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NASA NTRSDate not supplied

Rapid Spacecraft Payload Development: In-Orbit Demonstration of Flight Software Reuse, Scalability, and Dependability

As space mission design trends towards shared, multi-mission platforms and high-performance onboard computing architectures, the number of spacecraft launched into operation is also steadily rising. Through ridesharing, spacecraft miniaturization, and other cost-reduction measures, the barriers to space are lowering, resulting in compounded growth in the amount of flight software being deployed. To meet the needs of both the growing quantity and evolving nature of spacecraft, flight software design must accordingly adapt to support more efficient development, solutions to computational resource-sharing, and software reusability. This paper focuses on a software payload demonstrating several core technologies that improve the state-of-the-art in these identified areas. Launched into low-earth orbit in January 2022, our software payload was conceived, designed, and delivered in a span of merely two months. It was developed on top of the NASA core Flight System (cFS) framework and the Distributed Spacecraft Autonomy (DSA) Comm cFS application, which translates cFS software bus messages across a Data Distribution Service (DDS) network. The flight software, packaged in Linux container images, was deployed as one of 18 flight applications managed through the Unibap SpaceCloud Framework. The applications were run on a Unibap iX5-102 radiation-tolerant payload computer, hosted on the D-Orbit SCV-004 spacecraft as part of an ESA-sponsored in-orbit technology test. Our payload, referred to as the DSA D-Orbit software, demonstrates the reusability of the DSA Comm app in a substantially different context and purpose as its original mission. Comm’s original design goal was to reliably distribute messages between spacecraft swarms of arbitrary size and dynamic network topology. However, we leverage this same functionality to introduce redundancy and opportunistic parallel data processing in the context of a representative onboard image processing workload. This adaptive mission architecture was enabled in part by the SpaceCloud Framework’s use of container virtualization as the payload integration interface. By using a base container image with common high-level language runtimes and libraries, we were able to rapidly design, develop, and validate our image processing application without many of the technological barriers common to flight software development. We present details the goals, approach, results, and lessons learned through this technology demonstration experiment and contextualize those observations against present and future challenges in spacecraft software development.

computer programming↗

NASA NTRSDate not supplied

Safety Demonstrator Series for an In-Time Aviation Safety Management System

NASA's Advanced Air Mobility Integration Office has coordinated a meeting with the National Research Council Canada (NRC) to have an interchange of technical area activities to evaluate merit for international partnership. Both NASA and NRC will provide a brief overview of their Advanced Air Mobility activities. Additional aeronautics projects will have an opportunity to present a few slides on current activities and plans. Topics include wildfire, vehicle automation technologies and detect and avoid, and national campaign flight initiatives. NASA's System-Wide Safety (SWS) Project will provide a high-level overview of the the safety demonstrator series. The project has scheduled operational demonstrations of an in-time aviation safety management system across a series of disaster-oriented operations. First up is a wildland fire demonstration scheduled for 2025. Opportunities for synergy will be discussed.

system-wide safety↗

NASA NTRSDate not supplied

PAAV Tabletop 4 Results – Integrating m:N Remotely Piloted Operations

NASA's Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project is investigating procedures and technologies to facilitate seamless integration of future UAS operations into the NAS. The Tabletop 4 activity solicited subject matter expertise to identify solutions to the potential challenges expected when the remote pilot-to-vehicle ratio scales from 1:1 to m:N, where one or more ground-based pilots control multiple uncrewed aircraft. This presentation details the method and high-level results of the PAAV Tabletop 4 activity.

m:N↗

NASA NTRSDate not supplied

Orion Backup Flight Software (BFS)

Orion Backup Flight Software (BFS) is a joint NASA/Lockheed Martin effort designed to prevent the loss of the Orion crew. BFS will only take over in the event the primary flight software (PFSW) fails to operate properly due to either hardware or software failures. Since the PFSW runs identical software on identical hardware, it is conceivable that a single issue could simultaneously bring down all the PFSW. To minimize the likelihood BFS would be affected by the same issue, BFS was specifically designed to be as different as possible from PFSW: BFS runs on different hardware, a separate operating system, a different compiler, does not share software libraries, and is written by a different team of programmers. This presentation will provide a high-level overview of the Artemis missions and the Orion vehicle, as well as provide additional details of the BFS system (including how BFS is different than the PFSW). The overall BFS capability evolution and timeline (milestones reached as well as work remaining) through the Artemis III mission will be discussed. Additionally, the verification and validation plans for BFS will be presented, describing how we ensure that only validated configuration data is loaded onto the flight vehicle. Finally, the presentation will close with lessons learned and future plans for Orion BFS.

