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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Highly Supercooled Riming and Unusual Triple-Frequency Radar Signatures Over McMurdo Station, Antarctica

Riming of ice crystals by supercooled water droplets is an efficient ice growth process, but its basic properties are still poorly known. While it has been shown to contribute significantly to surface precipitation at mid-latitudes, little is known about its occurrence at high latitudes. In Antarctica, two competing effects can influence the occurrence of riming: (i) the scarcity of supercooled liquid water clouds due to the extremely low tropospheric temperatures and (ii) the low aerosol concentration, which may lead to the formation of fewer and larger supercooled drops potentially resulting in an enhanced riming efficiency. In this work, by exploiting the deployment of an unprecedented number of multiwavelength remote sensing systems (including triple-frequency radar measurements) in West Antarctica, during the Atmospheric Radiation Measurements West Antarctic Radiation Experiment (AWARE) field campaign, we evaluate the riming incidence at McMurdo Station and find that riming occurs at much lower temperatures when compared to previous results in the mid-latitudes. This suggests the possible occurrence of a common atmospheric state over Antarctica that includes a rather stable atmosphere inhibiting turbulent mixing, and a high riming efficiency driven by large cloud droplets. We then focus on a peculiar case study featuring a persistent layer with a particularly pronounced riming signature in triple-frequency radar data but only a relatively modest amount of supercooled liquid water. In-depth analysis of the radar observations suggests that such signatures can only be explained by the combined effects of moderately rimed aggregates or similarly shaped florid polycrystals and a narrow particle size distribution (PSD). Simulations of this case study performed with a one-dimensional bin model indicate that similar triple-frequency radar observations can be reproduced when narrow PSDs are simulated. Such narrow PSDs can in turn be explained by two key factors: (i) the presence of a shallow homogeneous droplet or humidified aerosol freezing layer aloft seeding an underlying supercooled liquid layer, and (ii) the absence of turbulent mixing throughout a stable polar atmosphere that sustains narrow PSDs, as hydrometeors grow from the nucleation region aloft to ice particles of several millimeters in size, by vapor deposition and then riming.

Riming↗
NASA NTRS2018

Clockwork Axions in Cosmology. Is Chromonatural Inflation Chrononatural?

Many cosmological models rely on large couplings of axions to gauge fields. Examples include theories of magnetogenesis, inflation on a steep potential, chiral gravitational waves, and chromonatural inflation. Such theories require a mismatch between the axion field range and the mass scale appearing in the aFF~ coupling. This mismatch suggests an underlying monodromy, with the axion winding around its fundamental period a large number of times. We investigate the extent to which this integer can be explained as a product of smaller integers in a UV completion: in the parlance of our times, can the theory be “clockworked”? We argue that a clockwork construction producing a potential μ4cos(ajFa) for an axion of fundamental period Fa will obey the constraint μ < Fa. For a some applications, including chromonatural inflation with sub-Planckian field range, this constraint obstructs a clockwork UV completion. Alternative routes to a large coupling include fields of large charge (an approach limited by strong coupling) or kinetic mixing (requiring a lighter axion). Our results suggest that completions of axion cosmologies that explain the large parameter in the theory potentially alter the phenomenological predictions of the model.

Cosmology of Theories beyond the SM↗
NASA NTRS2022

Introducing and Evaluating the Climate Hazards Center IMERG with Stations (CHIMES) Timely Station-Enhanced Integrated Multisatellite Retrievals for Global Precipitation Measurement

