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NASA NTRSDate not supplied

Recommendations For Developing Space Suit Integrated Food Systems and Delivering Nutrition Before, During, and After Lunar Eva

INTRODUCTION Artemis missions will include a higher tempo and frequency of extravehicular activities (EVAs) than any previous space program. Because of the physical demands expected from the crew, future space suit designs are required to incorporate nutritional support to the astronauts during lunar surface EVAs lasting longer than 4 hours. The purpose of this project was to provide recommendations to aid the development of an in-suit system that can adequately, safely, and acceptably deliver nutrition to a crewmember while confined to a space suit during EVA. METHODS Physiological, logistical, and engineering aspects of potential in-suit nutrition approaches were assessed through literature reviews, assessments of commercial off the shelf (COTS) foods, suit volumetric modeling, and feedback from subject matter experts and crewmembers. Key driving factors in the development of in-suit nutrition requirements included how much and what type of nutrition should be included, what food formulations are appropriate and safe, what are inherent limitations of space suits, what are the potential risks to the crewmember in the suit, and what practices and preferences from astronauts should be considered. Design references were conceptualized and assessed for strengths and limitations as potential in-suit nutrition systems for surface EVA. RESULTS Acute exogenous energy demands vary greatly depending on activity intensity and duration, and partial energy replenishment (i.e., 60–80 kcal∙hr-1 of EVA, or 460–680 kcal for EVAs lasting up to 8 hours) during activities could improve performance, safety, and recovery. COTS foods capable of providing these energy requirements exist; however, no COTS foods have been identified that pass NASA flight standards for microbiological safety and stability. In-suit nutrition delivery design references that were considered included in-suit concepts for a prefilled drink bag, a hydratable drink bag, and a solid food stick. In addition, a helmet feed port concept was considered for use with drink bags external to the suit. Volumetric models of the in-suit drink bag concepts, based on xEMU dimensions, indicate challenges of fitting formulations > 200 ml (equating to approximately 200 kcal). Astronaut feedback on the four concepts indicated that despite some individual preferences for inclusion of solid foods and helmet port designs, the prefilled drink bag concept was the most preferred. A prefilled drink bag can only be used if food safety and stability can be ensured, possibly requiring advancements in food delivery hardware. CONCLUSION The ability to meet the increased need for nutrition during surface EVAs through provision of nutrients in the suited configuration would benefit overall crew health, performance, and morale, and thus increase the likelihood of mission success. It is recommended that in-suit nutrition capabilities provide at least 400–600 kcal within the suit during EVAs lasting > 4 hours and that suit designs include a dedicated volume for food grade nutrition systems. The developed food system should either allow for 1) installation of prefilled (sealed sterile) liquid nutrition in the suit and provide a mechanism to break the seal at the time that consumption is desired or 2) demonstrate that the unsealed food product shelf life allows for safe consumption after at least 12 hours of EVA.

E L Dillon↗

NASA NTRSDate not supplied

Recommendations for Developing Space Suit Integrated Food Systems and Delivering Nutrition Before, During, and After Lunar EVA

space suit↗

NASA NTRS2015

Lander Technologies

Since 2006 NASA has been formulating robotic missions to the lunar surface through programs and projects like the Robotic Lunar Exploration Program, Lunar Precursor Robotic Program, and International Lunar Network. All of these were led by NASA Marshall Space Flight Center (MSFC). Due to funding shortfalls, the lunar missions associated with these efforts, the designs, were not completed. From 2010 to 2013, the Robotic Lunar Lander Development Activity was funded by the Science Mission Directorate (SMD) to develop technologies that would enable and enhance robotic lunar surface missions at lower costs. In 2013, a requirements-driven, low-cost robotic lunar lander concept was developed for the Resource Prospector Mission. Beginning in 2014, The Advanced Exploration Systems funded the lander team and established the MSFC, Johnson Space Center, Applied Physics Laboratory, and the Jet Propulsion Laboratory team with MSFC leading the project. The lander concept to place a 300-kg rover on the lunar surface has been described in the New Technology Report Case Number MFS-33238-1. A low-cost lander concept for placing a robotic payload on the lunar surface is shown in figures 1 and 2. The NASA lander team has developed several lander concepts using common hardware and software to allow the lander to be configured for a specific mission need. In addition, the team began to transition lander expertise to United States (U.S.) industry to encourage the commercialization of space, specifically the lunar surface. The Lunar Cargo Transportation and Landing by Soft Touchdown (CATALYST) initiative was started and the NASA lander team listed above is partnering with three competitively selected U.S. companies (Astrobotic, Masten Space Systems, and Moon Express) to develop, test, and operate their lunar landers.

