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At least 253 records · Page 14

Effects of A 33-Ion Sequential Beam Galactic Cosmic Ray Analog on Male Mouse Behavior and Evaluation of CDDO-EA as A Radiation Countermeasure

In long-term spaceflight, astronauts will face unique cognitive loads and social challenges which will be complicated by communication delays with Earth. It is important to understand the central nervous system (CNS) effects of deep spaceflight and the associated unavoidable exposure to galactic cosmic radiation (GCR). Rodent studies show single- or simple-particle combination exposure alters CNS endpoints, including hippocampal-dependent behavior. An even better Earth-based simulation of GCR is now available, consisting of a 33-beam (33-GCR) exposure. However, the effect of whole-body 33-GCR exposure on rodent behavior is unknown, and no 33-GCR CNS countermeasures have been tested. Here astronaut-age-equivalent (6mo-old) C57BL/6J male mice were exposed to 33-GCR (75cGy, a Mars mission dose). Pre-/during/post-Sham or 33-GCR exposure, mice received a diet containing a ‘vehicle’ formulation alone or with the antioxidant/anti-inflammatory compound CDDO-EA as a potential countermeasure. Behavioral testing beginning 4mo post-irradiation suggested radiation and diet did not affect measures of exploration/anxiety-like behaviors (open field, elevated plus maze) or recognition of a novel object. However, in 3-Chamber Social Interaction (3-CSI), CDDO-EA/33-GCR mice failed to spend more time exploring a holder containing a novel mouse vs. a novel object (empty holder), suggesting sociability deficits. Also, Vehicle/33-GCR and CDDO-EA/Sham mice failed to discriminate between a novel stranger vs. familiarized stranger mouse, suggesting blunted preference for social novelty. CDDO-EA given pre-/ during/post-irradiation did not attenuate the 33-GCR-induced blunting of preference for social novelty. Future elucidation of the mechanisms underlying 33-GCR-induced blunting of preference for social novelty will improve risk analysis for astronauts which may in-turn improve countermeasures.

Space radiation↗

Imaging-Based Human Physiology Research and Innovation in Early Spaceflight: Polaris Dawn Mission

Objectives - Physiological data - Early inflight period historically unobtainable - Spacefaring population becoming more diverse - Many spaceflight changes still poorly understood, risks unmitigated - Private spaceflight offers more rapid access to higher n - Autonomous procedures - Communication delays and outages - Transition to new training paradigms - Terrestrial application (remote medicine, DOD) - Leverage new hardware and software - Concepts extend beyond medical realm (medical ultrasound as a use case)

A. Sargsyan↗

Risk Trade-Space Analysis for Safe Human Expeditions to Mars

We assessed the integrated safety, health, and performance risk to crews on long-duration missions, specifically to Mars. Using a systems approach rather than one focused on individual countermeasures, we examined the trade space around several such risks to identify high-potential risk mitigation strategies and characterize aspects of Mars mission architectures that could lower aggregated risk. Current Mars Design Reference missions would require durations well over two years and would increase crew exposure to radiation and microgravity well beyond ISS levels, likely resulting in significantly reduced performance beyond our current capability to mitigate that could jeopardize mission success. A “fast Mars transit” round-trip mission concept was studied using an innovative flight dynamics approach to quantify the minimum total mission energy required for a Mars transit with total mission duration less than 400 days. This approach holds promise for sending humans to Mars and returning them safely with acceptable, potentially mitigatable, exposure to microgravity and radiation using current or near-term technologies. The fast transit concept would also result in fewer time-driven vehicle failures and enable sustainable deployment of humans and infrastructure to Mars on a regular cadence, allowing steady exploration and colonization of Mars. Finally, we conclude that reliance on the Low Earth Orbit (LEO) mission operations paradigm – i.e., one of near-complete real-time dependence on experts at Mission Control to manage the combined state of the mission, vehicle, and crew – is high risk given the communication delays and limited resupply of any Mars mission, and this risk is not eliminated by the shorter missions durations of fast transit scenarios. Based on historical trends, it is highly likely that the crew will face a high-consequence problem of uncertain origin during Mars transit when ground support will be greatly reduced. While it may be possible to reduce anomaly rates through improved reliability analysis and testing, and to reduce anomaly impacts through added robustness, such mitigations address only known failure modes and known uncertainties. Therefore, a radical shift in the Human-Systems Integration Architecture (HSIA) that defines the operational paradigm, systems design, and human-systems interactions is required to improve the risk posture to an acceptable level regardless of mission duration.