As human exposure to hydroclimatic extremes increase and the number of in situ precipitation observations declines, precipitation estimates, such as those provided by the Integrated Multisatellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) mission, provide a critical source of information. Here, we present a new gauge-enhanced dataset [the Climate Hazards Center IMERG with Stations (CHIMES)] designed to support global crop and hydrologic modeling and monitoring. CHIMES enhances the IMERG Late Run product using an updated Climate Hazards Center (CHC) high-resolution climatology (CHPclim) and low-latency rain gauge observations. CHPclim differs from other products because it incorporates long-term averages of satellite precipitation, which increases CHPclim ’s fidelity in data-sparse areas with complex terrain. This fidelity translates into performance increases in unbiased IMERGlate data, which we refer to as CHIME. This is augmented with gauge observations to produce CHIMES. The CHC’s curated rain gauge archive contains valuable contributions from many countries. There are two versions of CHIMES: preliminary and final. The final product has more copious and better-curated station data. Every pentad and month, bias-adjusted IMERGlate fields are combined with gauge observations to create pentadal and monthly CHIMESprelim and CHIMESfinal. Comparisons with pentadal, high-quality gridded station data show that IMERG late performs well (r = 0.75), but has some systematic biases which can be reduced. Monthly cross-validation results indicate that unbiasing increases the variance explained from 50% to 63% and decreases the mean absolute error from 48 to 39 mm month −1. Gauge enhancement then increases the variance explained to 75%, reducing the mean absolute error to 27 mm month −1.

Chris C funk↗
NASA NTRS2021

Constraining particle acceleration in Sgr A? with simultaneous GRAVITY, Spitzer, NuSTAR, and Chandra observations

We report the time-resolved spectral analysis of a bright near-infrared and moderate X-ray flare of Sgr A⋆. We obtained light curves in the M, K, and H bands in the mid- and near-infrared and in the 2 − 8 keV and 2 − 70 keV bands in the X-ray. The observed spectral slope in the near-infrared band is νLν ∝ ν0.5 ± 0.2; the spectral slope observed in the X-ray band is νLν ∝ ν−0.7 ± 0.5. Using a fast numerical implementation of a synchrotron sphere with a constant radius, magnetic field, and electron density (i.e., a one-zone model), we tested various synchrotron and synchrotron self-Compton scenarios. The observed near-infrared brightness and X-ray faintness, together with the observed spectral slopes, pose challenges for all models explored. We rule out a scenario in which the near-infrared emission is synchrotron emission and the X-ray emission is synchrotron self-Compton. Two realizations of the one-zone model can explain the observed flare and its temporal correlation: one-zone model in which the near-infrared and X-ray luminosity are produced by synchrotron self-Compton and a model in which the luminosity stems from a cooled synchrotron spectrum. Both models can describe the mean spectral energy distribution (SED) and temporal evolution similarly well. In order to describe the mean SED, both models require specific values of the maximum Lorentz factor γmax, which differ by roughly two orders of magnitude. The synchrotron self-Compton model suggests that electrons are accelerated to γmax ∼ 500, while cooled synchrotron model requires acceleration up to γmax ∼ 5 × 104. The synchrotron self-Compton scenario requires electron densities of 1010 cm−3 that are much larger than typical ambient densities in the accretion flow. Furthermore, it requires a variation of the particle density that is inconsistent with the average mass-flow rate inferred from polarization measurements and can therefore only be realized in an extraordinary accretion event. In contrast, assuming a source size of 1 RS, the cooled synchrotron scenario can be realized with densities and magnetic fields comparable with the ambient accretion flow. For both models, the temporal evolution is regulated through the maximum acceleration factor γmax, implying that sustained particle acceleration is required to explain at least a part of the temporal evolution of the flare.

R. Abuter↗
NASA NTRSDate not supplied

Safe Space Conduct: NASA Best Practices Overview

While prevention of launch and on-orbit collisions has been an institutional concern of NASA for several decades (beginning with the Shuttle program), historically the paucity of spaceactors and deployed payloads made the conduct of such protection activities relatively straightforward. With the substantial increases in launched payloads over the last several years, collision avoidance operations have become substantially more complicated. At the same time, many operators are uncertain regarding what collision avoidance activities are appropriate to their missions. The lack of a space traffic management authority to articulate standards and guidelines for such conduct has only increased the confusion.In response to this situation, NASA has published a Spacecraft Conjunction Assessment and Collision Avoidance Handbook, which articulates and explains the launch and on-orbit collision avoidance best practices that the Agency has developed and is requiring of present and future NASA missions. Because the CA2 Handbook is a living document regularly updated to reflect best practices changes as the industry develops, feedback from both NASA missions and other users is continuously collected in order to issue CA2 Handbook updates.This talk will summarize and explain the collision avoidance best practices from the CA2Handbook, along with the key issues that drove the selection of those practices.