Chavers, Greg↗

NASA NTRSDate not supplied

Exploring Innovative Methods for Earth Science Communication Through NASA’s Earth Information Center

Environmental challenges stemming from unprecedented changes in our planet have increased the need to communicate our understanding of Earth as a connected system. In June 2023, NASA unveiled the Earth Information Center (EIC), part of NASA’s Earth Action Strategy aimed at amplifying NASA’s Earth science impact by engaging decision-makers beyond the scientific community. Existing in both physical and virtual space, the EIC provides critical information on how the planet is changing and affecting livelihoods across the globe. For over fifty years, NASA has utilized the unique vantage point space offers to monitor Earth in collaboration with Federal partners. Through an expanding fleet of Earth observing satellites and sensors, NASA informs local to global decision making within nine thematic areas: agriculture, biodiversity, disasters, greenhouse gases, health and air quality, sea level rise and coastal impacts, sustainable energy, water resources, and wildfires. Visitors to the inaugural location of the EIC at NASA Headquarters in Washington D.C., can interact with Earth observation data and models through innovative exhibits and storytelling. Designed by an interdisciplinary team, the EIC is designed for multiple modality learning to reach a wide base of end-users. Data driven visualizations, near real-time information, and curated stories highlight the applications of Earth observations to address environmental challenges. Complementary exhibits and immersive storytelling allow visitors to physically step inside environmental data and connect with information on an emotional level. Taken together, the collective EIC provides scientists and non-scientists alike with the ability to see our home planet as NASA sees it, as a system of systems, while delivering easily accessible information to those who need it most.

Earth Information Center↗

NASA NTRS1982

Space environment and lunar surface processes, 2

The top few millimeters of a surface exposed to space represents a physically and chemically active zone with properties different from those of a surface in the environment of a planetary atmosphere. To meet the need or a quantitative synthesis of the various processes contributing to the evolution of surfaces of the Moon, Mercury, the asteroids, and similar bodies, (exposure to solar wind, solar flare particles, galactic cosmic rays, heating from solar radiation, and meteoroid bombardment), the MESS 2 computer program was developed. This program differs from earlier work in that the surface processes are broken down as a function of size scale and treated in three dimensions with good resolution on each scale. The results obtained apply to the development of soil near the surface and is based on lunar conditions. Parameters can be adjusted to describe asteroid regoliths and other space-related bodies.

Comstock, G. M.↗

NASA NTRS2017

Detection of DNA Damage by Space Radiation in Human Fibroblasts Flown on the International Space Station

Space radiation consists of energetic charged particles of varying charges and energies. Exposure of astronauts to space radiation on future long duration missions to Mars, or missions back to the Moon, is expected to result in deleterious consequences such as cancer and comprised central nervous system (CNS) functions. Space radiation can also cause mutation in microorganisms, and potentially influence the evolution of life in space. Measurement of the space radiation environment has been conducted since the very beginning of the space program. Compared to the quantification of the space radiation environment using physical detectors, reports on the direct measurement of biological consequences of space radiation exposure have been limited, due primarily to the low dose and low dose rate nature of the environment. Most of the biological assays fail to detect the radiation effects at acute doses that are lower than 5 centiSieverts. In a recent study, we flew cultured confluent human fibroblasts in mostly G1 phase of the cell cycle to the International Space Station (ISS). The cells were fixed in space after arriving on the ISS for 3 and 14 days, respectively. The fixed cells were later returned to the ground and subsequently stained with the gamma-H2AX (Histone family, member X) antibody that are commonly used as a marker for DNA damage, particularly DNA double strand breaks, induced by both low-and high-linear energy transfer radiation. In our present study, the gamma-H2AX (Histone family, member X) foci were captured with a laser confocal microscope. To confirm that some large track-like foci were from space radiation exposure, we also exposed, on the ground, the same type of cells to both low-and high-linear energy transfer protons, and high-linear energy transfer Fe ions. In addition, we exposed the cells to low dose rate gamma rays, in order to rule out the possibility that the large track-like foci can be induced by chronic low-linear energy transfer radiation.

Lu, Tao↗

DOE OSTI2024

AstroCLIP: a cross-modal foundation model for galaxies

ABSTRACT We present AstroCLIP, a single, versatile model that can embed both galaxy images and spectra into a shared, physically meaningful latent space. These embeddings can then be used – without any model fine-tuning – for a variety of downstream tasks including (1) accurate in-modality and cross-modality semantic similarity search, (2) photometric redshift estimation, (3) galaxy property estimation from both images and spectra, and (4) morphology classification. Our approach to implementing AstroCLIP consists of two parts. First, we embed galaxy images and spectra separately by pre-training separate transformer-based image and spectrum encoders in self-supervised settings. We then align the encoders using a contrastive loss. We apply our method to spectra from the Dark Energy Spectroscopic Instrument and images from its corresponding Legacy Imaging Survey. Overall, we find remarkable performance on all downstream tasks, even relative to supervised baselines. For example, for a task like photometric redshift prediction, we find similar performance to a specifically trained ResNet18, and for additional tasks like physical property estimation (stellar mass, age, metallicity, and specific-star-formation rate), we beat this supervised baseline by 19 per cent in terms of R2. We also compare our results with a state-of-the-art self-supervised single-modal model for galaxy images, and find that our approach outperforms this benchmark by roughly a factor of two on photometric redshift estimation and physical property prediction in terms of R2, while remaining roughly in-line in terms of morphology classification. Ultimately, our approach represents the first cross-modal self-supervised model for galaxies, and the first self-supervised transformer-based architectures for galaxy images and spectra.