CFS↗

NASA NTRS2022

CLASSY. II. A Technical Overview of the COS Legacy Archive Spectroscopic Survey

The COS Legacy Archive Spectroscopic SurveY (CLASSY) is designed to provide the community with a spectral atlas of 45 nearby star-forming galaxies that were chosen to cover similar properties to those seen at high z (z > 6). The prime high-level science product of CLASSY is accurately coadded UV spectra, ranging from ∼1000 to 2000 Å, derived from a combination of archival and new data obtained with HST's Cosmic Origins Spectrograph (COS). This paper details the multistage technical processes of creating this prime data product and the methodologies involved in extracting, reducing, aligning, and coadding far-ultraviolet and near-ultraviolet (NUV) spectra. We provide guidelines on how to successfully utilize COS observations of extended sources, despite COS being optimized for point sources, and best-practice recommendations for the coaddition of UV spectra in general. Moreover, we discuss the effects of our reduction and coaddition techniques in the scientific application of the CLASSY data. In particular, we find that accurately accounting for flux calibration offsets can affect the derived properties of the stellar populations, while customized extractions of NUV spectra for extended sources are essential for correctly diagnosing the metallicity of galaxies via C iii] nebular emission. Despite changes in spectral resolution of up to ∼25% between individual data sets (due to changes in the COS line-spread function), no adverse affects were observed on the difference in velocity width and outflow velocities of isolated absorption lines when measured in the final combined data products, owing in part to our signal-to-noise regime of S/N < 20.

Bethan L. James↗

NASA NTRS2023

Exploration Electronic Health Record (xEHR) Techport Entry

Exploration missions beyond low Earth orbit will experience significant communication delays and communication black outs that will necessitate asynchronous, increasingly Earth-independent provision of medical care to onboard crew. In this new paradigm, the Crew Medical Officer (CMO), other Crewmembers, and ground support will have to quickly, efficiently, and independently, view medical data, make decisions, and relay important information. Currently, the NASA electronic health record (EHR) is intended only for ground use and is not accessible to in-mission ISS crew for medical decision support and communication. An EHR capable of providing the crew health data, medical store-and-forward communications, and necessary medical administrative tools is critical in enabling NASA’s standard of healthcare during increasingly autonomous operations. The Exploration Medical Integrated Product Team (XMIPT) project called Medical Exploration Development and Implementation Scoping (MEDIScope) developed and reviewed objectives and concept of operations for an exploration EHR (xEHR) with project stakeholders, developed preliminary high-level requirements, and coordinated the handoff of the project to a design and implementation team at the Johnson Space Center (JSC). This JSC team will develop system requirements for the xEHR with inputs from subject matter experts. Following final requirements development, a team will be chosen to develop the xEHR and to conduct a demonstration on a future exploration vehicle such as Gateway.

MEDIScope↗

NASA NTRS2023

Autonomy Verification & Validation Roadmap and Vision 2045

Advanced capabilities planned for the next generation of autonomous and increasingly autonomous air vehicles will include non-traditional components based on artificial intelligence, machine learning, and complex optimization and planning algorithms. These complex components will be used to provide enhanced safety and high-level decision-making functions. However, there are serious barriers to the deployment of autonomous aircraft in the National Airspace System (NAS). Current civil aviation certification processes are based on the concept that the correct behavior of a system or a component must be completely specified and verified prior to operation. This report from the Autonomy Verification and Validation (V&V) Roadmap and Vision 2045 project presents the most recent effort to build a comprehensive list of verification challenges and needs for autonomous aircraft, a roadmap to meet those autonomy V&V needs, the services they can enable, and point to the certification gaps they fill. To accomplish these goals, we assembled a team of world-class researchers from the aerospace industry (Boeing, Collins Aerospace, and GeneralElectric) and academia (University of Michigan, University of Texas, and Massachusetts Institute of Technology) with deep expertise in autonomy, aerospace systems, and assurance of Artificial Intelligence/machine learning systems.