Mars↗

Compliant Behaviors for Supervised and Autonomous Robotic Operations

The demands of traditional industrial robotics differ significantly from those of remote, supervised operations in hostile environments, such as operations in space. While industry requires robots that can perform repetitive tasks with precision and speed, the space environment needs robots to cope with uncertainties, dynamics, and communication delays or interruptions, similar to human astronauts. These demands make a well-suited application for compliant robotics and behavior-based programming. Pose Target Wrench Limiting (PTWL) is a compliant behavior paradigm developed specifically to meet these demands. PTWL controls a robot by moving a virtual attractor to a target pose. The attractor applies virtual forces, based on stiffness and damping presets, to an underlying admittance controller. Guided by virtual forces, the robot will follow the attractor until safety conditions are violated or success criteria are met. PTWL was tested on a variety of quasi-static and dynamic tasks that may be useful for future space operations. Results demonstrate that PTWL is a powerful tool. It makes teleoperation easy and safe for a wide range of quasi-static tasks. It also facilitates the creation of semi-autonomous state machines that can reliably complete complex tasks with minimal human intervention.

Joseph D. Cressman↗

Establishing Trust in NASA’s Artemis Campaign Computer-Human Interface (CHI) Implementation

The NASA Artemis program will return humans to the Moon. This time, with the help of commercial and international partners, the program's objective is a permanent moon base. The moon base infrastructure, including an orbiting moon station and moon surface assets, will be developed for astronauts to stay for the long haul to learn to live and work on another planet in preparation for an eventual Humans-to-Mars mission. As the roundtrip communication delays increase in deep space exploration, the crew will need more onboard systems autonomy and functionality to maintain and control the vehicle or habitat. These mission constraints will change the current Earth-based spacecraft to ground control support approach that will demand more safe, efficient, and effective Computer-Human Interface (CHI) control. For Artemis, CHI is defined as the elements that the crew interfaces with: audio, video, lighting, and crew controls subsystems. Understanding how CHI will need to evolve to support deep space missions will be critical for the Artemis program--especially crew controls, which is the focus of this paper. How does NASA ensure crew controls are reliable enough to control complex systems and prevent a catastrophic event due to human error--especially when the astronauts could be physiologically and/or psychologically impaired? NASA's approach to mitigating catastrophic hazards in human spaceflight system development such as crew controls, is through a holistic system engineering and Human System Integration methodology that focuses on incorporating NASA's Human-Rating Requirements-that ensures human performance characteristics to control/safely recover the crew from hazardous situations within the human interface design are considered. This paper discusses, at a high level, CHI for the Artemis program. Next, a discussion of what it means to human-rate a space system crew controls and how trust in the human-computer interface begins with the NASA human rating requirements. Finally, a discussion on how systems engineering and the human system integration process ensures that crew control implementation incorporates the NASA human-rating requirements.

artemis↗

Facilitating Crew-Computer Collaboration During Mixed-Initiative Space Mission Planning

As NASA looks toward longer duration missions, there will inevitably be a stronger emphasis on crew autonomy, particularly in the domains of mission planning. Ensuring that astronauts, while subject to lengthy periods of communication delay with Earth-based mission support personnel, are able to independently adapt their schedules to rapidly changing environments is a critical aspect of deep-space exploration. This task will likely require the assistance of computer support systems, as the task of mission planning is complex and currently requires dedicated console operators. A mixed-initiative approach can help alleviate some of the more workload-heavy aspects of planning by offloading the intricate task of constraint management to a computer, while still allowing the crew member to maintain overall control of the plan. Playbook is a mission planning tool that has been developed specifically to support this type of mixed-initiative scheduling. This paper examines: 1) the operational evidence of the challenges and viability of autonomous crew planning, and 2) the novel scheduling capabilities in Playbook that are meant to address those findings.

human-computer interaction↗

Compliant Robotic Behaviors for Satellite Servicing

The demands of traditional industrial robotics differ significantly from those of space robotics. While industry requires robots that can perform repetitive tasks with precision and speed, the space environment needs robots to cope with uncertainties, dynamics, and communication delays or interruptions, similar to human astronauts. These demands make a well-suited application for compliant robotics and behavior-based programming. Pose Target Wrench Limiting (PTWL) is a compliant behavior paradigm developed specifically to meet these demands. PTWL controls a robot by moving a virtual attractor to a target pose. The attractor applies virtual forces, based on stiffness and damping presets, to an underlying admittance controller. Guided by virtual forces, the robot will follow the attractor until safety conditions are violated or success criteria are met. We tested PTWL on a variety of quasi-static tasks that may be useful for future space operations. Our results demonstrate that PTWL is an extremely powerful tool. It makes teleoperation easy and safe for a wide range of quasi-static tasks. It also facilitates the creation of semi-autonomous state machines that can reliably complete complex tasks with minimal human intervention.

