flexible surfaces in motion, with a particular focus on suppressing flutter. This study employs numerical, experimental, and data-driven approaches to develop new sensing and flow control strategies that enable the control of flow transitions and wing structure deformation using a modular, cluster-based framework. Flutter suppression is a critical area of investigation as it improves the stability of high-aspect-ratio wings and reduces the cost of control, leading to more efficient and effective aircraft systems. The study will investigate the onset of flutter in turbulent environments, which can cause the aerodynamic forces acting on the aircraft to change rapidly and unpredictably, leading to large changes in wing deformation. The estimation and control strategies developed in this study are designed to be accurate and robust in the presence of experimental measurement noise, which is a critical challenge in developing control systems for aeroelastic systems. The control strategies developed in this study leverage natural transitions in the system to provide control for a minimum number of transitions along a desired path. This approach reduces the cost of control and is highly desirable for the online control of flutter. The study will explore various actuation techniques for suppressing flutter, including blowing actuation, piezo and thermal actuation in experiments, which can help to optimize the aerodynamic performance of aircraft systems. The results of this study will have significant implications for the development of more effective and efficient aircraft systems, including unmanned aerial vehicles and next-generation aircraft designs. This research will ultimately provide valuable contributions to the field of aeroelasticity and advance state-of- the-art flutter suppression and control strategies.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 06, 2024
- Source ID
- FA95502310483
Entities
People
- Aditya Nair
Organizations
- Air Force Office of Scientific Research
- Nevada System of Higher Education
- Office of the Secretary of Defense