Conjunction Assessment↗
NASA NTRSDate not supplied

NASA Best Practices Overview

While prevention of launch and on-orbit collisions has been an institutional concern of NASA for several decades (beginning with the Shuttle program), historically the paucity of space actors and deployed payloads made the conduct of such protection activities relatively straightforward. With the substantial increases in launched payloads over the last several years, collision avoidance operations have become substantially more complicated. At the same time, many operators are uncertain regarding what collision avoidance activities are appropriate to their missions. The lack of a space traffic management authority to articulate standards and guidelines for such conduct has only increased the confusion. In response to this situation, NASA has published a Spacecraft Conjunction Assessment and Collision Avoidance Handbook, which articulates and explains the launch and on-orbit collision avoidance best practices that the Agency has developed and is requiring of present and future NASA missions. Because the CA2 Handbook is a living document regularly updated to reflect best practices changes as the industry develops, feedback from both NASA missions and other users is continuously collected in order to issue CA2 Handbook updates. This talk will summarize and explain the collision avoidance best practices from the CA2 Handbook, along with the key issues that drove the selection of those practices.

Conjunction Assessment↗
NASA NTRSDate not supplied

A Cold Wet Mars: A Testable Hypothesis for Ancient Mars Ocean Freezing Point Depression Via Low Molecular Weight Organics

Mars exhibits widespread evidence of surface water in the distant past, but global modeling has had difficulty producing climatological conditions conducive to a wet surface. The hypothesis discussed here examines a different way of approaching the problem rather than focusing on climate, instead an examination of the nature of the surface liquid itself. Previous work has largely assumed that martian surface water was a brine analogous to terrestrial ocean water, but recent discoveries suggest that significant amounts of light organic compounds may have been present via abiogenic native production of light organics on Mars [1]. Light organics such as methanol and formaldehyde have an approximate order-of-magnitude greater freezing point depression than brine, potentially lowering the freezing point of martian surface fluids sufficiently to remain liquid even if the mean surface temperature is below zero Centigrade. As Mars evolved and the surface transitioned to the strongly oxidized conditions seen today, the light organics would have oxidized to carbon dioxide and may be a constituent of the atmosphere today. Considerable work must be done to constrain the freezing points of Mars-relevant organic/water and organic/salt/water mixtures, but this investigation might explain the presence of surface fluid on a cold early Mars – a cold, wet Mars as opposed to a warm, wet Mars. Additionally, this approach may work in conjunction with climatological modeling to better describe early conditions conducive which adequately explain observations. This hypothesis can be tested by examination of ancient fluid inclusions (either in situ or via Mars Sample Return) such as those commonly found in halite, preserving samples of ancient martian surface fluid.

M D Fries↗
NASA NTRS2021

Soil Moisture–Atmosphere Feedbacks Dominate Land Carbon Uptake Variability

Year-to-year changes in carbon uptake by terrestrial ecosystems play an essential role in determining atmospheric carbon dioxide concentrations. It remains uncertain to what extent temperature and water availability can explain these variations at the global scale. Here we use factorial climate model simulations and show that variability in soil moisture drives 90% of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture–atmosphere feedbacks amplify temperature and humidity anomalies, and enhance the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate a dominant role of soil moisture which is not readily apparent in land surface model simulations and observational analyses. These findings highlight the need to account for feedbacks between soil and atmospheric dryness when estimating the carbon cycle’s response to climatic change globally, as well as when conducting field-scale investigations of the ecosystem response to droughts. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects which are controlled by soil moisture.

Atmospheric dynamics↗
NASA NTRS2015

Terrestrial Planet Formation Constrained By Mars and the Structure of the Asteroid Belt