Software Assurance↗

NASA NTRS2023

BERT-Based Topic Modeling and Information Retrieval to Support Fishbone Diagramming for Safe Integration of Unmanned Aircraft Systems in Wildfire Response

Recent concepts for emerging wildfire response operations have included unmanned aircraft systems (UAS) due to their increasing accessibility and capabilities. To integrate UAS into wildfire response safely, researchers have studied the use of large repositories of historic incident reports to improve the scope of root cause analysis. Recent work has emphasized applying state-of-the-art natural language processing techniques to extract useful information from these repositories. However, it has not yet been studied how these results can be interpreted and integrated into the systems engineering process. In this work, we propose a process in which Bidirectional Encoder Representations from Transformers (BERT)-based topic modeling and information retrieval are applied to a relevant set of documents in order to support the development of a fishbone diagram in a semiautomated process. High-level themes in the document set are identified using topic modeling, which are then refined and interpreted by a human analyst. Then, the themes are used to guide a finer search using information retrieval, which returns specific incident reports of relevance. This provides traceability to specific incidents as well as broader categorizations that comprise the fishbone branches. We apply the proposed process to relevant documents from NASA’s Aviation Safety Reporting System (ASRS). The proposed process is widely applicable when relevant documents are available, and the results from this study will be useful to identifying potential causes of wildfire response UAS incidents.

Hazard analysis↗

NASA NTRSDate not supplied

Cost Benefit Analysis of Space Debris Remediation

These slides provide a high-level summary of a cost-benefit analysis of approaches for debris remediation, which is defined as any action taken to reduce the risks posed by orbital debris by moving, removing, or reusing it. A better understanding of the near-term costs and benefits of the different approaches to remediation can support decision-making about R&D investment and policy creation in this area.

Tom Colvin↗

NASA NTRS2021

An Efficient Approach for Scheduling Imaging Tasks Across a Fleet of Satellites

Dynamically retasking satellites in response to scientific alerts is challenging because the tasks and opportunities of one satellite can influence this of another. This abstract focuses on our high-level approach for scheduling imaging tasks across a constellation of satellite, which is subject to orbital and other practical constraints such as finding a feasible up-/down- link schedule. Our approach is inspired by combining insights from two existing approaches about the structure of these problems to create an efficient, new approach. We show that our approach stacks up favorably against two baselines–an optimal solver as well as a naive, greedy approach.

Maillard, Adrien↗

NASA NTRS2020

Integrated Modeling and Development of Component-Based Embedded Software in Scala

Programming of embedded systems is challenging due to the low-level design patterns normally applied in the implementation of such systems. Furthermore, programming languages normally considered suitable for this level of programming, such as C and C++, are themselves low-level compared to more modern programming languages. We report on an effort exploring modeling and programming of embedded systems in modern high-level programming languages combining object-oriented and functional programming. We present an integration of four separate internal DSLs (libraries), considered useful for embedded program- ming, in the Scala programming language, for programming and testing component-based systems. These include a DSL for defining components and their connections, and a DSL for programming the individual components as hierarchical state machines. Two additional DSLs support testing, and include a DSL for writing temporal logic flavored test oracles for monitoring program executions, and a DSL for rule-based test input generation. The paper discusses the gap between Scala as used here and the needs for embedded systems programming.

Bocchino, Robert↗

NASA NTRSDate not supplied

NASA Icing Overview 2023

This presentation summarizes NASA icing research for an invited talk to be presented on June 22, 2023, at the SAE International Conference on Icing of Aircraft, Engines, and Structures. The presentation describes the NASA icing portfolio including facilities and computational tools. In addition, high-level summaries of NASA’s current icing research activities are provided. This includes: (1) Transonic Truss Brace Wing, (2) High Lift Common Research Model, (3) Advanced Air Mobility, (4) Characterization of Low Ice Adhesion Materials, (5) High Ice Water Content Flight Research, (6) Simulated Inter-compressor Duct Research Model, (7) Efficient Quiet Integrated Propulsor. Finally, the presentation summarizes collaboration and partnership opportunities with NASA.

