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At least 145 records · Page 8

Reversionary Control Modes for the Mitigation of Failures in a Partially Turboelectric Aircraft Propulsion System

In support of emission and fuel burn reduction goals, the aviation industry is actively pursuing the advancement of electrified aircraft propulsion (EAP) technology. This includes turboelectric and hybrid electric propulsion designs that combine gas turbine engine and electrical system hardware. Such architectures exhibit a high degree of coupling between subsystems. This drives the need for system-level control strategies to ensure the safe, coordinated, and efficient operation of all subsystems. The design and certification of any aircraft propulsion system requires that all potential subsystem failures are identified, and the hazards posed by these failures are appropriately mitigated. This requirement is particularly challenging for EAP systems due to their integrated nature. One approach to assist in EAP failure mitigation is the inclusion of automated reconfiguration capabilities within the propulsion control system. Such control modes, referred to as reversionary control modes, are designed to automatically detect failures and activate backup control modes upon failure detection. This paper covers the design and evaluation of reversionary control mode logic developed for a partially turboelectric propulsion concept. Test results from a real-time hardware-in-the-loop evaluation of the concept are also presented and discussed. The results show that the developed reversionary control logic can successfully detect and mitigate subsystem failures in a representative environment that includes actual electrical system hardware.

Electrified Aircraft Propulsion↗

Initial Development of A Digital Twin Model for an Electrified Aircraft Propulsion Emulation Rig

In support of aviation fuel burn and emission reduction goals, NASA is pursing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP), which relies on the generation, storage, transmission, and use of electrical power for producing thrust and optimizing propulsion system efficiency. Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes advances in propulsion controls, which will be vital for ensuring coordinated efficient operation of the complex integrated subsystems that comprise EAP architectures. To support EAP controls research, the NASA Glenn Research Center has developed the Hybrid Propulsion Emulation Rig (HyPER). The HyPER laboratory hardware includes shaft-mounted electric machines, power converters, power supplies, power distribution cables, and an energy storage device that can be reconfigured to represent a variety of EAP architectures. It also includes an integrated real-time computer system that hosts developed EAP control software and turbomachinery simulations. This enables the electrical system and rotating shafts of EAP designs to be implemented in actual hardware and integrated with turbomachinery simulations and system-level EAP control logic implemented in software. In this form, the HyPER laboratory provides a partially simulated, partially hardware-in-the-loop test environment enabling the initial development and evaluation of EAP control technology. A prerequisite for the development of EAP control designs is the availability of a system model that accurately reflects the operation of the electrical system hardware. To support this need, a digital twin model of the HyPER electrical system hardware is under development. This model is being coded in the MATLAB Simulink environment and uses the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) to construct a digital twin framework. EMTAT contains generic electrical component building blocks that are simulated at turbomachinery timescales. Associated inputs and outputs allow the blocks to be combined to model complete electrical systems. The EMTAT blocks also contain adjustable internal maps and parameters that can be set to reflect the operation of a specific electrical component. For the HyPER digital twin, the settings of these EMTAT block internal maps and parameters is determined through machine learning approaches applied to characterization run data collected from the laboratory. During characterization runs the laboratory electrical system hardware is subjected to a full range of torque, speed, and power settings. Acquired data is then used to estimate EMTAT block parameters using a variety of machine learning techniques. The resulting digital twin model is found to match the operation of actual HyPER hardware with an accuracy suitable for control development purposes. It also holds promise for other applications including modeling the performance of HyPER laboratory reconfigurations and model-based anomaly detection. Planned follow-on work to automate post-processing of acquired laboratory data to update the HyPER digital twin model will also be presented and discussed.

