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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗
NASA NTRS2013

Orbiting Rainbows: Optical Manipulation of Aerosols and the Beginnings of Future Space Construction

Our objective is to investigate the conditions to manipulate and maintain the shape of an orbiting cloud of dust-like matter so that it can function as an ultra-lightweight surface with useful and adaptable electromagnetic characteristics, for instance, in the optical, RF, or microwave bands. Inspired by the light scattering and focusing properties of distributed optical assemblies in Nature, such as rainbows and aerosols, and by recent laboratory successes in optical trapping and manipulation, we propose a unique combination of space optics and autonomous robotic system technology, to enable a new vision of space system architecture with applications to ultra-lightweight space optics and, ultimately, in-situ space system fabrication. Typically, the cost of an optical system is driven by the size and mass of the primary aperture. The ideal system is a cloud of spatially disordered dust-like objects that can be optically manipulated: it is highly reconfigurable, fault-tolerant, and allows very large aperture sizes at low cost. See Figure 1 for a scenario of application of this concept. The solution that we propose is to construct an optical system in space in which the nonlinear optical properties of a cloud of micron-sized particles are shaped into a specific surface by light pressure, allowing it to form a very large and lightweight aperture of an optical system, hence reducing overall mass and cost. Other potential advantages offered by the cloud properties as optical system involve possible combination of properties (combined transmit/receive), variable focal length, combined refractive and reflective lens designs, and hyper-spectral imaging. A cloud of highly reflective particles of micron-size acting coherently in a specific electromagnetic band, just like an aerosol in suspension in the atmosphere, would reflect the Sun's light much like a rainbow. The only difference with an atmospheric or industrial aerosol is the absence of the supporting fluid medium. This new concept is based on recent understandings in the physics of optical manipulation of small particles in the laboratory and the engineering of distributed ensembles of spacecraft clouds to shape an orbiting cloud of micron-sized objects. In the same way that optical tweezers have revolutionized micro- and nano-manipulation of objects, our breakthrough concept will enable new large scale NASA mission applications and develop new technology in the areas of Astrophysical Imaging Systems and Remote Sensing because the cloud can operate as an adaptive optical imaging sensor. While achieving the feasibility of constructing one single aperture out of the cloud is the main topic of this work, it is clear that multiple orbiting aerosol lenses could also combine their power to synthesize a much larger aperture in space to enable challenging goals such as exoplanet detection. Furthermore, this effort could establish feasibility of key issues related to material properties, remote manipulation, and autonomy characteristics of cloud in orbit. There are several types of endeavors (science missions) that could be enabled by this type of approach, i.e. it can enable new astrophysical imaging systems, exoplanet search, large apertures allow for unprecedented high resolution to discern continents and important features of other planets, hyperspectral imaging, adaptive systems, spectroscopy imaging through limb, and stable optical systems from Lagrange-points. Future micro-miniaturization might hold promise of a further extension of our dust aperture concept to other more exciting smart dust concepts with other associated capabilities.

Space Construction↗
NASA NTRS2015

Core Analysis Combining MT (TIPPER) and Dielectric Sensors (Sans EC) in Earth and Space

On terrestrial planets and moons of our solar system cores reveal details about a geological structure's formation, content, and history. The strategy for the search for life is focused first on finding water which serves as a universal solvent, and identifying the rocks which such solvent act upon to release the constituent salts, minerals, ferrites, and organic compounds and chemicals necessary for life. Dielectric spectroscopy measures the dielectric properties of a medium as a function of frequency. Reflection measurements in the frequency range from 300 kHz to 300 MHz were carried out using RF and microwave network analyzers interrogating SansEC Sensors placed on clean geological core samples. These were conducted to prove the concept feasibility of a new geology instrument useful in the field and laboratory. The results show that unique complex frequency spectra can be acquired for a variety of rock core samples. Using a combination of dielectric spectroscopy and computer simulation techniques the magnitude and phase information of the frequency spectra can be converted to dielectric spectra. These low-frequency dielectric properties of natural rock are unique, easily determined, and useful in characterizing geology. TIPPER is an Electro-Magnetic Passive-Source Geophysical Method for Detecting and Mapping Geothermal Reservoirs and Mineral Resources. This geophysical method uses distant lightning and solar wind activity as its energy source. The most interesting deflections are caused by the funneling of electrons into more electrically conductive areas like mineralized faults, water or geothermal reservoirs. We propose TIPPER to be used with SansEC for determining terrain/ocean chemistry, ocean depth, geomorphology of fracture structures, and other subsurface topography characteristics below the ice crust of Jovian moons. NASA envisions lander concepts for exploration of these extraterrestrial icy surfaces and the oceans beneath. One such concept would use a nuclear powered heated tip for melting through the ice sheath of Europa and inserting a down hole SansEC with TIPPER interface. NASA's Juno space probe already on the way to Jupiter as part of the Exploration New Frontiers Program and the planned Europa mission will conduct detailed reconnaissance of Jupiter's moon Europa and investigate whether the icy moon could harbor conditions suitable for life. It has already been observed that Jovian moons have auroras that may serve as naturally occurring active energy sources for a TIPPER instrument.