Icing↗

NASA NTRS2023

Do Citizen Science Intense Observation Periods Increase Data Usability? A Deep Dive of the NASA GLOBE Clouds Data Set With Satellite Comparisons

The Global Learning and Observations to Benefit the Environment (GLOBE) citizen science program has recently conducted a series of month-long intensive observation periods (IOPs), asking the public to submit daily reports on cloud and sky conditions from all regions of Earth. This provides a wealth of crowdsourced observations from the ground, which complements other conventional scientific cloud data. In addition, the GLOBE reports are matched in space and time with geostationary and low Earth orbit satellites, which allows for a straightforward comparison of cloud properties, and minimizes the biases associated with mismatched sampling between participants and satellites. The matched GLOBE dataset is used to calculate the mean observed cloud cover by atmospheric level both worldwide and by region. The overall magnitudes of cloud cover between the GLOBE participants and the matched satellites agree within 10%, which is notable given the distinctly different natures of the data sources. The mean vertical cloud profiles show GLOBE reporting more low-level clouds and fewer high-level clouds than satellites. The low cloud disagreement is likely related to satellites missing low clouds when high clouds block their view. Conversely, the high cloud disagreement is related primarily to cloud opacity, as satellites may miss some optically thin clouds. Monte Carlo testing shows the results to be robust, and the tripled amount of IOP data reduces uncertainty by half. These findings also highlight ways in which citizen science IOP data may be used to support scientific research while accounting for their unique properties. Plain Language Summary: Citizen science is becoming an increasingly prominent aspect of scientific research, and so it important to study how citizen science data can be used effectively. For example, The GLOBE Program has recently conducted a series of special data-collecting events, or “challenges”, which gathered large numbers of reports on cloud and sky conditions. Because NASA GLOBE Clouds matches the participant reports with cloud observations from satellites, we can use these data to get a combined view of clouds from above and below. When looking at the average cloud cover for different atmospheric levels across Earth, we find that the GLOBE participants and the satellites agree quite closely. This is a surprising and fascinating find, given how different in nature volunteer ground reports are to satellite measurements. However, there are some small but notable disagreements between GLOBE participants and satellites about the distribution of cloud cover at different levels. In addition, by testing the data for uncertainty, we show that the results from the GLOBE data are reliable, and that more public participation improves the reliability. So, by carefully designing the analysis methodology, and by testing for the uncertainty of the data, citizen science can make a meaningful contribution to scientific research.

J. Brant Dodson↗

NASA NTRS2022

Mars 2020 Entry, Descent, and Landing System Software Implementation

On February 18th, 2021, the Mars 2020 project's Perseverance Rover successfully touched down on the Martian surface after nearly eight years of development. The Mars 2020 Entry, Descent, and Landing (EDL) System largely leveraged heritage from the Mars Science Laboratory (MSL) EDL System while employing targeted technological advancements. The landing process is autonomously directed by a software behavior implemented in the rover's primary flight computer called the EDL Timeline that assumes control of the vehicle six days before atmospheric entry. This paper first walks through the basics of the EDL Timeline mechanics and how the behavior is designed to account for internal system variations and environmental unknowns. It then summarizes the interactions between the EDL timeline and other high-level system behaviors like spacecraft mode transitions and system fault protection, focusing on the complications that arise when passing spacecraft control between executive functions. Although the MSL-inherited EDL System is reliable and capable, targeted updates and a thorough verification and validation program were required for Mars 2020. This paper discusses changes made to close vulnerabilities discovered during both MSL and Mars 2020 development cycles, landing system capability enhancements that were enabling for Mars 2020's mission, and how these updates were integrated with the heritage system. It then describes how both analysis and testing campaigns were utilized to verify and validate all aspects of EDL and system behaviors that run during the six days before landing, as well as the operational workarounds that were needed to address problems found during the development and commissioning process. Finally, this paper imparts lessons learned from Mars 2020 EDL development, implementation, and operations, emphasizing how systems designed to conduct time-critical mission events with low margin of error can be improved in the future.