Electrified Aircraft Propulsion↗

Modeling and Simulation of Variable Mass, Flexible Structures

The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the distribution of mass in the fuel tank or Solid Rocket Booster (SRB) case for various propellant levels. Based on the mass consumed by the liquid engine or SRB, the appropriate propellant model is coupled with the dry structure model for the stage. Then using vehicle configuration data, the integrated vehicle model is assembled and operated on by the constant system shape functions. The system mode shapes and frequencies can then be computed from the resulting generalized mass and stiffness matrices for that mass configuration. The rigid body mass properties of the vehicle are derived from the integrated vehicle model. The coupling terms between the vehicle rigid body motion and elastic deformation are also updated from the constant system shape functions and the integrated vehicle model. This approach was first used to analyze variable mass spinning beams and then prototyped into a generic dynamics simulation engine. The resulting code was tested against Crew Launch Vehicle (CLV-)class problems worked in the TREETOPS simulation package and by Wilson [2]. The Ares I System Integration Laboratory (SIL) is currently being developed at the Marshall Space Flight Center (MSFC) to test vehicle avionics hardware and software in a hardware-in-the-loop (HWIL) environment and certify that the integrated system is prepared for flight. The Ares I SIL utilizes the Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) tool to simulate the launch vehicle and stimulate avionics hardware. Due to the presence of vehicle control system filters and the thrust oscillation suppression system, which are tuned to the structural characteristics of the vehicle, ARTEMIS must incorporate accurate structural models of the Ares I launch vehicle. The ARTEMIS core dynamics simulation models the highly coupled nature of the vehicle flexible body dynamics, propellant slosh, and vehicle nozzle inertia effects combined with mass and flexible body properties that vary significant with time during the flight. All forces that act on the vehicle during flight must be simulated, including deflected engine thrust force, spatially distributed aerodynamic forces, gravity, and reaction control jet thrust forces. These forces are used to excite an integrated flexible vehicle, slosh, and nozzle dynamics model for the vehicle stack that simulates large rigid body translations and rotations along with small elastic deformations. Highly effective matrix math operations on a distributed, threaded high-performance simulation node allow ARTEMIS to retain up to 30 modes of flex for real-time simulation. Stage elements that separate from the stack during flight are propagated as independent rigid six degrees of freedom (6DOF) bodies. This paper will present the formulation of the resulting equations of motion, solutions to example problems, and describe the resulting dynamics simulation engine within ARTEMIS.

Tobbe, Patrick A.↗

Evolving circuits in seconds: experiments with a stand-alone board-level evolvable system

The purpose of this paper is twofold: first, to illustrate a stand-alone board-level evolvable system (SABLES) and its performance, and second to illustrate some problems that occur during evolution with real hardware in the loop, or when the intention of the user is not completely reflected in the fitness function.

evolvable hardware FPTA DSP evolutionary algorithm↗

Digital tracking loops for a programmable digital modem

In this paper, an analysis and hardware emulation of the tracking loops for a very flexible programmable digital modem (PDM) will be presented. The modem is capable of being programmed for 2, 4, 8, 16-PSK, 16-QAM, MSK, and Offset-QPSK modulation schemes over a range of data rates from 2.34 to 300 Mbps with programmable spectral occupancy from 1.2 to 1.8 times the symbol rate; these operational parameters are executable in burst or continuous mode. All of the critical processing in both the modulator and demodulator is done at baseband with very high-speed digital hardware and memory. Quadrature analog front-ends are used for translation between baseband and the IF center frequency. The modulator is based on a table lookup approach, where precomputed samples are stored in memory and clocked out according to the incoming data pattern. The sample values are predistorted to counteract the effects of the other filtering functions in the link as well as any transmission impairments. The demodulator architecture was adapted from a joint estimator-detector (JED) mathematical analysis. Its structure is applicable to most signalling formats that can be represented in a two-dimensional space. The JED realization uses interdependent, mutually aiding tracking loops with post-detection data feedback. To expedite and provide for more reliable synchronization, initial estimates for these loops are computed in a parallel acquisition processor. The cornerstone of the demodulator realization is the pre-averager received data filter which allows operation over a broad range of data rates without any hardware changes and greatly simplifies the implementation complexity. The emulation results confirmed tracking loop operation over the entire range of operational parameters listed above, as well as the capability of achieving and maintaining synchronization at BER's in excess of 10(exp -1). The emulation results also showed very close agreement with the tracking loop analysis, and validated the resolution apportionment of the various hardware elements in the tracking loops.

