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At least 1,603 records · Page 89

Test & Measurement System Security in an IT World

Automated test and measurement systems are coming under increased cybersecurity scrutiny. Most of these systems fall under the “Operational Technology” designation, as defined by NIST, and often have unique requirements that conflict with enterprise security policy. These systems are typically not well understood by traditional enterprise IT personnel, which leaves them ill-supported or invalidated.▪This presentation attempts to help Test System owners recognize the security landscape, determine their unique system requirements and concerns, and negotiate a peer-level working arrangement with an existing IT department while maintaining a NIST-recommended level of autonomy and sovereignty.

automated test↗

CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

clinical decision support↗

Novel Ways to use the International Spacer Station as an Exploration Analog: International Progress in Planning "ISS4Mars"

In October 2020, International Space Station (ISS) Partner Agencies held a set of international workshops to solicit and develop creative and forward-looking ideas for using the ISS as an analog for preparation for Mars missions during its 3rd decade of operations. The workshops brought together participants from nine international space agencies or organizations, with stakeholders consisting of research managers, discipline experts, technology developers, flight physicians, flight operators, and astronauts. Breakout meetings and brainstorming sessions were conducted focusing on the following topics: Critical hazards and countermeasures for the transit to Mars; gravity transitions and early surface operations; environmental control and life support systems; food systems; human microbiome, microbial monitoring, and planetary protection; medical operations for Mars missions; isolation and confinement; autonomous systems and crew-centered autonomy; and communications delay effects on operations. In many cases the scenarios and approaches identified were compelling but challenging to implement under the current utilization structure used to manage the ISS for experiments. Following the series of workshops, a team of utilization leaders across the ISS partnership worked to compile the workshop recommendations and extract a set of use-cases with their prerequisites and constraints. The work considered the following aspects: what can be effectively done on ISS; which new technologies, approaches and scenarios are feasible; what alternatives could be considered; and what steps should be taken to enable integrated testing and future use of ISS as an analog for Mars missions. The final report will be published so that the use cases can be considered in each agency’s strategic planning processes. This paper will cover the process of international assessment in detail and how this process has influenced and broadened the vision of ISS utilization beyond single experiments to integrated studies and testing for future Mars missions. This approach to international collaboration informs both the next decade of international exploration research on the ISS and advancement of its utilization as an analog for deep space missions. For many of the participating partners, it also helps to frame the strategy for human research in Artemis as we begin planning for human missions to the moon. We conclude with a summary of the progress on the actions in the report and the additional implementation discussions that have occurred across the partnership.

Julie A Robinson↗

Machine Learning for Extravehicular Mobility Unit (EMU) Glove Inspections

The Extravehicular Mobility Unit (EMU) Glove Machine Learning Inspection project utilizes machine learning to expedite the inspection, analysis, and recommendation for continued use of space suit gloves post spacewalks. Today, ISS glove photos are individually reviewed by a team of experts to determine the conditions of space suit gloves. For this project the Microsoft Azure platform is used to perform Automated Machine Learning (AutoML) to detect issues with tagged images from previous Extravehicular Activities (EVA’s) to build a predictive model. The model analyzes a test image and deems the glove GO or NO-GO for additional EVA’s. The goal for this ML project is to decrease the time spent reviewing images by ground personnel and crewmembers in high frequency EVA locations such as the Moon and Mars. For destinations such as the Moon and Mars the goal is to give crew autonomy in determining glove conditions with limited support from Earth. This paper will outline the results to date and future work needed to expand the capability for in-situ recommendations.

EVA↗

Surface Systems Capability Gaps for Enabling NASA’s Sustainable Lunar Operations

This paper discusses the NASA Ground, Test, and Surface Systems Taxonomy (TX-13) related capability gaps, including details of architecture, technology, engineering, and policy gaps for enabling sustainable lunar surface operations and subsequent Mars missions. Architecture gaps include standardized architectures and interfaces, multi-element systems engineering and integration, design for supportability, and nuclear payload processing and launch approach. Technology gaps, primarily focused on uncrewed surface operations, include automated/autonomous cryogenic loading, transfer, servicing, and storage of commodities; health determination and fault management; automated/autonomous planning and scheduling; automated/autonomous inspection, maintenance and repair; logistics management and reliability; launch and landing site preparation; commodity management; and advanced umbilicals and dust tolerant interfaces. Engineering gaps include high-purity propellant production for ground and surface applications and large-scale xenon servicing capabilities. The policy gap includes nuclear propulsion acceptance testing and qualification approach. Strategically identifying human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle is essential for achieving the mission objectives for a sustainable human lunar presence, improving performance and mission effectiveness, reducing operations costs and reliance on humans to perform tasks, and accommodating ground communication delays.

