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NASA Crew Health & Performance Capability Development for Exploration: 2022 to 2023 Overview

NASA has identified twenty-eight specific risks to human health and performance that must be adequately understood and addressed to enable future crewed missions to Mars. These risks are due to radiation, reduced gravity, distance from earth, isolation and confinement, and the effects of living within artificially created and controlled life support environments. Research and technology development is required to better understand these risks and to inform, develop, and test technologies and strategies to mitigate these risks. NASA’s System Capability Leads coordinate across the agency to continually identify, prioritize, and monitor technology investments in support of these future missions. This paper describes progress over the past year in strategic planning, coordination, and technology development related to crew health and performance capabilities that are needed for future Mars missions. Technology maturation progress and future plans are described in the following capability areas: crew health countermeasures; spacesuit physiology and performance; food and nutrition; and exploration medical capabilities.

Andrew F J Abercromby↗

Progressively Enabling Earth Independent Medical Operations (EIMO)

This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.

Jay Lemery↗

Progressively Enabling Earth Independent Medical Operations (EIMO)

This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.

John Lemery↗

Bionutrients: Microbial Production of on-Demand Nutrients on the International Space Station

Providing adequate nutrition to crew members is essential as deep-space missions cannot rely on consistent Earth-based resupply. The current NASA pre-packaged food system is designed for low-earth-orbit missions with a stated shelf-life of two years and notable vitamin degradation over time. One strategy to mitigate nutrient loss is to implement bioregenerative food sources to supplement the pre-packaged food system. The BioNutrients project is designed to provide targeted production of short shelf-life nutrients in a single-use production pack. BioNutrients-1 includes two strains of edible yeast that have been genetically engineered to produce carotenoids, β-carotene, and zeaxanthin. This five-year mission on the International Space Station (ISS), launched in 2019, tests the long-term storage and nutrient production of the microorganisms of interest. Additional microorganisms are also stored in stasis packs to determine the effects of long-duration storage on the ISS. These organisms may be useful for production of fermented foods, pharmaceuticals, or biomanufacturing processes. Improving on the BioNutrients-1 project, BioNutrients-2 has optimized the production pack hardware by reducing the overall mass and volume of the system. Furthermore, BioNutrients-2 has expanded the projects scope by investigating novel products and microbial food sources. BioNutrients-2 is a six-month mission, launched in 2022, which tests production of fresh foods such as yogurt and kefir. The BioNutrients missions seek to provide advances for in-space biomanufacturing by addressing safe and reliable production of high-value nutrients and on-demand foods for future exploration efforts.

BioNutrients↗

Impact of Canadian Wildfires on Mid Atlantic’s Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗

Analyzing the Impact of Canadian Wildfires on Air Quality in the U.S. Mid-Atlantic: with Data and Tools from NASA’s Atmospheric Sciences Data Center

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗

Harnessing CPF Hyperspectral Radiances to Homogenize Earth Observing Systems

Homogenization across Earth observing systems is essential for ensuring consistency in geophysical retrievals over time and enabling the construction of long-term climate records. As the first SI Traceable Satellite (SITSat) for the reflected solar, the CLARREO Pathfinder (CPF) will provide high-accuracy spectrally resolved benchmark measurements of Earth-reflected solar radiation, serving as a standardized in-orbit reference for other reflected solar (RS) instruments. The CPF intercalibration team has developed a state-of-the-art method to intercalibrate the RS channels of the VIIRS instrument onboard the NOAA-20 satellite using CPF benchmark measurements, aiming for a methodology uncertainty of 0.3-0.6% (1-sigma). To achieve this stringent accuracy, the CPF team has devised strategies to mitigate the effects of spatial, spectral, polarization, and angular disparities between the intercalibration footprints of CPF and VIIRS. Despite nearly identical instrument designs, the three VIIRS instruments currently in operation onboard SNPP, NOAA-20, and NOAA-21 platforms exhibit systematic radiometric biases up to 8%. Although each VIIRS sensor’s calibration is independent and traceable to standards maintained by NIST, there is significant concern within the community about which VIIRS sensor most accurately represents the absolute radiometric scale. The precise intercalibration between CPF and NOAA-20 VIIRS will reveal the absolute radiometric accuracy of VIIRS. This accuracy can then be extended to other RS sensors, including MODIS and other VIIRS sensors, via vicarious methods. The 3-nm spectral sampling of CPF measurements will enable users to quantify scene-dependent spectral biases between sensors, thereby aiding in establishing both spectral and radiometric homogenization across these platforms. The CPF mission overview, along with details of its intercalibration capabilities and homogenization approaches, will be discussed at the meeting.

Raj Bhatt↗

Severe droughts reduce river navigability and isolate communities in the Brazilian Amazon

The Amazon basin is experiencing severe droughts that are expected to worsen with climate change. Riverine communities are especially vulnerable to these extreme events. This study investigates the experiences of Brazilian Amazonian communities during droughts occurring from 2000-2020. We assess the distribution of settlements at risk of prolonged isolation during extreme low-water periods, along with impacts reported in digital news outlets. Using historic time series of river levels from 90 gauges, we look at how long droughts lasted in regions with reported impacts. Results indicate that the droughts in 2005, 2010, and 2016 were the most severe, with over an additional month of low water levels in those years. Such drought events routinely disrupt inland water transport and isolate local populations, limiting access to essential goods (food, fuel, medicine) and basic services (healthcare, education). Given this new reality, Amazon countries must develop long-term strategies for mitigation, adaptation, and disaster response.

