Aurora Flight Sciences (United States)

Abstract We present a case study of a moderate geomagnetic storm, which exhibits an abrupt relativistic enhancement in the heart of the radiation belt accompanied by low‐latitude purple auroral emission. The relativistic enhancement occurs on a timescale of tens of minutes and reaches MeV energies deep within the inner magnetosphere. The enhancement is concurrent with mesoscale purple patches which protrude below the pre‐existing auroral oval. We analyze the event using a novel combination of observational data sets and physics‐based modeling. This includes multispectral auroral imaging, dosimeter data from the Global Positioning System constellation, auroral transport modeling, and global geospace modeling. Our analysis reveals the cause of both the radiation belt enhancement and purple emission to be direct, mesoscale injections of electrons reaching relativistic energies. Finally, we show that these injections are most likely caused by near‐Earth reconnection which produces deeply depleted entropy bubbles capable of trapping and transporting energetic particles into the inner magnetosphere.

Aircraft conceptual design is a high-dimensional optimization problem, involving up to hundreds of continuous design variables and constraints. The design of novel aircraft concepts such as electric vertical takeoff and landing (eVTOL) vehicles can benefit from the systematic exploration of the design space through the use of gradient-based optimization. In this paper, we demonstrate the application of large-scale multidisciplinary design optimization (MDO) to NASA's lift-plus-cruise electric air taxi concept, using low and mid-fidelity physics-based simulations to model the aircraft. We improve the modeling fidelity from our previous work on the same air taxi concept through refined rotor-aerodynamic and aeroacoustic models as well as in-the-loop structural analysis. In addition, we expand the scope of the analysis to include several steady design conditions, a quasi-steady transition maneuver, structural sizing conditions, as well as one-engine-inoperative (OEI) scenarios, amounting to 18 design conditions. To perform the analysis and optimization, we use a newly developed software library called the Comprehensive Aircraft high-Dimensional Design Environment (CADDEE), which facilitates the integration of all discipline models. We solve a gross weight minimization problem with over 300 design variables and over 200 constraints, spanning all modeled disciplines. Results show a decrease in gross weight of 10% after a total optimization time of about 17 hours. These results demonstrate the effectiveness of applying of large-scale MDO to the aircraft conceptual design problem.

This article considers the problem of real-time control and learning in dynamic systems subjected to parameteric uncertainties. We propose a combination of a reinforcement learning (RL)-based policy in the outer loop suitably chosen to ensure stability and optimality for the nominal dynamics, together with adaptive control (AC) in the inner loop so that in real-time AC contracts the closed-loop dynamics toward a stable trajectory traced out by RL. In total, two classes of nonlinear dynamic systems are considered, both of which are control affine. The first class of dynamic systems utilizes equilibrium points and a Lyapunov approach, whereas second class of nonlinear systems uses contraction theory. AC-RL controllers are proposed for both classes of systems and shown to lead to online policies that guarantee stability using a high-order tuner and accommodate parameteric uncertainties and magnitude limits on the input. In addition to establishing a stability guarantee with real-time control, the AC-RL controller is also shown to lead to parameter learning with persistent excitation for the first class of systems. Numerical validations of all algorithms are carried out using a quadrotor landing task on a moving platform.

For eVTOL vehicles, electric motors are used to drive the lifting rotors and forward propellers in several possible combinations with independent and/or combined configurations. In order to meet these varying demands of rotors and propellers, there are many different motor topologies that have been studied, such as, radial flux motors with inner rotors, out-runner motors, and axial flux motors. Due to the nature of the rotor design for space and noise, the relatively low prop RPM favors electric machine designs with highest torque/weight ratio. Presented here is a design concept with novel rotor permanent magnet array with carbon fiber integration, combined with advanced cooling schemes to achieve the market leading torque/weight ratio for continuous operation as well as peak power modes. With the various operational modes of the aircraft, trade-studies must be made to achieve the overall best performance, for instance, the lift motor needs to be as light as possible with relatively short time operation during take-off and landing, which leads to an optimized design target with almost highest torque/weight ratio, while its energy conversion efficiency is sacrificed. The thermal behavior of a prototype design is also discussed in this paper.