Reproducing the large Earth/Mars mass ratio requires a strong mass depletion in solids within the protoplanetary disc between 1 and 3 au. The Grand Tack model invokes a specific migration history of the giant planets to remove most of the mass initially beyond 1 au and to dynamically excite the asteroid belt. However, one could also invoke a steep density gradient created by inward drift and pile-up of small particles induced by gas drag, as has been proposed to explain the formation of close-in super-Earths. Here we show that the asteroid belt’s orbital excitation provides a crucial constraint against this scenario for the Solar system. We performed a series of simulations of terrestrial planet formation and asteroid belt evolution starting from discs of planetesimals and planetary embryos with various radial density gradients and including Jupiter and Saturn on nearly circular and coplanar orbits. Discs with shallow density gradients reproduce the dynamical excitation of the asteroid belt by gravitational self-stirring but form Mars analogues significantly more massive than the real planet. In contrast, a disc with a surface density gradient proportional to r(exp −5.5) reproduces the Earth/Mars mass ratio but leaves the asteroid belt in a dynamical state that is far colder than the real belt. We conclude that no disc profile can simultaneously explain the structure of the terrestrial planets and asteroid belt. The asteroid belt must have been depleted and dynamically excited by a different mechanism such as, for instance, in the Grand Tack scenario.

Numerical methods↗
NASA NTRSDate not supplied

Analysis of CDC Bioreactor Internal Thermal Measurements and Sample Coupon Temperatures

The CDC Biofilm Reactor is an integral laboratory tool for the Environmental Control and Life Support Systems (ECLSS) biofilm formation and growth research program. Critical to this research is the need to adjust and maintain various surface temperatures of the coupons housed within the CDC Biofilm Reactor. The purpose of this study was to provide quantitative temperature gradient information when the CDC Biofilm Reactor was operating according to several process scenarios. Two primary process parameters were evaluated. For the first set of test parameters, the liquid level was maintained at 350 mL, with an inlet flowrate of 0.1 mL/min, 1 mL/min, 10 mL/min. The liquid was allowed to gravity drain out of the outlet spout. For the second set of test parameters, the liquid level within the reactor was maintained at 550 mL, with an inlet flow of 0.1 mL/min, 1 mL/min, 10 mL/min and draining intermittently controlled to 0.8 mL/min to maintain the 550 mL level. Due to the placement of the thermocouple in the reactor, a difference in temperature occurred between the coupon surfaces and target biofilm reactor temperature when operated according to the first set of test parameters. When the reactor was operated according to the second set of parameters, which resulted in the thermocouple being submerged, the temperature gradient was eliminated. The results demonstrated minimal temperature gradient between the top and bottom coupon surfaces for coupons placed in a single rod within the CDC Biofilm Reactor for both sets of test parameters evaluated. The collection of this information helped to explain previous ECLSS biofilm formation test runs, along with providing guidance on best operating practices for future ECLSS experiments. The placement of the thermocouple also helps to explain the challenge of achieving and maintaining bulk liquid temperatures when biofilm is grown according to the standardized test methods.

CDC Bioreactor↗
NASA NTRSDate not supplied

Temperature Sensing to Above 1500 °C Using Y 2 SiO 5 :Er Phosphor Thermometry

A transition from metallic to ceramic turbine components that can operate at higher turbine engine temperatures will push component surface temperatures from below 1200 °C into a 1300 to 1500 °C temperature range that is much more challenging for phosphor thermometry measurements. To address this challenge, Y 2 SiO 5 :Er was selected for its high temperature sensing performance by both luminescence lifetime and luminescence intensity ratio (LIR) methods as well as its thermochemical compatibility with the current generation of rare earth silicate environmental barrier coatings (EBCs) that are required to protect SiC/SiC ceramic composite components. Lifetime measurements that monitor the Er3+ 4S3/2→4I15/2 emission decay at 542 nm exhibited a slow decrease in decay time with temperature up to 1300° C, above which the decay decreased steeply to provide good temperature sensitivity in the 1300 to 1500 °C range (Fig. 1). LIR images were obtained where each pixel represented the ratio I488/I561 (I488 and I561 are the detected 488 nm 4F7/2→4I15/2 and the 561 nm 4S3/2→4I15/2 emission band intensities, respectively). Good temperature sensitivity (Fig. 2) and signal-to-background ratios were observed to above 1500 °C. Contrary to conventional guidance on selecting phosphors for high temperature sensing, the detected emission band intensities and decay times exhibited remarkably slow decreases with temperature up into the 1300 to 1500 °C range despite high phonon energies (>900 cm-1) that allow the energy gap between the 4S3/2 emitting reservoir level and the 4F9/2 level below it to be bridged by as few as three phonons. The benefits of utilizing a thermographic phosphor at very high temperatures that exhibits strong nonradiative multiphonon relaxation even at room temperature is explained by a competition between spontaneous and stimulated multiphonon emission, and the more temperature-sensitive decay time above 1300 °C is explained by a transition from high to low effective phonon energies.