Stehura, Aaron↗

NASA NTRS2022

The Psyche Planning Software Subsystem: Creating a Robust Toolset for a Discovery-class Mission

Psyche is a Discovery-class mission to the small metal-rich asteroid (16) Psyche, and is slated to launch in 2022. Psyche, like many missions, requires low-cost activity planning and sequence generation that serves as the backbone to overall uplink design. Such tools must be maintainable over long periods of operations, and powerful enough to solve complex issues that deep-space one-off missions encounter. In this paper we introduce cost-effective solutions that leverage inner- and open-source principles to meet a variety of common and novel use cases.The uplink process that was designed to meet these challenges is presented, as well as the data-flow through the high-level architecture of the planning software subsystem. The user-facing planning tools are described, particularly the Science Opportunity Analyzer, the Plan Editor, Psyche’s planning automation in the Blackbird framework, and Psyche Simulation Reports. All these applications are either new or have been substantially revamped to meet Psyche’s concept of operations. In particular, ensuring the entire toolchain can correctly process epoch-relative activities is discussed. Underlying the main applications are a common set of dependencies developed and maintained by a new cross-mission association of planning developers. In this way, Psyche can inherit well-tested functionality which saves effort and ensures its developers can focus on solving domain challenges. Quality control of the applications and libraries is ensured with a code-review and unit-test based novel ‘CM lite’ process. Collaboration with international industry and academia using the open-source modules is already occurring.The planning and scheduling software is designed to maximize operator awareness of the integrated plan at every step of the process and use common interfaces and file formats to easily transfer information. Design choices plus the team’s test-driven development process enables more expansive capabilities compared to the decentralized planning and sequence generation functions typical of Discovery-class orbiters without significant development cost increases. Benefits and drawbacks of Psyche’s approach are discussed, including comparison to other missions and tools where appropriate.

Ramanathan, Keshav↗

NASA NTRS2022

New Rover Conops with High-Performance Onboard Computing: Give Up Raw Data to Reduce Ops Cost and Do More Science

A major portion of time during the tactical operation of Mars rovers is spent for selecting, prioritizing, and coordinating sciences and engineering activities such that they fit within resource constraints, including the downlink data volume, energy, and time. In particular, the downlink data volume constraint is getting particularly tighter in recent missions because modern instruments produce increasingly high data volume while the communication bandwidth is essentially bounded by the law of physics. Tactical operation would be substantially simplified, hence the operation cost could be reduced, if the data volume constraint is relaxed or even removed. In this abstract, we propose a new operation paradigm for achieving this goal. The key observation is that, both in science and engineering applications, the bit size of raw data is typically much greater than the volume of processed information that is needed for scientific or engineering analysis. For example, a full-resolution image from Mastcam-Z, the main science camera on Perseverance, is about 700 kB in volume and we downlinked 29,685 images up to Sol 243, totaling ~20 GB of data. But of course, scientists do not use every pixel of these images; what they really look for in the images are geological features, typically represented by specific geometric configurations or textures. An end product after processing hundreds of Mascam-Z images could be a single geological map summarizing the spatial distribution of the features. For another example, a 100-meter drive of Perseverance produces 7-12 MB of drive telemetry, which records every detail of the rover's motion at 8 Hz, including position, attitude, steering angles, encoder readings, motor currents and many other information. But what the ground engineers eventually pay attention to is the signs of anomaly, such as excessive motor currents or high slip; if a drive is nominal, the vast majority of this data is unused. What if, then, we process the raw data onboard and only downlink the processed data that is relevant to scientific or engineering analyses, such as a list of detected science features (with cropped images) or a list of potential signs of anomaly while driving? A major roadblock for such onboard, high-level information processing has been the onboard computational resource. RAD750, the main onboard computer of Perseverance, is obviously not sufficient for performing complex image or signal processing such as object detection, semantic segmentation, or anomaly detection. Interestingly, RAD750 is not the best processor that Perseverance has; Qualcomm's Snapdragon 801, a modern mobile processor, is on her Heli Base Station, a device for communicating with Mars Helicopter Ingenuity; also, Intel's Atom E3845 processors are on engineering cameras. In the reminder of this paper, we will introduce two particular uses cases of these high-performance co-processors (meaning auxiliary CPU, GPU, or other types of processors that are separate from the main processor that runs the main flight software) for lowering operation cost and accommodating more science activities for a given communication constraint.

