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At least 1,063 records · Page 59

How Autonomous Intelligent Systems Can Facilitate Earth-independent Medical Care: Going Beyond Telepresence

During the last decade, teleoperated robotic systems have extended humans’ sensorimotor competence to digitally fly beyond the physical barrier of distance and scale and thus transmit sensorimotor skills of the human through direct communication. Telepresence capabilities have enabled tele-physical remote access at small scales thanks to telerobotic mediums. Although the concept was initially motivated by space applications, such technologies quickly have expanded into the medical domain and resulted in teleoperated medical robots, including telerobotic surgical systems (such as the da Vinci surgical system). Effective telepresence fundamentally depends on an agile, reliable, and secure communication medium that can transmit real-time information between the operator and a remote device. However, direct telepresence may not be achievable for long-duration exploration spaceflight missions. Thus, autonomous systems and local intelligence represent potential solutions to the aforementioned issues. One example solution employs demonstration systems which enable learning from the pre-captured inputs of a skilled human operator. These will be computationally modeled and later probabilistically replicated toward the completion of remote physical tasks when direct telepresence is not viable - such as under communication blackout conditions. In other words, trained autonomous systems (e.g., robots) can perform remote operations that mimic the physical performance of experts during remote operations/training. Beyond learning the physics of the task, autonomous agents can also be used to conduct algorithmic decision-making that mimics the higher-level cognition of the expert. Thus, using an autonomous system, pre-trained cognitive and manipulation-based skills can be leveraged (acquired during pre-mission events) to produce digital twins of an intelligent operator. Such systems can be used for the real-time conduction of intricate tasks in complex and unstructured environments. Such systems will operationalize “cognitive digital twins” and can expand the reach of human cognition and manipulation through the power of data-driven learning from demonstration algorithms. This system category will be discussed as a fully autonomous operation in this talk. In addition to the above, we will also propose and discuss the possibility of partial-automation using remote intelligence and remote sensing. In contrast to full automation, partial automation can close the loop through a local operator equipped with augmented sensory awareness through wearable systems. Such technologies will allow the local operator to conduct delicate tasks while being guided using sensory augmentation and being monitored to gauge her/his level of cognitive focus and performance. The difference with the previous category is that a remote human will conduct the task. Further, rather than making a digital twin of human cognition, we will augment the control inputs of the local human to match those of the skilled expert operator who is not accessible in real-time. Going beyond classic telepresence and thus approaching intelligent telepresence, our vision is that autonomous agents will eventually enable the safe, consistent and efficient delivery of complex, remote and smart medical care during space exploration across operators in an Earth-independent fashion. We will discuss our collective vision from NASA and MERIIT@NYU lab in this talk.

Telepresence↗

Culture-Independent Fungal Profiling for the International Space Station using Nanopore Sequencing: Method Development

Microbial monitoring of the International Space Station (ISS) environment is a crew health requirement that encompasses both bacterial and fungal identification. To achieve this currently, culture-based methods are used for sample collection, and these samples must be returned to the laboratory for analysis. The use of culture and the need for sample return to Earth results in a bias toward culturable organisms and causes a significant delay between sample collection and delivery of final data (weeks to months), respectively. Recently, advancements in molecular technology have aided a broad range of applications, including medical, industrial, and basic sciences. Additionally, increases in portability and ease-of-use of molecular platforms have provided point-of-use capabilities demonstrated by the miniPCR thermal cycler (miniPCR bio) and the MinION sequencer (Oxford Nanopore Technologies). Together, these devices have been applied to, and validated for, the identification of bacteria onboard the ISS. Building on this work, we have developed a spaceflight-compatible fungal workflow. Molecular-based fungal analysis is complicated by low biomass, difficult-to-lyse spores, debate regarding the region for taxonomic assignment, and the lack of bioinformatic pipelines and reference databases. To overcome these difficulties, primers yielding an ~ 2 Kb amplicon were validated against a wide range of ISS fungal isolates. The current spaceflight library preparation was substantially optimized, a bioinformatic pipeline was created, and refinements to the UNITE database were implemented. To compare this optimized method to the current culture-based standard, 30 sample sets (60 total swabs, two swabs held in tandem) were evaluated. Parallel fungal profiles were obtained between the two methods, with the culture-independent method revealing increased diversity. The addition of this method to the already established bacterial process fulfills the crew health identification requirement. Moreover, the implementation of this method onboard ISS will enhance our understanding of its unique fungal microbiome.