temperature measurement↗
NASA NTRS2020

Galactic origin of relativistic bosons and XENON1T excess

We entertain the exotic possibility that dark matter (DM) decays or annihilations taking place in our galaxy may produce a flux of relativistic very weakly-coupled bosons, axions or dark photons. We show that there exist several upper bounds for this flux on Earth assuming generic minimal requirements for DM, such as a lifetime longer than the age of the Universe or an annihilation rate that leaves unaffected the background evolution during matter domination. These bounds do not depend on the identity or the couplings of the bosons. We then show that this new flux cannot be large enough to explain the recent XENON1T excess, while assuming that the bosons’ couplings to the Standard Model are consistent with all current experimental and observational constraints. We also discuss a possible caveat to these bounds and a route to explain the excess.

Jatan Buch↗
NASA NTRS2022

Trace Element Partitioning Between Olivine and Melt in Lunar Basalts

Mineral/melt partition coefficients have been widely used to provide insights into magmatic processes. Olivine is one of the most abundant and important minerals in the lunar mantle and mare basalts. Yet, no systematic olivine/melt partitioning data are available for lunar conditions. We report trace element partition data between host mineral olivine and its melt inclusions in lunar basalts. Equilibrium is evaluated using the Fe-Mg exchange coefficient, leading to the choice of melt inclusion-host olivine pairs in lunar basalts 12040, 12009, 15016, 15647, and 74235. Partition coefficients of 21 elements (Li, Mg, Al, Ca, Ti, V, Cr, Mn, Fe, Co, Y, Zr, Nb, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) were measured. Except for Li, V, and Cr, these elements show no significant difference in olivine-melt partitioning compared to the data for terrestrial samples. The partition coefficient of Li between olivine and melt in some lunar basalts with low Mg# (Mg# < 0.75 in olivine, or < ~0.5 in melt) is higher than published data for terrestrial * Corresponding author. Email address: youxue@umich.edu 2 samples, which is attributed to the dependence of DLi on Mg# and the lack of literature DLi data with low Mg#. The partition coefficient of V in lunar basalts is measured to be 0.17 to 0.74, significantly higher than that in terrestrial basalts (0.003 to 0.21), which can be explained by the lower oxygen fugacity in lunar basalts. The significantly higher DV can explain why V is less enriched in evolved lunar basalts than terrestrial basalts. The partition coefficient of Cr between olivine and basalt melt in the Moon is 0.11 to 0.62, which is lower than those in terrestrial settings by a factor of approximately 2. This is surprising because previous authors showed that Cr partition coefficient is independent of fO2. A quasi-thermodynamically based model is developed to correlate Cr partition coefficient to olivine and melt composition and fO2. The lower Cr partition coefficient between olivine and basalt in the Moon can lead to more Cr enrichment in the lunar magma ocean, as well as more Cr enrichment in mantle-derived basalts in the Moon. Hence, even though Cr is typically a compatible element in terrestrial basalts, it is moderately incompatible in primitive lunar basalts, with a similar degree of incompatibility as V based on partition coefficients in this work, as also evidenced by the relatively constant V/Cr ratio of 0.039 ± 0.011 in lunar basalts. The confirmation of constant V/Cr ratio is important for constraining concentrations of Cr (slightly volatile and siderophile) and V (slightly siderophile) in the bulk silicate Moon.

partition coefficients↗
NASA NTRSDate not supplied

Analysis of CDC Bioreactor Internal Thermal Measurements and Sample Coupon Temperatures