Poklemba, John J.↗

Simulation of Guidance, Navigation, and Control Systems for Formation Flying Missions

Concepts for missions of distributed spacecraft flying in formation abound. From high resolution interferometry to spatially distributed in-situ measurements, these mission concepts levy a myriad of guidance, navigation, and control (GNC) requirements on the spacecraft/formation as a single system. A critical step toward assessing and meeting these challenges lies in realistically simulating distributed spacecraft systems. The Formation Flying TestBed (FFTB) at NASA Goddard Space Flight Center's (GSFC) Guidance, Navigation, and Control Center is a hardware-in-the-loop simulation and development facility focused on GNC issues relevant to formation flying systems. The FFTB provides a realistic simulation of the vehicle dynamics and control for formation flying missions in order to: (1) conduct feasibility analyses of mission requirements, (2) conduct and answer mission and spacecraft design trades, and (3) serve as a host for GNC software and hardware development and testing. The initial capabilities of the FFTB are based upon an integration of high fidelity hardware and software simulation, emulation, and test platforms developed or employed at GSFC in recent years, including a high-fidelity Global Positioning System (GPS) simulator which has been a fundamental component of the GNC Center's GPS Test Facility. The FFTB will be continuously evolving over the next several years from a tool with capabilities in GPS navigation hardware/software-in-the-loop analysis and closed loop GPS-based orbit control algorithm assessment. Eventually, it will include full capability to support all aspects of multi-sensor, absolute and relative state determination and control, in all (attitude and orbit) degrees of freedom, as well as information management for satellite clusters and constellations. A detailed description of the FFTB architecture is presented in the paper.

Burns, Rich↗

Metric Tracking Services in the Era of Optical Communications

The Space Communications and Navigation program, at the National Aeronautics and Space Administration, is developing free-space optical communications technology to facilitate the next generation of space missions in near-Earth, Lunar, and planetary space. A discussion of optimetric observation performance and hardware-in-the-loop test results are presented. Simulation of orbit-determination for LEO and Lunar spacecraft relying on optimetric tracking extends raw observation accuracy to realizable orbit-determination performance. Potential science and operational applications are reviewed, along with NASA's approach for developing optimetric technology. Current investments in developing optimetric hardware and plans for NASA's future optical communications network define the path for a future operational optimetric capability in the 2020's and beyond.

optimetrics↗

An Agile-Like Approach to Hardware Development: The Ejectable Data Recorder (EDR) for Orion's Ascent Abort 2 (AA-2) Test Flight

On July 2, 2019, the Ascent Abort 2 (AA-2) Flight Test Vehicle was launched from Cape Canaveral, with the goal of demonstrating the performance of Orion’s Launch Abort System (LAS) and collecting data from hundreds of sensors throughout the vehicle. The data collected during this test flight is of paramount importance, as it will be used to certify the Orion vehicle for human spaceflight. Originally, the data was to be downlinked via a single string network of antennas on the LAS, with the associated risk of potential data dropouts, as well as loss of data once the LAS was jettisoned. Thus, additional antennas were added onto the crew module (CM) to support data downlink post-LAS jettison, a buffer rebroadcast capability was added to fill in any gaps in data downlink transmissions, and an ejectable data recorder (EDR) subsystem was added to the CM as a redundant measure to collect all the instrumentation data. The EDR subsystem was added to the project about one year after the project commenced, which significantly reduced the available development time when compared with the other subsystems of the AA-2 Test Flight. The project was further accelerated by six months, around the critical design review gate. Due to the schedule compression challenge and the fact that the EDR subsystem was a backup system and not flight critical, the EDR subsystem was further challenged to find a new and more efficient way to develop hardware. Thus, the EDR subsystem experimented with different management and systems engineering processes, team sizes, communication methods, and tools. Some examples are novel uses of SharePoint as a Data-centric Project Management & Systems Engineering environment, a continuous testing approach through the lifecycle, and a Skunkworks approach to managing the team. The EDR subsystem blended Commercial Off The Shelf (COTS) hardware with in-house developed hardware and software to create a novel data retrieval capability. The capability evolved rapidly through a hardware in the loop simulation environment that enabled incremental component updates for not only the EDR subsystem but across the entire Crew Module. This paper will present an overview of how the EDR subsystem was managed and compare it to an Agile approach to managing projects. The paper will further provide a recommended approach to future Agile-like hardware development that incorporates lessons learned from the EDR experience.