Didier, A.↗

NASA NTRS2023

Identifying and Closing Medical Capability Gaps for Human Spaceflight Missions Beyond Low Earth Orbit

BACKGROUND: Features of human space missions beyond low Earth orbit such as increasing distance from Earth, lack of real-time communication, and limited or no evacuation or resupply capability are expected to drive an increase in medical risk and require crews to operate in an increasingly autonomous fashion. A diverse set of stakeholders at NASA are seeking to fund the development of concepts of operations, medical requirements, and medical capabilities for such missions. However, a systematic approach to identification of current medical capability gaps and a strategic framework to gap closure is needed. OVERVIEW: The Exploration Medical Integrated Product Team (XMIPT) has developed a list of nine high-level medical capability gaps and associated activities required for gap closure. The list was derived based on inputs from subject matter experts at NASA including flight surgeons, other clinical providers, as well as operational and research communities regarding medical capabilities required to support human missions to the Moon and the Mars surface. Responses were reviewed and distilled to identify common themes across capabilities. To ensure alignment with established human system risks, the gap list was further refined based on inputs from NASA’s Human System Risk Board. Relevant medical gap closure activities outside of those funded by the XMIPT were identified through solicitation of inputs from Elements of NASA’s Human Research Program (particularly Exploration Medical Capability), the broader medical operations community, and other stakeholders. This medical capability gap list is reviewed and updated regularly as new information becomes available or new stakeholders are identified. DISCUSSION: The medical capability gap list has matured to include a large group of NASA stakeholders and development activities. This has enabled articulation of priorities to funding entities and programmatic stakeholders, while serving as an accessible resource summarizing gap closure activities, relevant programmatic infusion points, and opportunities for collaboration between stakeholders. This presentation will provide an overview of the nine NASA medical capability gaps and their associated gap closure activities.

Moriah Thompson↗

NASA NTRSDate not supplied

High-Intensity Radiated Field (HIRF) Map - An Avoidance Approach for UAM, AAM, and UAS Vehicles

Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in similar airspace to Transport Category Rotorcraft, thereby requiring them to meet the most severe requirements for HighIntensity Radiated Fields (HIRF) certification. The environment is severe for rotorcraft, much more so than for fixed-wing aircraft, due to lower altitude operations, potentially exposing the vehicles to close and direct view of high-power transmitters on the ground. High-level HIRF exposure potentially leads to avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF will be a significant barrier to size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel approach to HIRF protection, which reduces costs by testing and certifying vehicles to a “vehicle tolerance level” that is lower than required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources, calculated based on the vehicle's tolerance level and transmitter characteristics such as transmit power, antenna beamwidth, and direction. Tailored maps are developed, identifying transmitters and avoidance zones within an operating area or along a flight path, allowing for restricted vehicle operations. The HIRF avoidance zones could be smaller for vehicles with higher tolerance levels, enabling them to operate closer to transmitters. Transmitter data can be extracted from regulatory databases like the FCC and NOAA. A map tool is developed in Matlab to calculate and plot HIRF avoidance zones from transmitters in FCC and NOAA databases as proof of concept. Illustrations are presented for AM/FM/TV transmitters, communication satellite dishes, and weather radars. Also illustrated are HIRF zones for smaller transmitters, including land-mobile radios, pagers, microwave links, and cellular towers. An example of flight planning around the transmitters is presented. This method is a substantial deviation from the standard approach and involves slightly higher flight-planning complexity, but the potential cost savings are significant. Future AAM/UAM/UAS aeronautical charts could include these new HIRF avoidance zones.

HIRF↗