Hang N. Nguyen↗

A Strategy for Advancing Earth Independent Medical Operations

Exploration medical operations to the Moon and Mars present unprecedented challenges for providing in-mission medical care. The greater distance from Earth is the primary hazard that drives the need for a medical operations paradigm shift from low earth orbit mission. Increasingly complex long duration and long distance missions will have resource constraints (ex: mass, power, volume, data), a paucity of resupply or evacuation opportunities, and disruptions in real-time communications. In order to advance a more autonomous medical approach, a multi-faceted strategy will need to optimize all aspects of human health and performance in space. This strategy will include: increasing onboard medical autonomy through the development of novel crew health and performance systems; decision support capabilities to augment astronauts’ abilities in preventing, diagnosing, and treating medical conditions; creating new procedures and training tools for skill maintenance and just-in-time training; and enabling rapid crew access to data from all on-board systems, leading to better-informed, real-time, autonomous decisions. Collectively, this approach can be referred to as “Earth Independent Medical Operations” (EIMO). The Exploration Medical Capability Element of NASA’s Human Research Program has undertaken a longitudinal planning process to consensus around EIMO. Technical interchange meetings will occur with key constituents in late 2022 and again in early 2023 to define EIMO in practical terms and identify key elements of an EIMO system, with greater conceptual articulation and dissemination planned for the second half of 2023. We will share insights into the strategy for internal and external consensus building around EIMO, with a particular focus on the approach to partner stakeholders within NASA as well as commercial agencies.

Jay Lemery↗

Constraining Global Coronal Models with Multiple Independent Observables

Global coronal models seek to produce an accurate physical representation of the Sun's atmosphere that can be used, for example, to drive space-weather models. Assessing their accuracy is a complex task, and there are multiple observational pathways to provide constraints and tune model parameters. Here, we combine several such independent constraints, defining a model-agnostic framework for standardized comparison. We require models to predict the distribution of coronal holes at the photosphere, and neutral line topology at the model's outer boundary. We compare these predictions to extreme-ultraviolet (EUV) observations of coronal hole locations, white-light Carrington maps of the streamer belt, and the magnetic sector structure measured in situ by Parker Solar Probe and 1 au spacecraft. We study these metrics for potential field source surface (PFSS) models as a function of source surface height and magnetogram choice, as well as comparing to the more physical Wang–Sheeley–Arge (WSA) and the Magnetohydrodynamic Algorithm outside a Sphere (MAS) models. We find that simultaneous optimization of PFSS models to all three metrics is not currently possible, implying a trade-off between the quality of representation of coronal holes and streamer belt topology. WSA and MAS results show the additional physics that they include address this by flattening the streamer belt while maintaining coronal hole sizes, with MAS also improving coronal hole representation relative to WSA. We conclude that this framework is highly useful for inter- and intra-model comparisons. Integral to the framework is the standardization of observables required of each model, evaluating different model aspects.

S. T. Badman↗

Enabling Human Space Exploration Missions Through Progressively Earth Independent Medical Operations (EIMO)

Goal: Current Space Medicine operations depend on terrestrial support to manage medical events. As astronauts travel to destinations such as the Moon, Mars, and beyond, distance will substantially limit this support and require increasing medical autonomy from the crew. This paper defines Earth Independent Medical Operations (EIMO) and identifies key elements of a conceptual EIMO system. Methods: The NASA Human Research Program Exploration Medical Capability Element held a 2-day conference at Johnson Space Center in Houston, TX with NASA experts representing all aspects of Space Medicine. Results: EIMO will be a process enabling progressively resilient deep space exploration systems and crews to reduce risk and increase mission success. Terrestrial assets will continue to provide pre-mission screening, planning, health maintenance, and prevention, while onboard medical care will increasingly be the purview of the crew. Conclusions: This paper defines and describes the key components of EIMO.