Agile↗

Flash LIDAR Emulator for HIL Simulation

NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project is building a system for detecting hazards and automatically landing controlled vehicles safely anywhere on the Moon. The Flash Light Detection And Ranging (LIDAR) sensor is used to create on-the-fly a 3D map of the unknown terrain for hazard detection. As part of the ALHAT project, a hardware-in-the-loop (HIL) simulation testbed was developed to test the data processing, guidance, and navigation algorithms in real-time to prove their feasibility for flight. Replacing the Flash LIDAR camera with an emulator in the testbed provided a cheaper, safer, more feasible way to test the algorithms in a controlled environment. This emulator must have the same hardware interfaces as the LIDAR camera, have the same performance characteristics, and produce images similar in quality to the camera. This presentation describes the issues involved and the techniques used to create a real-time flash LIDAR emulator to support HIL simulation.

Brewster, Paul F.↗

X-38 Experimental Controls Laws

X-38 Experimental Control Laws X-38 is a NASA JSC/DFRC experimental flight test program developing a series of prototypes for an International Space Station (ISS) Crew Return Vehicle, often called an ISS "lifeboat." X- 38 Vehicle 132 Free Flight 3, currently scheduled for the end of this month, will be the first flight test of a modem FCS architecture called Multi-Application Control-Honeywell (MACH), originally developed by the Honeywell Technology Center. MACH wraps classical P&I outer attitude loops around a modem dynamic inversion attitude rate loop. The dynamic inversion process requires that the flight computer have an onboard aircraft model of expected vehicle dynamics based upon the aerodynamic database. Dynamic inversion is computationally intensive, so some timing modifications were made to implement MACH on the slower flight computers of the subsonic test vehicles. In addition to linear stability margin analyses and high fidelity 6-DOF simulation, hardware-in-the-loop testing is used to verify the implementation of MACH and its robustness to aerodynamic and environmental uncertainties and disturbances.

Munday, Steve↗

X-57 Flight Systems Integration Path

The foundation for a safe and successful flight test of the National Aeronautics and Space Administration (NASA) X-57 Maxwell all-electric experimental airplane, or any X-Plane, is comprehensive system testing on the ground. This test campaign includes verification and validation (V&V) that the integrated system operates as designed and expected, as well as understanding how the system reacts and responds to failures that can occur during flight by performing failure modes and effects testing (FMET). The aircraft should be in the final flight configuration for these test activities because any modifications, even those that appear insignificant, could affect test outcomes. Although the plan was to perform V&V and FMET testing once the airplane was in the flight configuration, due to multiple component redesigns, concurrent software development, and other problems with on-aircraft testing, the X-57 Maxwell never made it into a full-flight configuration. As a result, a build-up approach was followed to test software and hardware as they became ready in order to continue making progress wherever possible. Using this approach revealed problems with the hardware and software faster than waiting for a full-flight configuration, allowing solutions to be found more quickly and in parallel with other project tasks. Other than unloaded motor testing in a lab setting, the only other test setup was on the airplane itself. On-aircraft testing was preferrable in order to test things as close to a flight configuration as possible but was time consuming due to the requirements for testing on the airplane. To overcome some of the on-aircraft barriers, off-aircraft test configurations, such as the Systems Integration Laboratory (SIL) and hardware-in-the-loop (HIL) setups, were used, but each of these setups had limitations to be considered. As a result, solutions found in the SIL or HIL configurations did not always work as expected on the airplane, resulting in an iterative process between on- and off-aircraft testing to find the final solution. Having a dedicated test platform such as an iron bird that closely represents the aircraft - without flight hardware - would have been the most effective off-aircraft test setup, which could have allowed the project to save time and money and potentially reach flight. This paper will highlight the V&V and FMET considerations and testing prerequisites, the build-up approaches to both software and system testing, the benefits and drawbacks to different test configurations, as well as battery testing and operations.

