Calculation of Unsteady Aerodynamic Loads Using Fast-Response Pressure-Sensitive Paint (PSP)

In order to maintain the low cost, simplicity, and quick turnaround of cold-flow testing while improving accuracy, NASA evaluated unconventional gases for use as simulants. During such evaluations, NASA discovered that by adjusting stagnation temperature, the isentropic exponent of ethane can be tuned to approximate those of common rocket propellants (e.g., hydrogen, hypergols, alcohols, and hydrocarbons). Furthermore, due to ethanes high auto-ignition temperature and resistance to condensation, tuned ethane enables testing of expansion ratios much larger than conventional inert-gas testing. To leverage this discovery, NASA developed a hardware-based system to treat ethane and obtain nozzle chamber conditions that match the appropriate aerodynamics for a specific test. The system, named HYPERFIRE, works in the following manner. Liquid ethane is transferred to a piston-style run tank, where it is pressurized. Then, the ethane is run through two insulated pebble beds where it is heated, vaporized, and stabilized. Finally, the treated ethane is transferred from the second pebble bed to a small thrust takeout structure, and through the test article. Control of valves and regulators is managed by an onboard computer, accessed via a LabVIEW™ interface. The system is mounted on a hurricane-resistant steel frame to enable transportation via forklift. Heated ethane reproduces the aerodynamics of combustion products at low temperatures relative to alternative testing methods. Thus, test articles can be manufactured using low-cost, low temperature rated, transparent materials (e.g., acrylic). In addition to reducing testing cost, this grants optical access to internal flowfields, enabling advanced diagnostic techniques (e.g., Schlieren imaging, particle image velocimetry) not possible with hot-fire testing and less meaningful with conventional cold-flow testing.

Although polystyrene microspheres are often the seed material of choice for subsonic airflow studies. These seed materials, however, do not provide any benefit for near wall measurements compared to other state-of-the-art seed materials. Consequently, in this innovation NASA scientists have developed this method of generating dye-doped polystyrene microspheres using novel synthetic approaches. The novel features of this invention are the utility of specific chemical functionalities, monomeric species, environmental additives (buffers), and polyelectrolytes to promote incorporation of dye molecules into developing polystyrene microspheres while enabling control of the spectral properties of the dye relative to pH dependence. These particles will have great utility for wind tunnel measurements near the wall where the state-of-the-art seed materials are not able to collect data. Additionally, the incorporation of these dyes will offer other avenues of data collection including temperature and pressure of the airflows and wind tunnel regions. Likewise, the ability to selectively filter the data collected from these dye-doped polystyrene microspheres can have further applications including the direct visualization of 2 or more fluid flows mixing, among other applications.

Transonic flutter is a pacing item in transport aircraft design in that it is crucial to characterize this phenomenon for each aircraft to prevent catastrophic failure. Aerodynamic study of flows around airfoils is a canonical problem that entails both experimental and computational approaches. While the transonic flutter prediction can be more accurate with high-fidelity Computational Fluid Dynamics (CFD) methods than with unsteady potential flow methods, the computational cost is high. Therefore, computationally efficient methods for transonic flutter prediction continue to be of high interest to the aircraft design community. NASA Ames has developed a novel method that eliminates the need for expensive calculations of aerodynamics of wing flutter, which typically takes tens of hours on a supercomputer. Such calculations are now replaced by machine-learning-based closed form solutions that provide the solution almost instantaneously. The technology presents a new approach to predict the flow around pitching NACA00 series airfoils. NACA airfoils are generally symmetric, and thus they do not possess camber. However, the invention can readily extend to wings with camber. This novel data modeling approach is orders of magnitude faster than the traditional CFD approach of predicting aerodynamic effects of transonic pitching airfoils. The data model is based on a subset of unsteady CFD simulations that train the model. The trained model then resolves the pitching airfoil in time for any other set on the order of a second, as compared with a complete CFD simulation that typically takes 30 hours on a supercomputer. The data model is demonstrated in this invention for transonic flow corresponding to Mach number of 0.755 over pitching NACA00 series airfoils for a reduced frequency range typical of flutter, i.e., k lies in the range 0.02 - 0.25.

This invention is an imaging method that requires very simple optics on an airborne vehicle, a camera with an appropriate lens, and an area on the ground that provides visual texture. The complexity with this method is in the image processing and not as much with the hardware or positioning, making Background Oriented Schlieren (BOS) an attractive candidate for obtaining high spatial resolution imaging of shock waves and vortices in flight. First, images are obtained of a visually textured background pattern from an appropriate altitude. Next, a series of images are collected of a vehicle in flight below the observer vehicle and over the same spot on the ground that serves as a background pattern. Shock waves are deduced from distortions of the background pattern resulting from the change in refractive index due to density gradients. The invention requires special software to create the schlieren images. The schlieren image is a contour plot of a two-dimensional data array of measured distortions, in pixel units. The results are used by researchers to help understand the flow phenomenon and compare to computational models. The BOS method also yields measured deflection distances, which can be used to determine the strength of a given density gradient. The system design and flight planning were based on the camera characteristics, airplane coordination, and airspace limitations.

The technology presents an on-board estimation, navigation and control architecture for multi-rotor drones flying in an urban environment. It consists of adaptive algorithms to estimate the vehicle's aerodynamic drag coefficients with respect to still air and urban wind components along the flight trajectory, with guaranteed fast and reliable convergence to the true values. Navigation algorithms generate feasible trajectories between given way-points that take into account the estimated wind. Control algorithms track the generated trajectories as long as the vehicle retains a sufficient number of functioning rotors that are capable of compensating for the estimated wind. The technology provides a method of measuring wind profiles on a drone using existing motion sensors, like the inertial measurement unit (IMU), rate gyroscope, etc., that are observably necessary for any drone to operate. The algorithms are used to estimate wind around the drone. They can be used for stability or trajectory calculations, and are adaptable for use with any UAV regardless of the knowledge of weight and inertia. They further provide real-time calculations without additional sensors. The estimation method is implemented using onboard computing power. It rapidly converges to true values, is computationally inexpensive, and does not require any specific hardware or specific vehicle maneuvers for the convergence. All components of this on-board system are computationally effective and are intended for a real time implementation. The method's software is developed in a Matlab/Simulink environment, and has executable versions, which are suitable for majority of existing onboard controllers. The algorithms were tested in simulations.