Compliance↗

Overview of Crew Operations for Transit to Mars

Crewed Mars missions are estimated to be 700-1,200 days in length which is two to three times longer than any continuous human spaceflight mission to date. When architecting a Mars mission there are numerous resources that must be considered, evaluated, and planned for, including—but not limited to—mass, cost, performance, and risk. Crew time is a limited resource that will need to be appropriately allocated during future Mars missions. NASA’s “Moon to Mars Objectives” specifically recognizes as Recurring Tenets the need to return crews safely to Earth while mitigating adverse impacts to crew health and maximizing crew time available for science and engineering activities within planned mission durations. Crew operations and the crew time allocation for a Mars missions will likely be different than current operational planning aboard the ISS due to communication delays, crew health and performance needs, transportation system needs, potential vehicle dormancy, and mass ejection. Crew will need to operate much more Earth independently and potentially be responsible for more operations since traditional Earth ground support will be delayed. Incidents requiring immediate crew action will therefore either be the responsibility of the crew or an automated feature of the transit vehicle. This paper discusses the operational challenges of a Mars transit mission and the associated activities that will need to take place during each operational phase of transit to and from Mars.

Crew Time↗

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

BACKGROUND The medical capabilities necessary for long-duration exploration missions (LDEMs) will differ tremendously from those currently available to crew medical officers (CMOs) on the International Space Station (ISS). Ground support will be more challenging due to distance-related communication delays and data transmission, and resource utilization must be optimized given limited ability for resupply. Clinical decision support systems (CDSSs) can help mitigate these limitations. The recent launch of generative artificial intelligence (AI) tools based upon large language models (LLM) support the creation of a smart assistant for onboard triage, diagnosis, and guided treatment of medical conditions during these missions. The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool can help predict which clinical problems and outcomes are likely to occur for a design reference mission (DRM) and assist Medical Operations and systems engineering teams in creating a medical system that may optimally mitigate the predicted risks. The purpose of this study was to identify AI tools currently available or in development for the assistive diagnosis and care of medical conditions predicted for an extended duration Lunar mission. METHODS The 119 medical conditions currently built into the IMPACT suite were categorized into systems, and these diagnoses were used as keywords for our literature search. Using PubMed and Google Scholar, we performed a literature survey of AI tools applicable to these conditions. Article inclusion criteria included publication between the years 2017-2023, as the sentinel paper discussing the “selective attention” driving ChatGPT and other generative transformer models was published in June 2017. Where applicable, we reviewed only the top 1000 research articles (based on relevance) for each of the keywords/phrases. AI tools whose training sets were exclusive to a pediatric patient population were excluded. We also excluded any medical diagnostic tools (such as CT, MRI, mass spectrometry) or procedures (such as endoscopy, surgery) that are unlikely to be available during LDEMs due to mass and volume constraints, CMO knowledge, skills, and abilities, and/or inherent procedural risks. RESULTS Our survey highlighted several AI-driven tools for the triage, diagnosis, and management of those medical conditions highlighted by IMPACT. Selected publications for each medical condition were then screened for inclusion within ten systems-based categories including: general diagnostic tools (25), tools to diagnose and manage respiratory (40), dermatologic (34), neurologic (28), auditory and vestibular (30), ophthalmic (34), musculoskeletal (104), infection-associated (92), and gynecologic (19) conditions, as well as tools that could be deployed in the setting of trauma and emergency (34). CONCLUSIONS Numerous AI-driven tools were highlighted within this literature survey, ranging from chatbot assistants that triage knee pain to vision transformer models for diagnosis of ophthalmic conditions using ocular surface images captured with a mobile phone. Remaining challenges include optimizing connectivity and integration of existing and developing systems into the vehicles or habitats. Notably, findings from this survey could help guide the initial design of an all-encompassing, onboard medical AI assistant for use during future LDEMs.

R A Lacinski↗

Overview of Crew Operations for Transit to Mars

Crewed Mars missions are estimated to be 700-1,200 days in length which is two to three times longer than any continuous human spaceflight mission to date. When architecting a Mars mission there are numerous resources that must be considered, evaluated, and planned for, including—but not limited to—mass, cost, performance, and risk. Crew time is a limited resource that will need to be appropriately allocated during future Mars missions. NASA’s “Moon to Mars Objectives” specifically recognizes as Recurring Tenets the need to return crews safely to Earth while mitigating adverse impacts to crew health and maximizing crew time available for science and engineering activities within planned mission durations. Crew operations and the crew time allocation for a Mars missions will likely be different than current operational planning aboard the ISS due to communication delays, crew health and performance needs, transportation system needs, potential vehicle dormancy, and mass ejection. Crew will need to operate much more Earth independently and potentially be responsible for more operations since traditional Earth ground support will be delayed. Incidents requiring immediate crew action will therefore either be the responsibility of the crew or an automated feature of the transit vehicle. This paper discusses the operational challenges of a Mars transit mission and the associated activities that will need to take place during each operational phase of transit to and from Mars.