Surface Systems↗

Results of the Field Test and Defining Sensormotor Fitness for Duty Standards

The primary goals of the Field Test were (1) to determine functional abilities associated with long-duration space flight crews beginning as soon after landing as possible (< 2 hours), and (2) to characterize the time course of recovery with additional follow-up measurement sessions within 24 hours after landing. The NASA and Russian teams have collected data on a total of 39 different United States Orbital Segment (USOS) and Russian crewmembers, with 9 Russian crewmembers being tested twice (total of 48 tests). Eighteen subjects (7 Russian, 11 USOS) completed a reduced Field Test (pilot) protocol and 30 subjects (19 Russian and 11 USOS) participated in the full Field Test. This presentation will focus on a subset of the measures that will be used in the upcoming ground study to determine sensorimotor fitness for duty standards, namely: tandem walk, obstacle walk, eye-hand coordination task, finger-to-nose task, and Computerized Dynamic Posturography (CDP). Exploration-class missions including Artemis, Gateway, and beyond will require a new level of autonomy around periods of gravitational transition, where sensorimotor disturbances increase. The operational support that is available upon return to Earth including rescue teams, medical interventions, and the ability to rest as needed will not be available after landing on the lunar or Martian surface. Because of this, there is a need to define fitness for duty standards that will help inform crew capabilities during and soon after gravitational transitions. Due to the new requirements of the exploration environment, we must utilize a set of exploration field measures, for which no previous spaceflight data exists to define fitness for duty standards. A Sensorimotor Adaptation Analog (SAA) that can provide different levels of acute disorientation through combined vestibular, visual, and proprioceptive disruptions will be used to increase the range of performance in exploration field measures, simulating the moderate-to-severe performance decrements observed in spaceflight. The levels of SAA will be titrated and validated by comparison to gold standard measures that have a wealth of spaceflight data at different time points during recovery. These data will be pulled directly from the results of Field Test and help ensure the range of performance while being exposed to SAA mimics the range of performance from pre-flight to immediately postflight in Field Test subjects. Specifically, we will be using the tandem walk, obstacle walk, eye-hand coordination task, finger-to-nose task, and CDP as the gold standard measures. Referencing this Field Test data in the form of gold standard measures will also help us characterize and contextualize how each magnitude of SAA disorientation compares to recovery from long-term microgravity exposure.

M J F Rosenberg↗

Clinical Decision Support Software: Modeling and Capabilities

With its distance from Earth and communication delays, exploration space flight will place new demands for crew autonomy. Crewmembers operating during such missions require a dedicated Clinical Decision Support System (CDSS) that enhances their earth independence by augmenting their knowledge, skills, and abilities in different medical scenarios. A CDSS is a software application that must function optimally in diverse and varied scenarios (while interfacing with and providing actionable information to appropriate vehicle systems) to augment crew performance by enhancing or adding knowledge, skills, and abilities that preserve health and wellness and ultimately helping to ensure mission success. In addition, the software tool should provide various functions and computational models to meet the demands of astronauts beyond low earth orbit.

B Russell↗

Supervised Autonomous Assembly to Create and Evolve Persistent Assets

Supervised autonomous assembly (SAA) will create a paradigm shift in the planning and design of future persistent assets (PAs), both in near zero-g environments and on planetary surfaces. SAA refers to an autonomy approach that has the benefits of autonomous assembly as well as the benefits provided by a supervisor (operator) who is available to resolve unexpected situations. SAA provides both increased design freedom as well as reduced programmatic risk. SAA enables evolution of future PAs over decades as in-space operations transition from single purpose missions to creation of PAs, such as laboratories and experimental stations which more closely resembling terrestrial laboratories that can easily adapt and evolve to new missions leveraging repeated visits to the PA. The ability to evolve enables PAs to rapidly respond to changing objectives resulting from new questions as our understanding improves. A recently initiated National Aeronautics and Space Administration (NASA) project in the Space Technology Mission Directorate (STMD) Game Changing Development (GCD) Program called the Precision Assembled Space Structure (PASS), leverages the advantages of SAA to develop technologies that enable efficient creation and evolution of hexagonal topologies; both planar (example: fuel depots) and curved (examples: telescopes and shelters). PASS will be used to provide context for the philosophy and concepts discussed as well as the decision and selections made. PASS objectives are: a) Develop confidence in SAA and on-orbit servicing, assembly and manufacturing (OSAM) technologies by executing a test campaign that uses a path-to-flight autonomous precision assembly process directly applicable to future space telescopes. b) Test autonomous technologies including automated path planning and error recovery, to emphasize a robust approach that relies on generic robots and special purpose tools. c) Validate critical component models using a digital twin that includes the assembled primary mirror support structure and assembly process. A digital twin is a high-fidelity simulation of the asset capable of predicting the on-orbit performance. The paper concludes after identifying the critical need for a modest assembly flight experiment to validate and develop confidence in the SAA paradigm, thus accelerating adoption of the benefits described. SAA is a game changing paradigm that enhances the ability of an organization to infuse new technology through rapid evolution of PAs while leveraging OSAM technologies.