Mound, Michael C.↗
NASA NTRS2013

Development of the Orion Crew-Service Module Umbilical Retention and Release Mechanism

The Orion CSM umbilical retention and release mechanism supports and protects all of the cross-module commodities between the spacecrafts crew and service modules. These commodities include explosive transfer lines, wiring for power and data, and flexible hoses for ground purge and life support systems. The mechanism employs a single separation interface which is retained with pyrotechnically actuated separation bolts and supports roughly two dozen electrical and fluid connectors. When module separation is commanded, either for nominal on-orbit CONOPS or in the event of an abort, the mechanism must release the separation interface and sever all commodity connections within milliseconds of command receipt. There are a number of unique and novel aspects of the design solution developed by the Orion mechanisms team. The design is highly modular and can easily be adapted to other vehiclesmodules and alternate commodity sets. It will be flight tested during Orions Exploration Flight Test 1 (EFT-1) in 2014, and the Orion team anticipates reuse of the design for all future missions. The design packages fluid, electrical, and ordnance disconnects in a single separation interface. It supports abort separations even in cases where aerodynamic loading prevents the deployment of the umbilical arm. Unlike the Apollo CSM umbilical which was a destructive separation device, the Orion design is resettable and flight units can be tested for separation performance prior to flight.Initial development testing of the mechanisms separation interface resulted in binding failures due to connector misalignments. The separation interface was redesigned with a robust linear guide system, and the connector separation and boom deployment were separated into two discretely sequenced events. These changes addressed the root cause of the binding failure by providing better control of connector alignment. The new design was tuned and validated analytically via Monte Carlo simulation. The analytical validation was followed by a repeat of the initial test suite plus test cases at thermal extremes and test cases with imposed mechanical failures demonstrating fault tolerance. The mechanism was then exposed to the qualification vibration environment. Finally, separation testing was performed at full speed with live ordnance.All tests of the redesigned mechanism resulted in successful separation of the umbilical interface with adequate force margins and timing. The test data showed good agreement with the predictions of the Monte Carlo simulation. The simulation proved invaluable due to the number of variables affecting the separation and the uncertainty associated with each. The simulation allowed for rapid assessment of numerous trades and contingency scenarios, and can be easily reconfigured for varying commodity sets and connector layouts.

Separation↗
NASA NTRS2018

GPM Mission's Best Practices: PERP

Similar to other missions, the Global Precipitation Measurement (GPM) Core Observatory's Command and Data Handling (C&DH) subsystem is critical for operations of the spacecraft. The onboard C&DH system comprises of two fully redundant boxes - a primary and a cold backup. Within each box, amongst other components, is a Single Board Computer (SBC) that hosts the flight software (FSW) system. In the event of an SBC reset, the Flight Operations Team (FOT) is poised with a lengthy task of restoring the SBC to nominal configuration. Due to the complexity of the C&DH system, this may take many days at a time to complete. The spacecraft's FSW applications are located in Electronically Erasable Programmable Read-Only Memory (EEPROM) and are copied into Random Access Memory (RAM) upon SBC initialization/reset. Each SBC has two banks of EEPROM, with each bank containing a copy of the FSW. Since launch, there have been many configuration changes to tables and applications that have been loaded into just RAM. Unfortunately, these changes are vulnerable to being wiped during a SBC initialization/reset, when the RAM is overwritten by the EEPROM. Although the EEPROM loads the default FSW configurations, the process to command non-default individual table and application changes is very cumbersome and time consuming. This consequentially increases the time until the spacecraft is back into nominal Mission Science Mode (MSM) drastically. The GPM Power-On Reset (POR) Expedited Recovery Process (PERP) Design introduces a method of consolidating commands into a single file load which the SBC can process independently of the ground - decreasing recovery time, the level of TDRS support reliance, and human error. This tested design can be implemented across many other missions that utilize a similar core Flight Executive (cFE) platform; hence providing an easy-to-follow, safe, and efficient process that can be applied across the board.

