On-line Mu-Method for Robust Flutter Prediction in Expanding a Safe Flight Envelope for an Aircraft Model Under Flight Test

Patent: US6,216,063

Objective

The National Aeronautics and Space Administration seeks companies to license its patented On-line Mu-Method for Robust Flutter Prediction in Expanding a Safe Flight Envelope for an Aircraft Model Under Flight Test (US Patent Number 6,216,063). This method was developed by NASA to supplement and increase the efficiency of traditional methods of determining an aircraft's flutter margin envelope for safe operation solely by flight testing. NASA's innovation works by using both computed model data and flight data. The on-line estimation of flutter margins is computed dynamically during actual flight testing. The method provides a more robust flutter margin prediction, thereby enabling the safe flight condition envelope to be determined without actually flying an aircraft to conditions anywhere close to a flutter point.

Product Profile

NASA's innovative method for robust flutter prediction and expansion of the safe flight envelope is a dynamic process using a Flutterometer algorithm that draws on computer-generated aircraft models and actual flight test data. Each aircraft system model is defined by a structured singular value, Mu. Mu is used in NASA's Flutterometer algorithm to compute robust flutter margins based on a computer model of the particular aircraft plant. Ensuing flight test data are fed back into the algorithm to predict a new, expanded flutter point at a higher dynamic pressure. If this newly predicted flutter point differs significantly from the present flight test condition, then the safe flight envelope can be expanded to the predicted point. This process is repeated until the difference between the predicted flutter point and the present flight test condition is small, at which point the most recently predicted flutter point becomes a point on the flutter margin. The main advantage of the Mu-method over traditional methods is that with each iteration at a new flight condition, a new predicted flutter point is determined.

The Flutterometer can also reduce the risk and cost associated with flight flutter testing by predicting unstable flight conditions from a current test point in order to determine what change in flight conditions may be safely considered for the next test point.

Benefits

• Improves flight test efficiency while maintaining a high level of safety
• Provides an on-line method of producing a robust flutter margin envelope
• Mathematically conceptualizes the aircraft to a structured singular value, Mu, that guarantees a level of modeling errors to which the aircraft is robustly stable
• Allows for the formation of a realistic representation of modeling errors that can be described as the difference between the predicted and measured flight data
• Generates reliable and confident predictions of flutter margin
• Algorithm uses flight test data to update continuously the structured singular value, Mu
• Technology does not make any assumptions regarding the number or type of modes that interact as the flutter mechanism
• Automatically takes into account time-varying changes in the aircraft that give rise to modulating errors
• Computation may be done in a control room online, or onboard if sufficient resources exist, providing real-time information about changes in flutter margin as well as damping trend to indicate an imminent flutter condition
• Technology is accurate and cost effective

Potential Commercial Uses

NASA's On-line Mu-Method for Robust Flutter Prediction in Expanding a Safe Flight Envelope for an Aircraft Model Under Flight Test is suitable for the following commercial applications:

• Commercial aircraft design and manufacturing
• Military aircraft design and manufacturing
• Testing of redesigned and reconfigured aircraft
• Sports and race car design and manufacturing
• Speed boat design and manufacturing
• Designers and makers of airfoils
• Applications with damping characteristic curves similar to those of flight flutter

Technical Basics

Flutter margins have traditionally been established by a two-step process. The first step involves creation of a "best guess" computer model of the aircraft and off-line estimation of flutter margins using a well-known p-k method. If the computed margins are too small, the aircraft is redesigned and the model modified to reflect the redesign. If the computed margins are large enough, flight testing ensues. The flight testing alone then determines the boundaries of the safe operating envelope. During flight testing, the aircraft is taken to a test point at test condition F, a dynamic pressure defined by airspeed and altitude, for example. Flight data is analyzed by a computer which estimates dynamics from flight data such as damping. Levels and trend of the dynamics are evaluated and if they are acceptable, the aircraft is taken to a new flight condition closer to the last estimated aeroelastic flutter condition. The flight data from this new condition are then analyzed, levels and trends of the dynamics are re-evaluated, and the process may then be repeated. When the evaluation of the trends for any flight test condition is not acceptable, then that test condition is considered to be a point on the flutter margin. The information from the computational model step is not used in the flight test step and the information generated in the flight test is not used in the computational model step.

The traditional method of testing the flutter margins of aircraft using flight testing only is risky due to the inherently unreliable nature of damping trends. This results in greater time and cost in flight testing. Expansion of the flight envelope occurs very slowly because flight test conditions must be changed in very small increments to avoid unforeseen sudden changes and instabilities.

The On-line Mu-analysis method, makes use of both the aircraft model computations and the flight test data concurrently to determine the flutter margins. Thus, in this method, the on-line estimation of flutter margins is computed dynamically during the actual flight test. NASA's method gets its name from the single parameter, Mu, that is repeatedly updated during the flight test. The parameter is a measure of how sensitive the model predictions are to uncertainties arising, for example, from non-repeatable flight test anomalies, time varying aircraft parameters and nonlinearities.  

Licensing opportunities are available.