ExMC↗

Task Load Management in Earth Independent Medical Operations

BACKGROUND: Medical care in spaceflight carries a high task load and can easily overwhelm a small crew. Present day operations in low Earth orbit (LEO) offload most medical tasks to ground teams in mission control. This team includes dozens of flight surgeons, specialists, and engineers and supports the on-orbit crew in monitoring environmental systems, tracking medications, guiding procedures, providing expert advice, and many other tasks. However, the physical limitations of the speed of light and technical limitations of bandwidth, channel capacity, and signal processing mean that missions beyond LEO cannot rely on this level of telemedical support. The further we travel from Earth the more these tasks will fall on the shoulders of the crew and the greater the risk of task saturation to the wellbeing of the crew and the success of the mission. Exploration class space crews will need progressively more robust systems for managing task load as they progress further out in space. OVERVIEW: Medical task management systems will need to assist with two broad categories of tasks; cognitively intensive tasks and procedure execution tasks. In both cases the goal is for the systems to operate in the background with minimal human-in-the-loop intervention. To accomplish this such systems will need to be designed with careful consideration for human factors and human systems integration to maximize efficiency, minimize alarm fatigue, and avoid inadvertently increasing task loads. Finally, the key domains of space medicine tasking can be used to map present day and near future technologies to the areas where they are best suited to support and identify gaps which can be targeted for research and development. DISCUSSION: Task load is a major challenge for Earth Independent Medical Operations to overcome. It will require careful coordination between experts in a variety of fields paying attention to human factors and human systems integration as well as technical and medical expertise. If done well medical task management systems can handle many of the tasks currently run by humans in mission control and enable human crews to maintain terrestrial standards of care in the extraterrestrial environment.

Dana Levin↗

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗

A Multi-Faceted Approach to Demonstrating Multi-Functional Integrated Medical Devices to Advance Earth-Independent Medical Operations

INTRODUCTION TO MIM DEVICES Multi-functional Integrated Medical (MIM) devices conveniently incorporate multiple medical system capabilities within one device. The NASA Exploration Medical Integrated Product Team (XM-IPT) sponsored a market survey and trade study which identified the Tempus ProTM and the LifeBot 10® as the MIM devices that best met the evaluation criteria of the trade study. The Tempus ProTM (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) and LifeBot 10® (LifeBot Health, Chicago, IL) both provide vital sign measurements such as blood pressure, electrocardiograms, heart rate, end tidal CO2, respiration rate, pulse oximetry and temperature along with ultrasound imaging. A video laryngoscopy capability is unique to the Tempus ProTM, while the LifeBot 10® supports connectivity with a digital stethoscope, otoscope, eye exam camera, and dermatoscope. Both devices include procedural guidance capabilities and have various data transmission and report generation features. TECHNOLOGY DEMONSTRATIONS NASA’s exploration-class missions will have severe resource constraints, long return trip durations, significant communication delays, and limited resupply opportunities. The medical systems of these missions will need to fit within an Earth-Independent Medical Operations (EIMO) construct. Key features of an EIMO medical system include: 1) technologies that support the prevention, diagnosis, and treatment of spaceflight medical events; 2) components that meet mass, volume, power and crew time/training constraints; 3) consideration of the medical skill level of the astronaut caregiver; 4) collection, storage and analysis of medical data within a central data architecture; and 5) incorporation of appropriate guidance and support tools that allow crew autonomy. Evaluations are underway to determine if it will be beneficial to include MIM devices within exploration medical systems by conducting a series of planned technical demonstrations. Exploration Atmosphere Chamber studies are being performed to determine MIM functionality in a high oxygen concentration atmosphere. A side-by-side comparison of the Tempus ProTM and LifeBot 10® will be performed during ground-based demonstrations. Use of the MIM devices within an EIMO medical scenario simulation will be practiced during ground-based demonstrations in preparation for International Space Station (ISS) demonstrations of the MIM device. These various demonstrations are designed to gather evidence for or against the inclusion of MIM devices within an EIMO medical system. EXPECTED DEMONSTRATION OUTCOMES Information will be gained about the feasibility, benefits, and challenges of using a multifunctional, all-in-one, medical device for medical diagnosis. Information will also be collected about performance differences as available ground support decreases. Gaining this understanding will allow for further development of exploration medical system capabilities, which take the EIMO construct into consideration.