Crew Time↗

Preliminary Medical Risk Estimates and Clinical Capability Needs for Artemis IV

BACKGROUND Human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in- mission medical care. Compared with the ISS, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to: a) quantitatively estimate human system risk attributable to medical conditions, a process known as Probabilistic Risk Analysis, and b) use these estimates to inform medical system design. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a PRA and medical trade space analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 improves upon and will soon replace NASA’s existing tool, the Integrated Medical Model, with: a novel evidence base baselined to exploration environments; an expanded list of 119 medical conditions; a significant increase in the number of medical resources that can be utilized and in the flexibility of their use; and the modelling of time lost performing mission-specific tasks due to medical conditions. METHODOLOGY: This abstract will present IMPACT estimates of medical system risk and clinical capability needs for the Artemis IV mission. Artemis IV is currently scheduled for 2026 and will visit the Gateway space station in lunar orbit prior to the second lunar landing of the Artemis program. The baseline Artemis IV mission that was modeled was 28 days in duration with phases including Orion outbound, 4 days on the Gateway space station in lunar orbit, 2 crew on the surface of the Moon for approximately one week, an additional 5 days on Gateway, and then return to Earth. This baseline was compared to two alternative 34-day design reference missions (DRMs) that shifted the lunar sortie earlier or later in the mission profile. Assumptions included 2 female and 2 male crew and a notional medical system mass of 25 kg. Medical system risk estimates include loss of crew life (LOCL), consideration of medical evacuation (known as return to definitive care – RTDC), and an estimate of crew time lost due to medical conditions (Task Time Lost – TTL). The presentation will also describe the medical conditions that are the greatest drivers of risk as well as the clinical capabilities and resources that have the largest effect on risk. RESULTS: All three DRMs had very low probability of LOCL from medical conditions, primarily due to short duration. RTDC was also similar across the DRMs. In contrast, TTL was higher in the early lunar sortie DRM due to earlier occurrence of EVA-related medical conditions. Taken as a whole, there was no clinically significant difference in medical risk across the three missions. Results for clinical capabilities and an example medical equipment list will be discussed but were similar across DRMs.

D Hilmers↗

Medical Risk Estimates and Clinical Capability Needs for A Long Duration Artemis Mission

BACKGROUND Human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. Compared with the ISS, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to: a) quantitatively estimate human system risk attributable to medical conditions, a process known as Probabilistic Risk Analysis, and b) use these estimates to inform medical system design. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a PRA and medical trade space analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 improves upon and will soon replace NASA’s existing tool, the Integrated Medical Model, with: a novel evidence base baselined to exploration environments; an expanded list of 119 medical conditions; a significant increase in the number of medical resources that can be utilized and in the flexibility of their use; and the modelling of time lost performing mission-specific tasks due to medical conditions. DISCUSSION: This abstract will present IMPACT estimates of medical system risk and clinical capability needs for an extended duration Artemis mission of approximately 9 months, with phases including outbound transit, 3 months on the Lunar Gateway space station, 3 months on the Lunar surface with EVAs, 3 months on Gateway (simulating the return phase of a Mars mission), and transit back to Earth. Medical system risk estimates include loss of crew life (LOCL), consideration of medical evacuation (known as return to definitive care – RTDC), and an estimate of crew time lost due to medical conditions (Task Time Lost – TTL). The presentation will also describe the medical conditions that are the greatest drivers of risk as well as the clinical capabilities and resources that have the largest effect on risk.

