Pinpointing Consumption "Sweet Spot" Makes Formation Flight More Fuel Efficient

Vehicles designed for purposes of exploration of the planets and other atmospheric bodies in the Solar System favor the use of mid-Lift/Drag blunt body geometries. Such shapes can be designed so as to yield favorable hypersonic aerothermodynamic properties for low heating and hypersonic aerodynamic properties for maneuverability and stability. The entry trajectory selected influences entry peak heating and integrated heating loads which in turn influences the design of the thermal protection system. A nominal is used to compare each shape considered. The vehicle will be subject to both launch and entry loading along with structural integrity constraints that may further influence shape design. Further, such vehicles must be sized so as to fit on existing or realizable launch vehicles, often within existing launch payload shroud constraints.

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.

The term Advanced Air Mobility (AAM) refers to a new mode of transportation utilizing highly automated airborne vehicles for transporting goods and/or people. The adoption of widespread use of AAM vehicles will necessitate a network of vertiports located throughout a geographical region. A vertiport refers to a physical structure for the departure, arrival, and parking/storage of AAM vehicles. NASA-developed Vertiport Assessment and Mobility Operations System (VAMOS!) enables identifying geographical locations suitable for locating a vertiport or assessing suitability of pre-selected locations. For example, suitability evaluation factors include zoning, land use, transit stations, fire stations, noise, and time-varying factors like congestion and demand. The vertiport assessment system assigns suitability values to these factors based on user-input, and types, including location-based (e.g., proximity to mass transit stations), level-based (e.g., noise levels), characteristic-based (e.g., residential zoning), and time-based (e.g., demand). Based on user input, the system spreads a grid over the geographical area, specifies importance criteria and weights for scaling the impact of the suitability factors, and identifies specific sub-regions as candidate locations. The candidate sub-regions are shown on a user interface map overlay in a color-coded gradient that reflects the suitability strength for a sub-region. Vertiport locations are selected within these sub-regions. These candidate vertiport locations are refined by establishing feasibility of flight between them. VAMOS! includes a modeling component and a simulation component. The modeling component assists a user to identify one or more geographical locations at which a vertiport may be physically built. The simulation component of the technology displays, in real-time, the simulated operational behavior of AAM vehicles and in the context of their projected flight paths combined with data dynamically obtained from live sources. These data sources can be from the Federal Aviation Administration (FAA) or other private or public governing bodies, from one or more AAM vehicles in flight, and from weather sources.

For rapid parachute deployment simulation, the framework and methodology provided by the simulation database uses parametrized aerodynamic data for a variety of environmental conditions, air taxi design parameters, and landing system designs. The database also includes a compilation of drag coefficients, thrust and lift forces, and further relevant aerodynamic parameters utilized in the simulated flight of a proposed air taxi. The database and framework can be constructed using simulated data that accounts for oscillatory breathing of parachutes. The methodology can further employ an overset grid of body-fitted meshes to accurately capture deployment of an internally-stored parachute, as well as descent of the air taxi and deployed parachute. The systems and methods of the disclosed technology can be utilized with existing CFD solvers in a plug-and-play manner, such that the framework can be integrated to directly improve the performance of these solvers and the machines on which they are installed. The framework itself can employ parallelization to enable distributed solution of intensive CFD simulations to build a robust database of simulated data. Further, as up to 90% of computational time is spent in the calculation of aerodynamic parameters for use in coupled trajectory equations, the framework can significantly reduce the computational costs and design time for safe landing systems for air taxis. These reductions can lead to lower costs for design processes, while enabling rapid design and testing prior to physical prototyping.

Adverse yaw, present in current aircraft design, is the adverse horizontal movement around a vertical axis of an aircraft; the yaw opposes the direction of a turn. As an aircraft turns, differential drag of the left and right wings while banking contributes to aircraft yaw. Proverse yaw—yawing in the same direction as a turn—would optimize aircraft performance. Initial results from flight experiments at Armstrong demonstrated that this wing design unequivocally established proverse yaw. This wing design further reduces drag due to lift at the same time. How It Works The Armstrong team (supported by a large contingent of NASA Aeronautics Academy interns) built upon the 1933 research of the German engineer Ludwig Prandtl to design and validate a scale model of a non-elliptical loaded wing that reduces drag and increases efficiency. The key to the innovation is reducing the drag of the wing through use of an alternative bell-shaped spanload, as opposed to the conventional elliptical spanload. To achieve the bell spanload, designers used a sharply tapered wing, with 12 percent less wing area than the comparable elliptical spanload wing. The new wing has 22 percent more span and 11 percent less area, resulting in an immediate 12 percent drag reduction. Furthermore, using twist to achieve the bell spanload produces induced thrust at the wing tips, and this forward thrust increases when lift is increased at the wingtips for roll control. The result is that the aircraft rolls and yaws in the same direction as a turn, eliminating the need for a vertical tail. When combined with a blended-wing body, this approach maximizes aerodynamic performance, minimizes weight, and optimizes flight control. Why It Is Better Conventional aircraft make use of elliptical loaded wings to minimize drag. However, achieving aircraft stability and control in conventional elliptical wings produces a strong adverse yaw component in roll control (i.e., the aircraft will yaw the opposite direction with application of roll control). Therefore, a vertical tail or some other method of direct yaw control is required, such as split elevons for use as drag rudders. The use of elliptical wings also results in a suboptimal amount of structure to carry the integrated wing bending moment. Adopting the bell-shaped spanload change results in an immediate 12 percent drag reduction. In addition, optimization of the overall aircraft configuration is projected to achieve additional significant overall performance increases.