B. E. Lewandowski↗

A Floor in the Sun's Photospheric Magnetic Field: Implications for an Independent Small-scale Dynamo

Clette recently showed that F 10.7 systematically approaches a quiet Sun daily value of 67 solar flux units (sfu) at solar minima as the number of spotless days on the Sun increases. Previously, a floor of ∼2.8 nT had been proposed for the solar wind (SW) magnetic field strength (B). F 10.7 , which closely tracks the Sun's unsigned photospheric magnetic flux, and SW B exhibit different relationships to their floors at 11 yr solar minima during the last ∼50 yr. While F 10.7 approaches 67 sfu at each minimum, the corresponding SW B is offset above ∼2.8 nT by an amount approximately proportional to the solar polar field strength—which varied by a factor of ∼2.5 during this interval. This difference is substantiated by ∼130 yr of reconstructed F 10.7 (via the range of the diurnal variation of the East-component (rY) of the geomagnetic field) and SW B (based on the interdiurnal variability geomagnetic activity index). For the last ∼60 yr, the contribution of the slow SW to SW B has exhibited a floor-like behavior at ∼2 nT, in contrast to the contributions of coronal mass ejections and high-speed streams that vary with the solar cycle. These observations, as well as recent SW studies based on Parker Solar Probe and Solar Dynamics Observatory data, suggest that (1) the Sun has a small-scale turbulent dynamo that is independent of the 11 yr sunspot cycle; and (2) the small-scale magnetic fields generated by this nonvarying turbulent dynamo maintain a constant open flux carried to the heliosphere by the Sun's floor-like slow SW.

Solar magnetic fields↗

Earth Independent Medical Operations [EIMO] Definition Workshop

As the vanguard of human spaceflight increasingly transitions from one of low Earth orbit (LEO) to Lunar and subsequently Martian missions, there is a commensurate imperative for Earth-based medical authority to transition to space-based assets for the continued assurance of optimal astronaut health and performance. The transition to Earth Independent Medical Operations (EIMO) will be a process that enables progressively resilient systems and crews to reduce risk and enhance wellness and overall mission success for deep space exploration. Terrestrial assets will continue to be paramount in pre-mission screening, planning, maintenance, and prevention. Yet on-board care, response to unexpected medical events, and management of communication delays and dropouts will increasingly become the purview of the crew for primary management.

John Lemery↗

Optimal Communication Topology Determination and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach to sensors selection and network topology determination for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes minimum estimation error, maximum airspace coverage, minimum communication time and power consumption while guaranteeing the system observability and providing in-time quality information to a monitoring observer. The developed algorithm uses multi-objective optimization strategy taking into account trade-offs between conflicting objectives and relaxations for in time implementation. It is implemented utilizing graph theoretic tools. The approach is validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace.

Distributed sensing↗

SiC Charged Particle Telescope GRC Independent Research and Development (IRAD) Program End of Project Final Report

In an advancement over the state-of-the art, NASA Glenn Research Center (GRC) has developed a large area silicon carbide (SiC)-based charged particle telescope through an Independent Research and Development (IRAD) project. The telescope has been demonstrated to have improved noise characteristics and resolution than previous SiC detectors. This improvement will meet the challenges of compact multidirectional robust radiation detector systems to study a wide range of elementary particle mass and energies. In order to provide a complete understanding of how energetic processes internal and external to the solar system shape magnetospheres, atmospheres, and surfaces, in situ particle observations should include measurements of Solar Energetic Particles (SEP) and Galactic Cosmic Rays (GCR), along with solar wind and plasma. The potential temperature stability, tolerance to high radiation environments, and low noise characteristics expected in SiC-based detectors can have advantages over the state-of-the-art silicon detectors. These advantages will allow the detectors to be deployed in small compact systems on a variety of platforms, enabling compact structures for small satellite platforms with improved data quality.