recovery↗
NASA NTRSDate not supplied

Failure Modes and Mitigation Strategies for a Turboelectric Aircraft Concept with Turbine Electrified Energy Management

The electrification of gas turbine engines represents a major step-change in aircraft propulsion systems commonly known as Electrified Aircraft Propulsion (EAP). EAP involves the integration of electric machines potentially functioning as generators for large scale power extraction, as motors providing electrical augmentation of the engine spools, and even as a means of driving propulsors beyond the immediate scope of the engine. It may also include the use of energy storage. These and other characteristics of hybrid electric propulsion systems are relatively new to aircraft propulsion. The expanded propulsion architecture can be leveraged to improve propulsive efficiency and achieve better vehicle aerodynamics and controllability. It can also allow for additional benefits such as those enabled through Turbine Electrified Energy Management (TEEM). As the propulsion system and its functions expand, new failure modes are introduced. Due to the highly coupled nature of the propulsion system, failures could propagate throughout the system in ways that are unique to the new EAP architectures. To build confidence in the safety and practicality of EAP concepts, these failure modes need to be identified, explored, and addressed through mitigation strategies. This paper seeks to evaluate failure modes and failure mitigation strategies for the EAP concept known as the Single aisle Turboelectric AiRCaft with Aft Boundary Layer propulsor (STARC-ABL). The TEEM control concept is applied to improve transient operability. Several failure modes are considered and control based failure mitigation strategies are proposed with the goal of retaining operability and overall thrust. The results demonstrate the ability to maintain operability and a substantial amount of thrust in the event of various types of failures. Some challenges are also identified and discussed.

Turbine Electrified Energy Management↗
NASA NTRS2001

Enabling Advanced Automation in Spacecraft Operations with the Spacecraft Emergency Response System

True autonomy is the Holy Grail of spacecraft mission operations. The goal of launching a satellite and letting it manage itself throughout its useful life is a worthy one. With true autonomy, the cost of mission operations would be reduced to a negligible amount. Under full autonomy, any problems (no matter the severity or type) that may arise with the spacecraft would be handled without any human intervention via some combination of smart sensors, on-board intelligence, and/or smart automated ground system. Until the day that complete autonomy is practical and affordable to deploy, incremental steps of deploying ever-increasing levels of automation (computerization of once manual tasks) on the ground and on the spacecraft are gradually decreasing the cost of mission operations. For example, NASA's Goddard Space Flight Center (NASA-GSFC) has been flying spacecraft with low cost operations for several years. NASA-GSFC's SMEX (Small Explorer) and MIDEX (Middle Explorer) missions have effectively deployed significant amounts of automation to enable the missions to fly predominately in 'light-out' mode. Under light-out operations the ground system is run without human intervention. Various tools perform many of the tasks previously performed by the human operators. One of the major issues in reducing human staff in favor of automation is the perceived increased in risk of losing data, or even losing a spacecraft, because of anomalous conditions that may occur when there is no one in the control center. When things go wrong, missions deploying advanced automation need to be sure that anomalous conditions are detected and that key personal are notified in a timely manner so that on-call team members can react to those conditions. To ensure the health and safety of its lights-out missions, NASA-GSFC's Advanced Automation and Autonomy branch (Code 588) developed the Spacecraft Emergency Response System (SERS). The SERS is a Web-based collaborative environment that enables secure distributed fault and resource management. The SERS incorporates the use of intelligent agents, threaded discussions, workflow, database connectivity, and links to a variety of communications devices (e.g., two-way paging, PDA's, and Internet phones) via commercial gateways. When the SERS detects a problem, it notifies on-call team members, who then can remotely take any necessary actions to resolve the anomalies.The SERS goes well beyond a simple '911' system that sends out an error code to everyone with a pager. Instead, SERS' software agents send detailed data (i.e., notifications) to the most appropriate team members based on the type and severity of the anomaly and the skills of the on-call team members. The SERS also allows the team members to respond to the notifications from their wireless devices. This unique capability ensures rapid response since the team members no longer have to go to a PC or the control center for every anomalous event. Most importantly, the SERS enables safe experimentation with various techniques for increasing levels of automation, leading to robust autonomy. For the MIDEX missions at NASA GSFC, the SERS is used to provide 'human-in-the-loop' automation. During lights-out operations, as greater control is given to the MIDEX automated systems, the SERS can be configured to page remote personnel and keep them informed regarding actions taking place in the control center. Remote off-duty operators can even be given the option of enabling or inhibiting a specific automated response in near real time via their two-way pagers. The SERS facilitates insertion of new technology to increase automation, while maintaining the safety and security of mission resources. This paper will focus on SERS' overall functionality and how SERS has been designed to handle the monitoring and emergency response for missions with varying levels of automation. The paper will also convey some of the key lessons learned from SERS' deployment across of variety of missions, highlighting this incremental approach to achieving 'robust autonomy'.