Geography↗

Assessing the Influence of Decompression Sickness on Medical Risk for Artemis

As NASA begins to shift its focus from LEO missions to the Moon and beyond, our understanding of the risk associated with human spaceflight is challenged by mission profiles and objectives far different from preceding missions. For Artemis, one of these aspects is surface Extra Vehicular Activity (EVA) tempo, in which the crew will perform 3 to 4 surface EVA’s in quick succession. The crew health and performance risk associated with EVA Decompression Sickness (DCS) and its associated countermeasures, is an important consideration for Artemis missions given this new and unprecedented EVA frequency. Successfully completing Artemis mission objectives relies heavily on the crew being able to perform and complete these EVAs. This analysis quantifies how medical risk changes when accounting for the expected increase in DCS risk due to the increase in EVA frequency. If there is an occurrence of DCS during a mission, appropriate downtime needs to be accounted for. Treatment for DCS requires crewmember to stop the current EVA and return to the habitat. This impacts the current EVA the crew is performing, could potentially delay the next EVA, and increases the chance of the crewmember being unable to perform future EVAs. Capturing the downtime and impact of that downtime based on the number of DCS occurrences allows us to better understand how the risk associated with DCS affects the overall medical risk and completion of missions that have more frequent EVA tempo. There are preventative strategies and mitigation countermeasures to decrease the chance of DCS occurring such as different prebreathe protocols, variable suit pressure, and vehicle pressure settings. Modeling the medical risk with and without different DCS countermeasures enables quantitative comparisons of risk reduction associated with each DCS countermeasure. We present results on how these countermeasures affect medical risks and quantify changes in the medical kit contents with respect to the countermeasures implemented within Artemis-class missions.

Clara Gasiewski↗

Investigating Risks Due to Artemis EVA Tempo Via Probabilistic Risk Assessment

Spaceflight operations pose unique challenges to crew health, safety, and resource management. As space agencies and private companies continue to push the boundaries of human exploration, it is essential to understand the risks associated with Extravehicular Activities (EVAs) and develop strategies to mitigate them. The tempo at which EVAs are conducted – the total number and frequency of these activities – can have a profound impact on medical risks, resource consumption, and overall mission success. Probabilistic risk assessment (PRA) provides a powerful framework for evaluating complex systems and identifying potential hazards. Our work employs the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) [1] to simulate mission events, occurrence and treatment of medical conditions, and track the utilization of resources. Coupled with the Evidence Library [2], a medical evidence base for exploration-class missions developed by the Exploration Medical Capability within NASA’s Human Research Program, we can estimate these risks with increased fidelity and optimize medical kit contents to meet specific mission requirements. This presentation provides a detailed examination of how EVA tempo influences medical risk estimates for a lunar surface design reference mission. A comprehensive analysis is conducted to assess the additional mass and volume burden imposed on medical kits required to maintain adequate levels of risk mitigation. Furthermore, we estimate the distribution of the number of successful EVAs completed based on the level of task impairment imposed by medical events and flight rules related to specific medical events, such as decompression sickness.

Modeling↗

Strategies Toward Lunar Dust Adhesion Mitigation

Recently, the NASA Space Technology Mission Directorate solicited feedback to prioritize shortfalls, which were defined as technology areas needed to enable future exploration missions. Lunar dust mitigation emerged as a critical area and is cross-cutting with many of the highest ranked shortfalls with passive dust mitigation technologies being directly ranked in the top 50. Hazards associated with lunar dust are ubiquitous across all aspects of long duration lunar surface missions, whether crewed or robotic, due to the abrasive, electrostatically charged, and chemically reactive properties of lunar dust. Compounding the issue, lunar dust moves across the lunar surface due to levitation, twilight craters, and plume-surface interactions, which can result in particle velocities exceeding 1 km/h. To address lunar dust challenges, NASA is developing active and passive adhesion mitigation technologies to address specific mission needs, including electrodynamic dust screens, piezoelectric materials, biomimetic engineered surfaces, among many others. Additionally, abrasion-resistant materials are being evaluated for applications for use near landing sites and in surface manipulation and excavation equipment. These approaches, as well as test methodologies both in the laboratory and on the lunar surface to evaluate technology efficacy, will be described.