Kassidy M. Mclaughlin↗

X-57 Flight Systems Integration Path

The foundation for a safe and successful flight test of the National Aeronautics and Space Administration (NASA) X-57 Maxwell all-electric experimental airplane, or any X-Plane, is comprehensive system testing on the ground. This test campaign includes verification and validation (V&V) that the integrated system operates as designed and expected, as well as understanding how the system reacts and responds to failures that can occur during flight by performing failure modes and effects testing (FMET). The aircraft should be in the final flight configuration for these test activities because any modifications, even those that appear insignificant, could affect test outcomes. Although the plan was to perform V&V and FMET testing once the airplane was in the flight configuration, due to multiple component redesigns, concurrent software development, and other problems with on-aircraft testing, the X-57 Maxwell never made it into a full-flight configuration. As a result, a build-up approach was followed to test software and hardware as they became ready in order to continue making progress wherever possible. Using this approach revealed problems with the hardware and software faster than waiting for a full-flight configuration, allowing solutions to be found more quickly and in parallel with other project tasks. Other than unloaded motor testing in a lab setting, the only other test setup was on the airplane itself. On-aircraft testing was preferrable in order to test things as close to a flight configuration as possible but was time consuming due to the requirements for testing on the airplane. To overcome some of the on-aircraft barriers, off-aircraft test configurations, such as the Systems Integration Laboratory (SIL) and hardware-in-the-loop (HIL) setups, were used, but each of these setups had limitations to be considered. As a result, solutions found in the SIL or HIL configurations did not always work as expected on the airplane, resulting in an iterative process between on- and off-aircraft testing to find the final solution. Having a dedicated test platform such as an iron bird that closely represents the aircraft - without flight hardware - would have been the most effective off-aircraft test setup, which could have allowed the project to save time and money and potentially reach flight. This paper will highlight the V&V and FMET considerations and testing prerequisites, the build-up approaches to both software and system testing, the benefits and drawbacks to different test configurations, as well as battery testing and operations.

Kassidy McLaughlin↗

Distributed Spacecraft Autonomy - Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC) measurements. DSA will be demonstrated onboard the NASA Ames Starling mission – a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets. The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasmasphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input dataset for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software, aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements, which define the range of observability for the satellites, as well as exploitative measurements, which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth’s magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions. As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown. Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middleware provides reliable delivery, routing, and topic subscription features over User Datagram Protocol (UDP). Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarm scalability from 2 satellites to 100 satellites is shown.

Distributed Autonomy↗

Pterodactyl: Control System Demonstrator Development for Integrated Control Design of a Mechanically Deployed Entry Vehicle

The NASA-funded Pterodactyl project is a design, test, and build capability to (i) advance the current state of the art for Deployable Entry Vehicle (DEV) guidance and control (G&C), and (ii) determine the feasibility of control system integration for various entry vehicle types including those without aeroshells. This capability is currently being used to develop control systems for one such unconventional entry vehicle, the Lifting Nano-ADEPT (LNA) vehicle. ADEPT offers the possibility of integrating control systems directly onto the mechanically deployed structure and building hardware demonstrators will help assess integration and design challenges. Control systems based on aerodynamic control surfaces, mass movement, and reaction control systems (RCS) are currently being investigated for a down-select to the most suitable control architecture for the LNA.To that effect, in this submission, we detail the efforts of the Pterodactyl project to develop a series of hardware demonstrators for the different LNA control systems. Rapid prototypes, for a set of quarter- model or eighth-model vehicle segments, will be developed for all three architectures to validate mechanical design assumptions, and hardware-in-the-loop (HIWL) control approaches. A ground test control system demonstrator will be designed and built after the trade study is complete. The industrial-grade demonstrator will be designed so that it can be incorporated into a HWIL simulation to further validate the findings of the initial trade study. The HWIL simulation will leverage the iPAS environment developed at NASA's Johnson Space Center which facilitates integration testing to support technology maturation and risk reduction, necessary elements for the hardware demonstration development detailed in this paper.

Margolis, Benjamin W.↗

Distributed Spacecraft Autonomy (DSA): Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC)measurements. DSA will be demonstrated on board the NASA Ames Starling mission a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets.The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasma sphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input data set for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software,aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements,which define the range of observability for the satellites, as well as exploitative measurements,which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions.As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown.Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middle ware provides reliable delivery, routing, and topic subscription features over User Data gram Protocol (UDP).Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarms calability from 2 satellites to 100 satellites is shown.