Breed, Julie↗
NASA NTRS2001

Automating Trend Analysis for Spacecraft Constellations

Spacecraft trend analysis is a vital mission operations function performed by satellite controllers and engineers, who perform detailed analyses of engineering telemetry data to diagnose subsystem faults and to detect trends that may potentially lead to degraded subsystem performance or failure in the future. It is this latter function that is of greatest importance, for careful trending can often predict or detect events that may lead to a spacecraft's entry into safe-hold. Early prediction and detection of such events could result in the avoidance of, or rapid return to service from, spacecraft safing, which not only results in reduced recovery costs but also in a higher overall level of service for the satellite system. Contemporary spacecraft trending activities are manually intensive and are primarily performed diagnostically after a fault occurs, rather than proactively to predict its occurrence. They also tend to rely on information systems and software that are oudated when compared to current technologies. When coupled with the fact that flight operations teams often have limited resources, proactive trending opportunities are limited, and detailed trend analysis is often reserved for critical responses to safe holds or other on-orbit events such as maneuvers. While the contemporary trend analysis approach has sufficed for current single-spacecraft operations, it will be unfeasible for NASA's planned and proposed space science constellations. Missions such as the Dynamics, Reconnection and Configuration Observatory (DRACO), for example, are planning to launch as many as 100 'nanospacecraft' to form a homogenous constellation. A simple extrapolation of resources and manpower based on single-spacecraft operations suggests that trending for such a large spacecraft fleet will be unmanageable, unwieldy, and cost-prohibitive. It is therefore imperative that an approach to automating the spacecraft trend analysis function be studied, developed, and applied to missions such as DRACO with the intent that mission operations costs be significantly reduced. The goal of the Constellation Spacecraft Trend Analysis Toolkit (CSTAT) project is to serve as the pathfinder for a fully automated trending system to support spacecraft constellations. The development approach to be taken is evolutionary. In the first year of the project, the intent is to significantly advance the state of the art in current trending systems through improved functionality and increased automation. In the second year, the intent is to add an expert system shell, likely through the adaptation of an existing commercial-off-the-shelf (COTS) or government-off-the-shelf (GOTS) tool to implement some level of the trending intelligence that humans currently provide in manual operations. In the third year, the intent is to infuse the resulting technology into a near-term constellation or formation-flying mission to test it and gain experience in automated trending. The lessons learned from the real missions operations experience will then be used to improve the system, and to ultimately incorporate it into a fully autonomous, closed-loop mission operations system that is truly capable of supporting large constellations. In this paper, the process of automating trend analysis for spacecraft constellations will be addressed. First, the results of a survey on automation in spacecraft mission operations in general, and in trending systems in particular will be presented to provide an overview of the current state of the art. Next, a rule-based model for implementing intelligent spacecraft subsystem trending will be then presented, followed by a survey of existing COTS/GOTS tools that could be adapted for implementing such a model. The baseline design and architecture of the CSTAT system will be presented. Finally, some results obtained from initial software tests and demonstrations will be presented.

Davis, George↗