Structural Modeling↗

DEVELOP’s Approach to Experiential Learning

The NASA DEVELOP Program addresses environmental decision making needs and geoscience workforce development through 10-week feasibility studies that apply Earth observations to environmental issues at hand. The program builds capacity to use geospatial information in both its participants (students, recent graduates, early career professionals, and transitioning career professionals) and partner organizations (federal agencies, state & local governments, non-profits, and private industry). This is accomplished through a structured project execution model that provides opportunities for participants to have autonomy, learn “on the job,” and gain new skillsets for working with remote sensing data. A pipeline of leadership positions enhances opportunities for individuals engaged in the program to get hands-on experience conducting data analyses, communicating their work, leading technical projects, and building their knowledge bank of Earth-observing satellite capabilities. These skillsets and knowledge are then transferred to partners through the projects. This panel contribution will introduce the DEVELOP model, highlight experiences of participants, and share the program’s insights into good practices for effective experiential learning.

Capacity Building↗

Autonomous System Operations for Lunar Safe Haven Establishment and Sustainment

To enable a sustainable, permanent human lunar presence, NASA must provide a safe haven shelter to protect astronauts and equipment from radiation, thermal extremes, and micro-meteoroids (MM). Planning and development for a robust Safe Haven includes an examination of NASA activities in site preparation, excavation, regolith transfer, surface operations, autonomous monitoring and maintenance, advanced manufacturing, and in-situ resource utilization (ISRU) for identifying the best approaches when implementing a safe haven shelter. These NASA activities were reviewed as a part of a trade study conducted at NASA Langley to assess technological needs and estimated technology readiness levels (TRL). This paper presents a thorough review of the role and level of autonomy in the establishment and sustainment operations of a Lunar Safe Haven.

Walter J Waltz↗

Adaptive Multi-Sensor Fusion Based Object Tracking for Autonomous Urban Air Mobility Operations

Autonomous operations are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets. In order to enable this autonomy, systems must be able to build independently an accurate and detailed understanding of the own vehicle state as well as the surrounding environment, this includes detecting and avoiding moving objects in the sky, which can be cooperative (aircraft, UAM vehicles, etc.) as well as noncooperative (smaller drones, birds, ...). This paper focuses on the object tracking part that relies on adaptive multi-sensor fusion, taking into account specific properties and limitations of different sensor types. Results show the impact of dropouts of individual sensors on the accuracy of the tracking results for this adaptive sensor fusion approach.

sensor fusion↗

Adaptive Multi-Sensor Fusion Based Object Tracking for Autonomous Urban Air Mobility Operations

Autonomous operations are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets. In order to enable this autonomy, systems must be able to build independently an accurate and detailed understanding of the own vehicle state as well as the surrounding environment, this includes detecting and avoiding moving objects in the sky, which can be cooperative (aircraft, UAM vehicles, etc.) as well as noncooperative (smaller drones, birds, ...). This paper focuses on the object tracking part that relies on adaptive multi-sensor fusion, taking into account specific properties and limitations of different sensor types. Results show the impact of dropouts of individual sensors on the accuracy of the tracking results for this adaptive sensor fusion approach.

object tracking↗

Autonomous System Operations for Lunar Safe Haven Establishment and Sustainment

To enable a sustainable, permanent human lunar presence, NASA must provide a safe haven shelter to protect astronauts and equipment from radiation, thermal extremes, and micro-meteoroids (MM). Planning and development for a robust Safe Haven includes an examination of NASA activities in site preparation, excavation, regolith transfer, surface operations, autonomous monitoring and maintenance, advanced manufacturing, and in-situ resource utilization (ISRU) for identifying the best approaches when implementing a safe haven shelter. These NASA activities were reviewed as a part of a trade study conducted at NASA Langley to assess technological needs and estimated technology readiness levels (TRL). This paper presents a thorough review of the role and level of autonomy in the establishment and sustainment operations of a Lunar Safe Haven.