Field and particle detectors↗

Developing Mars-Based Clinical Scenarios for an Earth Independent Medical Operations (EIMO) – Based Decision Support Service

As crewed missions move beyond Low-Earth Orbit, pre-mission planning cannot fully buy down the medical risks of exploration-class missions. Martian missions, where increased hazards exist, (such as long-duration spaceflight, surface-level EVA operations, and communications delays) will require a paradigm shift in the structure of a medical system. An Earth-Independent Medical Operations-based Medical System (EIMO-MS) will need to optimize four critical domains to help provide medical care: utilization of Pre-Mission Planning, augmentation of Acute and Prolonged Medical Decision Making, automated tracking of Resource Management, and assistance in Task Load Balance. The ideal EIMO-MS will be able to accomplish this goal by having an interactive, adaptable interface that will be able to provide real-time medical services. It must respond based on the level of crewmember training, medical situation, and available medical and non-medical resources. To showcase the capabilities and requirements of such a sophisticated automated MS, a series of clinical scenarios of escalating complexity were developed with clinical and systems engineering input. These scenarios describe in clinical detail what a theoretical future medical system, enhanced with multiple information streams (such as a medical database, an AI-based Decision Support System, real-time monitoring, enhanced in-situ laboratory imaging, etc.) can achieve in conjunction with a trained and experienced crew. Scenarios are comprised of: a context section including objectives and applicable spaceflight environment, a highlighted assumptions section, a clinical narrative section, and a systems engineering activity diagram demonstrating the integrated Medical System (MS). The “swim lanes” of the activity diagram act as the logistical core of each scenario and show how the MS will interact with the crew, ground support, and other in-flight systems. The Design Reference Mission that is used for the scenarios is based on existing reference mission profiles [1] with a projected 30-sol stay on the Martian surface. Scenarios span the spectrum from planned evaluations, minor medical care, urgent care, surgical guidance, critical and expectant management, and behavioral health care. Mission complexity will exponentially increase during deep space and Mars exploration-class missions, and medical support for these missions will likewise need to increase in autonomy and adaptability. The integrated system that will support these missions will need to provide assistance in a variety of anticipated and unforeseen scenarios. These medical scenarios, guided by clinician input, are initial steps in crafting the requirements for an EIMO-based medical system. By working in a systems engineering framework, requirements and capabilities can be extracted and mapped while maintaining a clinical core.

Prashant Parmar↗

Optimal Communication Topology Construction and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach with no estimation feedback to sensors selection and communication network topology computation for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes maximum airspace coverage with minimal resources, minimum communication time and power consumption while guaranteeing the system observability and providing in-time high quality information to both stationary and mobile users. The developed algorithms use multi-objective optimization strategy taking into account trade-offs between conflicting objectives and are implemented using off-the-shelf computational tools. The algorithms are validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace and parameters of a notional wireless communication network.

