The most difficult phase of small Unmanned Aerial System (sUAS) deployment is autonomous operations below the notional 50 ft in urban landscapes. Understanding the feasibility of safely flying sUAS autonomously below 50 ft is a game changer for many civilian applications. This paper outlines three areas of research currently underway which address key challenges for flight in the urban landscape. These are: (1) Off-line and On-board wind estimation and accommodation; (2) Real-time trajectory planning via characterization of obstacles using a LIDAR; (3) On-board information fusion for real-time decision-making and safe trajectory generation.

Managing trajectory separation of unmanned aircraft is critical to ensuring accessibility, efficiency, and safety in low altitude airspace. The concept of a geo-fence has emerged as a way to manage trajectory separation. A geo-fence consists of distance buffers that enclose individual trajectories to identify a 'keep-in' region and/or enclose areas that identify 'keep-out' regions. The 'keep-in' geo-fence size can be defined as a static number or calculated as a function of vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Given that the fleet of Unmanned Aircraft Systems (UAS) operating in low altitude airspace will be numerous and non-homogeneous, calculating a 'keep-in' geo-fence will need to balance operational safety and efficiency. A recently tested UAS Traffic Management (UTM) prototype used a geo-fence size of 30 meters, horizontally and vertically, for every operation submitted. The goal of this work is to determine the feasibility of a generalized, simple algorithm that calculates geo-fence sizes as a function of vehicle performance and potential wind disturbances. The resulting geo-fence size could be smaller or larger because the vehicle performance in the presence of wind is considered, thus leading to trajectory separation that is safe and efficient.In this paper, two simplified methods were developed to determine the feasibility of calculating a geo-fence as a function of vehicle parameters and wind information. The first method calculates the geo-fence using basic vehicle parameters and wind sensor data in a set of algebraic-geometric equations. The second method models a generic PID control system that uses a simplified set of equations of motion for the plant and uses gain scheduling to account for wind disturbances. It was found that the Algebraic-Geometric Geo-fence Algorithm provides geofence sizes of approximately 15 meters horizontally and 5 meters vertically, which is much smaller than the UTM static value of 30 meters. In the PID Controller Geo-fence Algorithm it was found that the geo-fence size is further reduced to less than 5 meters, horizontally and vertically. These results reveal that implementing geo-fence calculations provide UTM with the ability to schedule and separate operations based on geofences that are dynamic to vehicle capability and environment, which is more efficient than using a single static geo-fence.

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The NASA Environmentally Responsible Aviation (ERA) Project explored enabling technologies to reduce impact of aviation on the environment. One project research challenge area was the study of advanced airframe and engine integration concepts to reduce community noise and fuel burn. To address this challenge, complex wind tunnel experiments at both the NASA Langley Research Center's (LaRC) 14'x22' and the Ames Research Center's 40'x80' low-speed wind tunnel facilities were conducted on a BOEING Hybrid Wing Body (HWB) configuration. These wind tunnel tests entailed various entries to evaluate the propulsion-airframe interference effects, including aerodynamic performance and aeroacoustics. In order to assist these tests in producing high quality data with minimal hardware interference, extensive Computational Fluid Dynamic (CFD) simulations were performed for everything from sting design and placement for both the wing body and powered ejector nacelle systems to the placement of aeroacoustic arrays to minimize its impact on vehicle aerodynamics. This paper presents a high-level summary of the CFD simulations that NASA performed in support of the model integration hardware design as well as the development of some CFD simulation guidelines based on post-test aerodynamic data. In addition, the paper includes details on how multiple CFD codes (OVERFLOW, STAR-CCM+, USM3D, and FUN3D) were efficiently used to provide timely insight into the wind tunnel experimental setup and execution.

The open-source Computational Fluid Dynamics software OpenFOAM is gaining wider acceptance in industry and academia for incompressible flow simulations. To date, there has been relatively little utilization of OpenFOAM for compressible external aerodynamic applications. The numerous turbulence models available in OpenFOAM makes it an attractive option for evaluating alternate Reynolds-Averaged Navier-Stokes (RANS) turbulent models to assess separated flow on atmospheric entry vehicles in the subsonic regime, where traditional turbulent models show reduced accuracy. This paper presents simulations of an axisymmetric capsule geometry at subsonic conditions using an OpenFOAM compressible flow solver. The results are compared with results from the NASA CFD code OVERFLOW and experimental data. These OpenFOAM simulations serve as a basis to explore OpenFOAM's extended turbulence models on compressible separated flows such as found on capsules.= Reynolds number based on space capsule diameter x, y, z = Cartesian coordinates U τ = friction velocity, u + = dimensionless velocity, u/U τ y+ = nondimensional wall distance, (yU τ /ν) ν = kinematic viscosity ρ = density τ w = wall shear stress