Dust Mitigation↗

Dynamic Recrystallization Model for Whisker and Hillock Growth

Tin (Sn) whiskers are not a recent development. Studies in the late 1930’s investigated thin filaments that grew spontaneously from Sn coatings used for the corrosion protection of electronic hardware. It was soon recognized that these Sn filaments,or whiskers, could create short circuits in the same electronic equipment. Figure 1a illustrates whisker growth in the hole of a printed circuit board having an immersion Sn surface finish. The engineering solution was to contaminate the Sn with > 3wt.% of lead (Pb). The result was that whisker growth was replaced with hillock formation (Fig. 1b) that posed a minimal reliability concernto electrical circuits. Today, Pb-containing finishes are being replaced with pure Sn coatings to meet environmental restrictions on Pb use. The same short-circuit concerns have been raised, once again, with respect to Sn whiskers. The present authors have taken the approach that, in order to develop more widely applicable, first-principles strategies to mitigate Sn whisker formation, it is necessary to understand the fundamental mechanism(s) and rate kinetics underlying their development. Numerous mechanisms have been proposed by other authors to describe whisker growth, including static recrystallization by Boguslavsky and Bush.

36 MATERIALS SCIENCE↗

Dissociation Mechanism of Processive Cellulases Explored Through Molecular Simulation

Cellulose is the most abundant biopolymer on the planet, with significant potential as a feedstock for bioderived products. In nature, fungi and bacteria secrete cellulases to hydrolyze cellulose into smaller carbohydrates for incorporation into their own metabolic processes. For effective biomass utilization at industrial scale, these cellulases are coupled together to produce a clean sugar stream. One such cellulase is Cel7A from Trichoderma reesei, which is used extensively in biotechnological applications. However, dissociation of Cel7A from a bound cellulose strand is rate-limiting, reducing catalytic efficiency and yields within industrial applications. To explore this unknown dissociation mechanism and devise potential enzyme engineering strategies to mitigate slow dissociation, we conduct Hamiltonian replica exchange molecular dynamics simulations. Two postulated dissociation mechanisms were tested ('dethreading' of the bound cellulose strand from the binding tunnel and 'clamshell'-like opening of the binding tunnel and recrystallization of the bound cellulose). For each mechanism, free energy profiles were determined together with estimated diffusion coefficients. The kinetics for both mechanisms were then estimated and compared against experimentally measured dissociation rates, which suggest that the dethreading mechanism ought to be preferred. These findings are further supported by dissociation rates measured on engineered mutants incapable of undergoing the clamshell mechanism.

09 BIOMASS FUELS↗

PAVE: An In Situ Framework for Scientific Visualization and Machine Learning Coupling

Machine learning (ML) has emerged as a tool for understanding data at scale. However, this new methodology comes at a cost because ML requires the use of even more HPC resources to generate ML algorithms. In addition to the compute resources required to develop ML algorithms, ML does not sidestep one of the biggest challenges on leading-edge HPC systems: the increasing gap between compute performance and I/O bandwidth. This has led to a strong push towards in situ, processing the data as it is generated, strategies to mitigate the I/O bottleneck. Unfortunately, there are no in situ frameworks dedicated to coupling scientific visualization and ML at scale to develop ML algorithms for scientific visualization. To address the ML and in situ visualization gap, we introduce PAVE. PAVE is an in situ framework which addresses the data management needs between visualisation and machine learning tasks. We demonstrate our framework with a case study that accelerates physically-based light rendering, path-tracing, through the use of a conditional Generative Adversarial neural Network (cGAN). PAVE couples the training over path-traced images resulting in a generative model able to produce scene renderings with accurate light transport and global illumination of a quality comparable to offline approaches in a more efficient manner.

Kim, Mark B.↗

Characterization of Annealing-Induced Phase Segregation in Composite Silicon Anodes for Li-ion Batteries

Silicon (Si) anodes present a promising alternative to graphite anodes for lithium-ion batteries (LIBs), as Si has a greater specific capacity. However, one major constraint is the volumetric change of Si during lithiation that results in an unstable solid-electrolyte interphase (SEI), so Si-containing electrodes require the use of various strategies to mitigate these effects and improve performance. One such solution is the use of Si nanoparticles (NPs) that maximize the surface area to volume ratio. Here, we discuss electrodes made with Si NPs treated with polyethylene oxide (PEO) (for improving dispersion during processing), conductive carbon NPs, and P84 polyimide binder which shows significant impacts of annealing treatment on improvements of active material utilization, first cycle efficiency, and capacity retention with extensive cycling . We used air-free argon ion polishing to create electrode cross sections and imaged through the electrode thickness using atomic force microscopy (AFM)-based nano-electrical characterization of scanning spreading resistance microscopy (SSRM), nano-mechanical characterizations of contact resonance and force volume (CR-FV), and scanning electron microscopy-based energy dispersive x-ray spectroscopy (SEM-EDS). Results show that the Si and conductive carbon segregate into phases with a distinctive carbon-rich banded morphology that surrounds the Si-rich phase during annealing. In pristine electrodes, the carbon- and SEI-rich bands exhibit a higher electronic conductivity and a lower elastic modulus than the Si active material phase. These structures, as well as distinct electronic and mechanical properties, remain during cycling, suggesting an improvement of electrical conduction pathways and a mechanical strain buffer for active Si material expansion during cycling. This phase separation may be a major factor in the improvement seen in electrochemical performance due to annealing. Additionally, our nm-scale and multi-mode characterizations provide a novel route for understanding and improving energy storage devices, which is advantageous due to the highly inhomogeneous of composite electrodes in nm-mm scales.

ENERGY STORAGE↗