Fugate, Jason↗

Ground-Based Capabilities for Lunar Infrastructure Testing

A focus of NASA’s Moon-to-Mars objectives is the development of the infrastructure on the lunar surface that will be needed to support broader lunar surface operations. This infrastructure is intended to support both United States and international partners to expand human presence on the lunar surface. As this lunar infrastructure is designed and established, it will be critical to ensure that the various hardware elements work together to both enable the capabilities and to avoid unintended actions. NASA’s Glenn Research Center (GRC) is establishing ground-based testing and emulation facilities to mimic the lunar environment that the surface power and communications infrastructure will operate in. These facilities are intended to represent power and communications providers, users, and interfaces to ensure that systems operate as intended to support the lunar economy. They will empower industry to rapidly evaluate new technologies under realistic conditions. In 2023 GRC is opening a new, state-of-the-art, Aerospace Communications Facility featuring hardware-in-the-loop and ground-to-orbit testbeds. The Multiple Asset Testbed for Research in Innovative Communications Systems (MATRICS) capability will emulate the lunar communications environment, enabling validation of mission concepts and technologies to reduce risk through performance and operations testing, training, and uncover potential issues in compatibility among communication systems providers and users. In addition to the communications testbed, GRC is also developing a full-scale power grid to reduce lunar mission risk. The Adaptable Surface Power Integration and Research (ASPIRE) project aims to reduce mission and hardware risk via high-fidelity integrated testing and pave the way for commercially supplied utility power on the lunar surface. The facility will be scalable and highly adaptable and will be available to NASA, Industry, Academia, and International Partners. ASPIRE will allow developers to integrate and demonstrate their power solutions in a relevant environment, and it will be able to characterize the lunar power performance in representative mission contexts.

ground-based testing↗

Electrified Aircraft Propulsion Controls Hardware Testing

Electrified Aircraft Propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn and emissions. To realize this potential for single-aisle aircraft, control technology challenges associated with EAP designs are increasing the demand for Hardware-In-the-Loop (HIL) studies that address the tightly coupled electrical powertrain and turbofan propulsion systems. Reconfigurable HIL testbeds enable the study of integrated supervisory control and control approaches that augment engine shaft torques to improve performance. This paper presents an overview of conceptual EAP controls architecture testing in two HIL testbeds. The NASA Electric Aircraft Testbed provides the ability for megawatt class electric powertrain testing for technology maturation. A 100 kilowatt testbed, the Hybrid Propulsion Emulation Rig, allows for rapid controls technology trade studies. In both testbeds, controls testing is performed by implementing the electrical power system in hardware while turbomachinery is emulated via electric machines that are commanded by a real-time model and controls. A novel scaling algorithm is applied to emulate the inertial loads of the turbomachinery that causes the electric machines to respond in a fashion similar to that of the full-scale propulsion system they represent. Results demonstrate desired control performance at both testbed scales for the conceptual EAP architecture.

Electrified Aircraft Propulsion↗

Electrified Aircraft Propulsion Controls Hardware Testing

Electrified Aircraft Propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn and emissions. To realize this potential for single-aisle aircraft, control technology challenges associated with EAP designs are increasing the demand for Hardware-In-the-Loop (HIL) studies that address the tightly coupled electrical powertrain and turbofan propulsion systems. Reconfigurable HIL testbeds enable the study of integrated supervisory control and control approaches that augment engine shaft torques to improve performance. This paper presents an overview of conceptual EAP controls architecture testing in two HIL testbeds. The NASA Electric Aircraft Testbed provides the ability for megawatt class electric powertrain testing for technology maturation. A 100 kilowatt testbed, the Hybrid Propulsion Emulation Rig, allows for rapid controls technology trade studies. In both testbeds, controls testing is performed by implementing the electrical power system in hardware while turbomachinery is emulated via electric machines that are commanded by a real-time model and controls. A novel scaling algorithm is applied to emulate the inertial loads of the turbomachinery that causes the electric machines to respond in a fashion similar to that of the full-scale propulsion system they represent. Results demonstrate desired control performance at both testbed scales for the conceptual EAP architecture.

Electrified Aircraft Propulsion↗