Distributed sensing↗

Earth-Independent Medical Operations (EIMO) Concept of Operations

In contrast to the current crew health paradigm for low-Earth orbit and Lunar missions, which depends on real-time communication with Mission Control, deep-space exploration missions will require a significant shift in medical operations. This shift is driven by the constraints of operating at a considerable distance from Earth, such as resource limitations—lack of resupply, restricted mass, power, volume, and data—as well as communication delays and the inability to evacuate back to Earth during emergencies. To move toward a more self-reliant medical model, a strategy is needed to gradually increase space-based crew autonomy and reduce risks to mission success in the challenging environment of deep space. This transformative change, known as "Earth-Independent Medical Operations" (EIMO), explores the gradual transfer of medical care and decision-making from Earth-based support to space-based systems. The goal of this transition is to enhance astronaut health and performance while minimizing mission risks. EIMO requires the development of a medical system that integrates seamlessly with mission planning, vehicle and spacesuit design, and data architecture. This integration is crucial for building a robust medical infrastructure that not only safeguards astronaut well-being but also ensures overall mission success. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has revised the EIMO model-based Concept of Operations (ConOps) which outlines an initial vision for EIMO. The ConOps, which is built on the stakeholders’ need, system goals, and objectives (NGOs), presents an array of in-mission scenarios that span a wide range of medical conditions demonstrating the system’s capabilities from basic to complex events. Developed by a multidisciplinary team of systems engineers, scientists, and clinicians within ExMC, the ConOps revision includes two new scenarios(Barotrauma and Self-Medical Management and Behavioral Health and Chronic Medical Care), and implementation of findings from EIMO technical interchange meetings that focused on data and training. The envisioned EIMO Medical System (MS) operates as a system of systems, gathering data from various sources such as reference databases, real-time wearable sensors, point-of-care diagnostics, and environmental controls. The MS also incorporates advanced training tools to support autonomous medical care, assisting the Crew Medical Officer (CMO) during medical events where Ground Support is either unavailable or communication-delayed beyond practicality. Furthermore, MS functions and capabilities were decomposed from the scenarios to establish foundational requirements for EIMO and traced to the NASA Spaceflight Human-System Standard(NASA-STD-3001, Volumes 1 and 2). These traces were performed to gain insights on the alignment of EIMO requirements with the NASA standard. This work serves as an initial recommendation to increase crew autonomy gradually and safely for Mars missions and future deep-space exploration.

medical system↗

Independent Verification and Validation for Artemis I Ascent Integrated Flight Performance Simulation

The NASA Engineering and Safety Center (NESC) has performed independent model development to support cross-model verification for the Space Launch System (SLS) Program since 2012 which culminated, for Artemis I, in a postflight reconciliation analysis of the Artemis I ascent trajectory (validation). This post-flight analysis was completed by both the NESC and the SLS Program. Upon successful completion of the Artemis I mission, multiple preflight simulations of the nominal ascent trajectory were updated with Day of Launch (DOL) conditions and simulated results were compared to reconstructed flight data derived from telemetry measurements. Dispersed trajectories were also produced using a combination of DOL conditions and preflight uncertainties, which ideally should bound the Artemis I flight data. Finally, multibody dynamics were simulated for some of the separation events to support clearance analyses. This paper focuses on validating and understanding the accuracy of the models by comparing simulated results against the Artemis I flight data. In addition, discrepancies uncovered between simulations led to opportunities to investigate areas for potential model improvement to refine preflight simulations for future Artemis missions. Included in this paper is background on the flight performance simulation tools, the postflight analysis approach, and a comparison of simulation results against the Artemis I flight data. Simulated results were found to generally be in close agreement with each other and the Artemis I flight data.

Jacob Fleck↗

Dynamic Anomaly Response and Integrated Analysis (DARIA): A Fault Investigation Toolset Supporting Earth-Independent Operations in Future Crewed Mars Missions

NASA's Moon to Mars Objectives outline a strategic vision for human spaceflight culminating in crewed missions to Mars. A critical component of this objective is the development of systems that are capable of being Earth-Independent Operated (EIO). A key aspect of EIO is the ability to rapidly detect, diagnose, and respond to anomalies in crew-supporting habitat and connected systems. To address this, the Dynamic Anomaly Response and Integrated Analysis (DARIA) architecture has been developed. DARIA incorporates a network of compact, wireless sensing devices called the System for Telemetry Amalgamation of Multimodal PrognosticS (STAMPS) for increased state awareness of EIO habitats. Able to perform on-the-fly data acquisition, STAMPS are connected to integrated anomaly data dashboards for crew visualization. DARIA is designed to seamlessly integrate into various off-world environments, including the International Space Station, Lunar Gateway, Artemis Base Camp, and future Mars habitats. By leveraging Commercial Off-The-Shelf (COTS) hardware, the NASA Internet of Things (NASA IoT) framework, and EIO fault detection methods, DARIA provides a cost-effective and adaptable solution for anomaly detection and response in EIO habitats.

Diagnostics↗

Platform-independent method for computer aided schematic drawings

A CAD/CAM method is disclosed for a computer system to capture and interchange schematic drawing and associated design information. The schematic drawing and design information are stored in an extensible, platform-independent format.

97 MATHEMATICS AND COMPUTING↗