MODELING AND IDENTIFICATION OF UNSTEADY AIRWAKE DISTURBANCES ON ROTORCRAFT
Open Access
- Author:
- Sparbanie, Sade M
- Graduate Program:
- Aerospace Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- December 04, 2008
- Committee Members:
- Joseph Francis Horn, Thesis Advisor/Co-Advisor
Joseph Francis Horn, Thesis Advisor/Co-Advisor - Keywords:
- Unsteady Airwake
Genhel
Ship Airwake
Shipboard Landing - Abstract:
- Shipboard operations can be among the most difficult missions for rotorcraft pilots. Ordinary tasks such as precision hovering and landing can become increasingly difficult when performed in the unsteady winds that develop behind ship superstructures and above a moving ship deck. Often, the increased pilot workload is the limiting factor in determining whether a particular task can be performed in certain wind-over-deck conditions. In recent years, research has been performed to identify the ship gusts that are affecting pilots. If the unsteady winds can be identified, then gust rejection tools can be developed to help reduce pilot workload, and to make missions safer. Additionally, from accurate wind information, high fidelity real time simulations can be developed to test new engineering designs and to train naval pilots. This study further investigates gust identification methods by applying new engineering tools to develop offline and online gust identification processes. In the offline environment, aircraft time history data is used to develop colored noise filters that capture the spectral properties of the ship airwake gusts. When the continuous filter is transformed to a discrete transfer function, and excited with a white noise input, the power spectral density of the filtered output matches the power spectral properties of the stochastic portion of the unsteady airwake gusts. Although the offline gust identification method is successful, it can become computationally intensive to develop gust identification filters for every ship airwake condition a particular helicopter may encounter. As a result, an online identification method is examined. In this initial feasibility study, a sixth order autoregressive Burg model is used to determine colored noise filter coefficients in a real-time simulation environment. Initial results shows that the spectral properties of the filters converge to key peaks that were evident in the offline filter fitting method. In this study, the gust identification principles used to identify the stochastic airwake properties are then applied to create a real time simulation airwake model. Previous approaches to developing airwake simulation models of the shipboard environment employed computational fluid dynamics. Often the memory restrictions placed on the size of data allowed for the real time simulation applications either limited the fidelity of the CFD solution, or the length of unrepeatable data created. By relying on a grid of stochastic filters, which are excited with a random white noise, the computational effort is significantly reduced and guaranteed not to show noticeable repetitions in flight simulation data. The stochastic airwake is tested by performing simulated flight trajectories, as well as using piloted simulation testing at Sikorsky Aircraft. Initial results suggest similar pilot workload, demonstrating the feasibility and accuracy of the stochastic airwake simulation model.