Walter J Waltz↗

Designing a Software Architecture for the Precision Assembly of Space Structures

As NASA’s space exploration and science missions expand in complexity, longevity, anddistance beyond earth’s orbit, Orbital Servicing, Assembly and Manufacturing (OSAM)technologies and concepts have become a critical area of ongoing research and innovation.Artemis’ Moon-to-Mars goals of building sustainable elements on and around the Moon andMars that allow our robots and astronauts to explore and conduct more scientific researchwill demand in situ resource utilization, construction, and maintenance to succeed. In-spaceAssembly (ISA), as a sub-component of OSAM, focuses on the on-orbit building or fabricationof mission infrastructure and payloads. One such ISA application is highlighted by the recentNASA In-Space Assembled Telescope (iSAT) study, which stated that the next generation ofspace observatories will exceed the fairing size of existing or even planned launch vehicles andISA has emerged as a viable approach for observatory assembly. Research efforts at NASALangley Research Center have led to the design of a novel TriTruss structural concept for themodular construction of large complex persistent platforms. The TriTruss design and otherdeveloping OSAM technologies enable larger and persistent space missions that would notbe possible with single-launch-sized structures. For example, 20 meter or larger telescopesor orbital platform applications. However, the increased complexity will require autonomousoperations for the construction and maintenance of long-term infrastructure to achieve missionsuccess. NASA’s Precision Assembly of Space Structures (PASS) project is focused on thestructural and autonomy capabilities required to construct an iSAT in deep space. PASSresearch efforts will develop and validate critical technologies needed for effective efficienton-orbit assembly that can be confidently adopted for future systems. PASS will utilize theTriTruss modules to demonstrate the autonomous modular assembly of a 20m-class iSAT mirrorbackbone structure including simulated mirrors and wiring harness. In this paper, we addressthe software and hardware design considerations, technologies, and challenges of designing arobust robotics framework for assembling modular space structures in support of In SpaceAssembly missions in general as well as for PASS specifically.

Benjamin N Kelley↗

Clinical Decision Support: Path to Functional Requirements

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

Clinical decision support↗

What to Take? When to Make? How to Break Even? Avoid Mistakes in Microbial Biomanufacturing in Support of Human Near-to-Deep-Space Exploration

In this whitepaper, we call for the concept of biomanufacturing to be expanded and widely adopted as a support function of human Space-travel. To demonstrate the impact and value of this strategy, we identify the specific offworld scenarios where the concept is most applicable, as well as the vital inventories that can be made available thereby. This will serve to increase capabilities of human operations beyond Earth-orbit and allow for extended mission design through greater autonomy while minimizing risks through redundancy. To this end, we sketch the potential routes and systems to arrive at these goals, in the form of specialized microbial cell factories that can most meaningfully leverage the resources available along the journey. The strategic vision presented here relies heavily on Synthetic Biology as it integrates with major plans for In Situ Resource Utilization and highlights applications that engineered biology is uniquely suited to address. We finish by advocating for the research and development investments that need to be made in order to significantly increase readiness of these technologies over the coming decade. This dovetails with current efforts to return humans to the Moon with Mars on the horizon. Besides ensuring the feasibility and sustainability of crewed Space exploration and habitation, the advancement of these technologies may spawn a new scalable microgravity-based biotechnology industry that contributes to the creation of a circular economy on Earth.

Biomanufacturing↗

NASA Science Technology Development Programs for Ocean Worlds Exploration

The exploration of ocean worlds such as Europa and Enceladus supports NASA’s goal to search for life and potentially habitable regions elsewhere in the universe, and further promises to help us understand the origins, evolution, and limits of life on Earth. Over the past several years, NASA’s Planetary Science Division has funded several technology development programs to enable future surface and subsurface missions to ocean worlds. These programs include Instrument Concepts for Europa Exploration (ICEE), Concepts for Ocean Worlds Life Detection Technology (COLDTech), Scientific Exploration Subsurface Access Mechanism for Europa (SESAME), Applied Information Systems Research: Autonomous Robotics Research for Ocean Worlds (AISR:ARROW), and Astrodynamics in Support of Icy Worlds Missions. Tasks selected under these programs include the development of scientific instruments including seismometers, imagers, spectrometers, and organic analyzers, and platform technologies including drills, melt probes, through-ice communications, radiation-hard electronics, and autonomy for surface operations. This paper describes the objectives of each of these programs and provides a summary of the work that has been completed or is underway in each.

technology↗