W Thompson↗

The Exploration Crew Health and Performance System of the Future - A Shared Mental Model

The challenges involved in vehicle/habitat design and operation for long-duration deep space missions are complex, and the needs of a human crew must be considered in the context of all the system trades required to enable such missions. An exploration Crew Health and Performance (CHP) system complements all the other vehicle/habitat systems to achieve one specific and critical endpoint – ensuring that the astronauts can perform the job that they were sent into space to do. This includes accounting for all aspects of the physiological, psychological, medical, and environmental realities that the human crew must face in deep space. Along with this system complexity comes the additional need for increased autonomy of the crew due to the immense distance from Earth. The design of future systems must respect the real human capabilities and limitations within the context of a mission to the Moon or Mars. The NASA Moon to Mars Objectives document outlines the need for advanced CHP system designs: • Develop systems that monitor and maintain crew health and performance throughout all mission phases, including during communication delays to Earth, and in an environment that does not allow emergency evacuation or terrestrial medical assistance. • Evaluate and validate progressively Earth-independent crew health & performance systems and operations with mission durations representative of Mars-class missions. • Validate readiness of systems and operations to support crew health and performance for the initial human Mars exploration campaign. This presentation will outline the initial work that Exploration Medical Capability is leading on the development of a prototype design for an exploration Crew Health and Performance (CHP) system for future NASA human deep space long-duration missions. This effort will require commitment from all stakeholders to a shared mental model of what a future exploration CHP system should look like, one that will address the needs, goals, and objectives of the Agency and help to ensure mission success in deep space.

K R Lehnhardt↗

Assessing the Number of Crew for Mars Against Trade Space Parameters

Missions to Mars will differ from all previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner given the long communication delays on Mars missions. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk in that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, the crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise in the Mission Control Central (MCC) team on which NASA has come to rely. We present a framework for trade space analysis along with results from human-performance models developed in IMPRINT. We discuss the implications of model results on the trade space for number of crew for missions to Mars. This work was funded by the NASA Engineering and Safety Center (NESC) with support from NASA’s Human Research Program (HRP).

Donna Dempsey↗

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↗

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗

Quantifying Risk to Improve Medical System Design for Long Duration Artemis Missions: A Demonstration of NASA's IMPACT Tradespace Analysis Tool

BACKGROUND NASA’s human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. A greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and constraints on the evacuation of ill or injured crew. Mass, volume, and power will be limited while higher demands will be placed on the crews to manage medical events. NASA’s Moon to Mars exploration strategy outlines increasingly complex Artemis missions both in terms of duration and operations. In these more challenging deep space missions, it is important to quantitatively estimate the human system risk attributable to medical conditions and use these estimates to advance medical system design. METHODS IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a probabilistic risk assessment (PRA) and tradespace analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 includes a novel evidence library baselined to exploration environments; an expanded list of 119 medical conditions; a large increase in the number of medical resources and the flexibility of their use; and the ability for rapid and iterative analysis. Medical system risk estimates include loss of crew life, consideration of the need for return to definitive care (medical evacuation), and an estimate of crew time affected due to medical conditions. A notional long duration lunar orbit and lunar surface design reference mission (DRM) was chosen with a 4-astronaut crew to mimic a foundational exploration Artemis mission. The DRM profile includes outbound transit on Orion, Gateway space station rendezvous in lunar orbit, 6 months on the Lunar surface with extravehicular activity (EVA), return rendezvous with Gateway, and transit back to Earth. RESULTS/DISCUSSION: Overall, IMPACT successfully quantified medical risk and derived an optimal medical system to support crew on a long duration lunar mission. In this DRM, the calculated loss of crew life from a medical event was 0.008 events per mission, risk of potential need for evacuation was 0.30 events per mission, and cumulative crew time affected by medical conditions was 103 days. The medical conditions that most contributed to medical risk were decompression sickness, trauma, and respiratory failure. The conditions that had the largest effects on crew performance included musculoskeletal injuries and lunar dust exposure. The IMPACT-generated medical system included resources that target the most common and highest risk conditions and performed as expected. This demonstrates the value of the IMPACT tool in medical system design for human exploration spaceflight missions.

Arian Anderson↗

Information Systems for Crew-Led Operations Beyond Low-Earth Orbit

On past and present human space missions, the management of vehicle health and status has primarily been executed from Earth. Missions such as Apollo, Space Shuttle, and ISS have relied on a safety net of ground-based experts with access to real-time telemetry data, broad and deep systems expertise, and powerful analytical and computing capabilities. The ground team monitors and manages the vehicle’s health in real-time and responds quickly to critical situations and malfunctions. Ground operators also provide real-time oversight and verbal guidance to flight crew members, especially during complex procedure execution and high-risk activities like extra-vehicular activities. However, this operational paradigm, in place for 60 years, will not transfer to long duration exploration missions beyond low Earth orbit (LEO). Lunar and deep-space crewed missions will encounter delayed communications that prohibit real-time operational and medical support. Additionally, there will be infrequent resupply and a diminished capacity to evacuate or rescue crew members. A small crew must operate independently, managing the vehicle’s state, responding to time-critical events, and executing complex procedures, all without the safety net of real-time support.

data representation↗