In modal testing and finite element model correlation, analysts desire modal results using free-free or rigid boundary conditions to ease comparisons of test versus analytical data. It is often expensive both in cost and schedule to build and test with boundary conditions that replicate the free-free or rigid boundaries. Static test fixtures for load testing are often large, heavy, and unyielding, but do not provide adequate boundaries for modal tests because they are dynamically too flexible and often contain natural frequencies within the frequency range of interest of the test article. Dynamic coupling between the test article and test fixture complicates the model updating process because significant effort is required to model the test fixture and boundary conditions in addition to the test article. If there were a way to correct the modal results for fixture coupling, then setups used for other structural testing could be adequate for modal testing. In the case described in this paper, a partial static loads testing setup was used, which allowed significant schedule and cost savings by eliminating a unique setup for a modal test. A fixed base correction technique was investigated during modal testing of a flexible wing cantilevered from part of a static test fixture.The technique was successfully used to measure the wing modes de-coupled from the dynamically active test fixture. The technique is promising for future aircraft applications, but more research is needed.

The Deformable Mirror Demonstration Mission (DeMi) is a 6U CubeSat that will characterize the on-orbit performance of a Microelectromechanical Systems (MEMS) deformable mirror (DM) with both an image plane wavefront sensor and a Shack-Hartmann wavefront sensor (SHWFS). Coronagraphs on future space telescopes will require precise wavefront control to detect and characterize Earth-like exoplanets. High-actuator count MEMS deformable mirrors can provide wavefront control with low size, weight, and power. The DeMi payload will characterize the on-orbit performance of a 140 actuator MEMS Deformable Mirror (DM) with 5.5 μm maximum stroke, with a goal of measuring individual actuator wavefront displacement contributions to a precision of 12 nm. The payload will be able to measure low order aberrations to λ/10 accuracy and λ/50 precision, and will correct static and dynamic wavefront phase errors to less than 100 nm RMS. We present an overview of the payload design, the assembly, integration, and test process, and report on the development and validation of an optical diffraction model of the payload. Launch is planned for late 2019.

In 2017 and 2018, under National Aeronautics and Space Administration (NASA) sponsorship, the New York Unmanned Aircraft Systems (UAS) Test Site and Northeast UAS Airspace Integration Research (NUAIR) Alliance conducted a year-long research project that culminated in a UAS technology flight demonstration. The research project included the creation of a concept of operations, and development and demonstration of UAS technologies. The concept of operations was focused on an unmanned aircraft transiting from cruise through Class E airspace into a high-density urban terminal environment. The terminal environment in which the test was conducted was Griffiss International Airport, under Syracuse Air Traffic Control (ATC) approach control and Griffiss control tower. Employing an Aurora Centaur optionally piloted aircraft (OPA), this project explored six scenarios aimed at advancing UAS integration into the National Airspace System (NAS) under both nominal and off-nominal conditions. Off-nominal conditions were defined to include complete loss of the communications link between the remote pilot’s control station on the ground and the aircraft. The off-nominal scenarios that were investigated included lost-link conditions with and without link recovery, an automated ATC initiated go-around, autonomous rerouting around a dynamic airspace obstruction (in this case simulated weather), and autonomous taxi operations to clear the runway.

Designing protocols for multi-agent interaction that achieve the desired behavior is a challenging and error-prone process. The standard practice is to manually develop proofs of protocol correctness that rely on human intuition and require significant effort to develop. Even then, proofs can have mistakes that may go unnoticed after peer review, modeling and simulation, and testing. The use of formal methods can reduce the potential for such errors. In this paper, we discuss our experience applying model checking to a previously published multi-agent protocol for unmanned air vehicles. The original publication provides a compelling proof of correctness, along with extensive simulation results to support it. However, analysis through model checking found an error in one of the proof’s main lemmas. In this paper, we start by providing an overview of the protocol and its original “proof” of correctness, which represents the standard practice in multi-agent protocol design. We then describe how we modeled the protocol for a three-vehicle system in a model checker, the counterexample it returned, and the insight this counterexample provided. We also discuss benefits, limitations, and lessons learned from this exercise, as well as what future efforts would be needed to fully verify the protocol for an arbitrary number of vehicles.