Methods for Predicting Transonic Flutter Using Simple Data Models

Gust loads may have detrimental impacts on flight including increased structural and aerodynamic loads, structural deformation, and decreased flight dynamic performance. This technology has been demonstrated to improve current gust load alleviation by use of a trailing-edge, free-floating surface control with a mass balance. Immediately upon impact, the inertial response of the mass balance shifts the center of gravity in front of the hinge line to develop an opposing aerodynamic force alleviating the load felt by the wing. This passive gust alleviation control covering 33% of the span of a cantilever wing was tested in NASA Langleys low speed wind tunnel and found to reduce wing response by 30%. While ongoing experimental work with new laser sensing technologies is predicted to similarly reduce gust load, simplicity of design of the present invention may be advantageous for certification processes. Additionally, this passive technology may provide further gust alleviation upon extending the use of the control to the entire trailing edge of the wing or upon incorporation with current active gust alleviation systems. Importantly, the technology can be easily incorporated into to the build of nearly all fixed wing aircrafts and pilot control can be maintained through a secondary trim tab. Though challenging to retrofit, passive gust alleviation could enable use of thinner, more efficient wings in new plane design.

According to the International Air Transport Association statistics, the annual fuel cost for the global airline industry is estimated to be about $140 billion in 2017. Therefore, fuel cost is a major cost driver for the airline industry. Advanced future transport aircraft will likely employ adaptive wing technologies that enable the wings of those aircraft to adaptively reconfigure themselves in optimal shapes for improved aerodynamic efficiency throughout the flight envelope. The need for adaptive wing technologies is driven by the cost of fuel consumption in commercial aviation. NASA Ames has developed a novel way to address aerodynamic inefficiencies experienced during aircraft operation. The real-time drag optimization control method uses an on-board, real-time sensor data gathered from the aircraft conditions and performance during flight (such as engine thrust or wing deflection). The sensor data are inputted into an on-board model estimation and drag optimization system which estimates the aerodynamic model and calculates the optimal settings of the flight control surfaces. As the wings deflect during flight, this technology uses an iterative approach whereby the system continuously updates the optimal solution for the flight control surfaces and iteratively optimizes the wing shape to reduce drag continuously during flight. The new control system for the flight control surfaces can be integrated into an existing flight control system. This new technology can be used on passenger aircraft, cargo aircraft, or high performance supersonic jets to optimize drag, improve aerodynamic efficiency, and increase fuel efficiency during flight. In addition, it does not require a specific aircraft math model which means it does not require customization for different aircraft designs. The system promises both economic and environmental benefits to the aviation industry as less fuel is burned.

RAM-C interfaces with computational software to provide test logic and manage a unique process that implements three main bodies of theory: (a) aircraft system identification (SID), (b) design of experiment (DOE), and (c) CFD. SID defines any number of alternative estimation methods that can be used effectively under the RAM-C process (e.g., machine learning techniques, regression, neural nets, fuzzy modeling, etc.). DOE provides a statistically rigorous, sequential approach that defines the test points required for a given model complexity. Typical DOE test points are optimized to reduce either estimation error or prediction error. CFD provides a large range of fidelity for estimating aircraft aerodynamic responses. In initial implementations, NASA researchers “wrapped” RAM-C around OVERFLOW, a NASA-developed high-fidelity CFD flow solver. Alternative computational software requiring less time and computational resources could be also utilized. RAM-C generates reduced-order aerodynamic models of aircraft. The software process begins with the user entering a desired level of fidelity and a test configuration defined in terms appropriate for the computational code in use. One can think of the computational code (e.g., high-fidelity CFD flow solver) as the “test facility” with which RAM-C communicates with to guide the modeling process. RAM-C logic determines where data needs to be collected, when the mathematical model structure needs to increase in order, and when the models satisfy the desired level of fidelity. RAM-C is an efficient, statistically rigorous, automated testing process that only collects data required to identify models that achieve user-defined levels of fidelity – streamlining the modeling process and saving computational resources and time. At NASA, the same Rapid Aero Modeling (RAM) concept has also been applied to other “test facilities” (e.g., wind tunnel test facilities in lieu of CFD software).

This technique injects precisely defined stationary transient growth disturbances into the free air slipstream over a wing that develop into streamwise elongated "streaks." These streaks are created with an alternating pattern of low and high streamwise velocity in the boundary layer flow adjacent to the aerodynamic surface of interest. Judicious selection of streak wavelength, amplitude, and profile allows the first-mode instability waves responsible for transition via oblique mode breakdown to be damped while the remaining, uncontrolled waves are kept below an amplification threshold. A similar control concept is also applicable to second mode transition at hypersonic Mach numbers.

Distributed propulsion and lightweight flexible structures on air vehicles pose a significant opportunity to improve mission performance while meeting next generation requirements including reduced fuel burn, lower emissions, and enhanced takeoff and landing performance. Flexible wing-shaping aircraft using distributed propulsion enable the ability to achieve improved aerodynamic efficiency while maintaining aeroelastic stability. Wing shaping concepts using distributed propulsion leverage the ability to introduce forces/ moments into the wing structure to affect the wing aerodynamics. This can be performed throughout the flight envelope to alter wing twist, hence local angle of attack, as the wing loading changes with air vehicle weight during cruise. Thrust-induced lift can be achieved by distributed propulsion for enhanced lift during take-off and landing. For a highly flexible wing structure, this concept could achieve a 4% improvement in lift-to-drag ratio, hence reduced fuel burn, as compared to a conventional stiff wing. This benefit is attributed to a reduction in lift-induced drag throughout the flight envelope by actively shaping the spanwise lift distribution using distributed propulsion. Vertical tail size could be reduced by utilizing differential thrust flight-propulsion control. This will result in weight reduction to achieve further fuel savings. Aeroelastic stability is addressed in the design process to meet flutter clearance requirements by proper placement of the propulsion units. This technology enables synergistic interactions between lightweight materials, propulsion, flight control, and active aeroelastic wing shaping control for reducing the environmental impact of future air vehicles.