The Center for Disease Control and Prevention (CDC) bioreactor is an integral laboratory tool for the Environmental Control and Life Support Systems (ECLSS) biofilm formation and growth research program. Critical to this research is the need to adjust and maintain various surface temperatures of the coupons housed within the CDC Bioreactor. The purpose of this study was to provide quantitative temperature gradient information when the CDC Bioreactor was operating according to several process scenarios. Two primary process parameters were evaluated. For the first set of test parameters, the liquid level was maintained at 350 mL, with an inlet flowrate of 0.1 mL/min, 1 mL/min, 10 mL/min. The liquid was allowed to gravity drain out of the outlet spout. For the second set of test parameters, the liquid level within the reactor was maintained at 550 mL, with an inlet flow of 0.1 mL/min, 1 mL/min, 10 mL/min and draining intermittently controlled to 0.8 mL/min to maintain the 550 mL level. Due to the placement of the thermocouple in the reactor, a difference in temperature occurred between the coupon surfaces and target Bioreactor temperature when operated according to the first set of test parameters. When the reactor was operated according to the second set of parameters, which resulted in the thermocouple being submerged, the temperature gradient was eliminated. The results demonstrated minimal temperature gradient between the top and bottom coupon surfaces for coupons placed in a single rod within the CDC Bioreactor for both sets of test parameters evaluated. The collection of this information helped to explain previous ECLSS biofilm formation test runs, along with providing guidance on best operating practices for future ECLSS experiments. The placement of the thermocouple also helps to explain the challenge of achieving and maintaining bulk liquid temperatures when biofilm is grown according to the standardized test methods.

CDC Bioreactor↗
NASA NTRS2023

Quantifying the Energy Budget in the Solar Wind from 13.3 to 100 Solar Radii

A variety of energy sources, ranging from dynamic processes, such as magnetic reconnection and waves, to quasi steady terms, such as plasma pressure, may contribute to the acceleration of the solar wind. We utilize a combination of charged particle and magnetic field observations from the Parker Solar Probe (PSP) to attempt to quantify the steady-state contribution of the proton pressure, the electric potential, and the wave energy to the solar wind proton acceleration observed by PSP between 13.3 and ∼100 solar radii (R☉). The proton pressure provides a natural kinematic driver of the outflow. The ambipolar electric potential acts to couple the electron pressure to the protons, providing another definite proton acceleration term. Fluctuations and waves, while inherently dynamic, can act as an additional effective steady-state pressure term. To analyze the contributions of these terms, we utilize radial binning of single-point PSP measurements, as well as repeated crossings of the same stream at different distances on individual PSP orbits (i.e., fast radial scans). In agreement with previous work, we find that the electric potential contains sufficient energy to fully explain the acceleration of the slower wind streams. On the other hand, we find that the wave pressure plays an increasingly important role in the faster wind streams. The combination of these terms can explain the continuing acceleration of both slow and fast wind streams beyond 13.3 R☉.

J S Halekas↗
NASA NTRS2023

A Wind-Driven Snow Redistribution Module for Alpine3d V3.3.0: Adaptations Designed for Downscaling Ice Sheet Surface Mass Balance

Ice sheets gain mass via snow accumulation at the ice sheet surface, which is the primary component of surface mass balance. On the Antarctic ice sheet, winds redistribute snow resulting in surface mass balance that is variable in both space and time. Representing wind-driven snow redistribution processes in models is critical for local assessments of surface mass balance, repeat altimetry studies, and interpretation of ice core accumulation records. To this end, we have adapted Alpine3D, an existing distributed snow modeling framework, to downscale Antarctic surface mass balance to horizontal resolutions up to 1 km. In particular, we have introduced a new two-dimensional advection-based wind-driven snow redistribution module that is driven by an offline coupling between WindNinja, a wind downscaling model, and Alpine3D. We then show that large accumulation variability can be at least partially explained by terrain-induced wind speed variations which subsequently redistribute snow around rolling topography. By comparing Alpine3D to airborne-derived snow accumulation measurements within a testing domain over Pine Island Glacier in West Antarctica, we demonstrate that our Alpine3D downscaling approach improves surface mass balance estimates when compared to MERRA-2, a global atmospheric reanalysis which we use as atmospheric forcing. In particular, when compared to MERRA-2, Alpine3D reduces simulated surface mass balance root mean squared error by 23.4 mm w.e.yr−1 (13%) and increases variance explained by 24%. Despite these improvements, Alpine3D still underestimates observed accumulation variability, thus providing an opportunity for future model improvement.

Eric Keenan↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