Parker, Liam (ORCID:0009000749521674)↗

DOE OSTI2020

The structural information filtered features (SIFF) potential: Maximizing information stored in machine-learning descriptors for materials prediction

Machine learning inspired potentials continue to improve the ability for predicting structures of materials. However, many challenges still exist, particularly when calculating structures of disordered systems. These challenges are primarily due to the rapidly increasing dimensionality of the feature-vector space which in most machine-learning algorithms is dependent on the size of the structure. In this article, we present a feature-engineered approach that establishes a set of principles for representing potentials of physical structures (crystals, molecules, and clusters) in a feature space rather than a physically motivated space. Our goal in this work is to define guiding principles that optimize information storage of the physical parameters within the feature representations. In this manner, we focus on keeping the dimensionality of the feature space independent of the number of atoms in the structure. Our Structural Information Filtered Features (SIFF) potential represents structures by utilizing a feature vector of low-correlated descriptors, which correspondingly maximizes information within the descriptor. We present results of our SIFF potential on datasets composed of disordered (carbon and carbon–oxygen) clusters, molecules with C 7 O 2 H 2 stoichiometry in the GDB9-14B dataset, and crystal structures of the form (Al x Ga y In z ) 2 O 3 as proposed in the NOMAD Kaggle competition. Our potential's performance is at least comparable, sometimes significantly more accurate, and often more efficient than other well-known machine-learning potentials for structure prediction. However, primarily, we offer a different perspective on how researchers should consider opportunities in maximizing information storage for features.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Fast-ion physics in SPARC

Potential loss of energetic ions including alphas and radio-frequency tail ions due to classical orbit effects and magnetohydrodynamic instabilities (MHD) are central physics issues in the design and experimental physics programme of the SPARC tokamak. The expected loss of fusion alpha power due to ripple-induced transport is computed for the SPARC tokamak design by the ASCOT and SPIRAL orbit-simulation codes, to assess the expected surface heating of plasma-facing components. We find good agreement between the ASCOT and SPIRAL simulation results not only in integrated quantities (fraction of alpha power loss) but also in the spatial, temporal and pitch-angle dependence of the losses. If the toroidal field (TF) coils are well-aligned, the SPARC edge ripple is small (0.15–0.30 %), the computed ripple-induced alpha power loss is small ( ~0.25% ) and the corresponding peak surface power density is acceptable ( 244 kW m -2 ). However, the ripple and ripple-induced losses increase strongly if the TF coils are assumed to suffer increasing magnitudes of misalignment. Surface heat loads may become problematic if the TF coil misalignment approaches the centimetre level. Ripple-induced losses of the energetic ion tail driven by ion cyclotron range of frequency (ICRF) heating are not expected to generate significant wall or limiter heating in the nominal SPARC plasma scenario. Because the expected classical fast-ion losses are small, SPARC will be able to observe and study fast-ion redistribution due to MHD including sawteeth and Alfvén eigenmodes (AEs). SPARC's parameter space for AE physics even at moderate Q is shown to reasonably overlap that of the demonstration power plant ARC (Sorbom et al., Fusion Engng Des., vol. 100, 2015, p. 378), and thus measurements of AE mode amplitude, spectrum and associated fast-ion transport in SPARC would provide relevant guidance about AE behaviour expected in ARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Diagnostic-free onboard battery health assessment

Diverse usage patterns induce complex and variable aging behaviors in lithiumion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are often used to untangle the battery’s current state of health from prior complex aging patterns. However, these same diagnostic cycles alter the battery’s degradation trajectory, are time-intensive, and cannot be practically performed in onboard applications. Here, in this work, we leverage portions of operational measurements in combination with an interpretable machine learning model to enable rapid, onboard battery health diagnostics and prognostics without offline diagnostic testing and the requirement of historical data. We integrate mechanistic constraints within an encoder-decoder architecture to extract electrode states in a physically interpretable latent space and enable improved reconstruction of the degradation path. The health diagnosis model framework can be flexibly applied across diverse application interests with slight fine-tuning.

battery aging reconstruction↗

DOE OSTI2024

Physics-Informed Active Learning With Simultaneous Weak-Form Latent Space Dynamics Identification

The parametric greedy latent space dynamics identification (gLaSDI) framework has demonstrated promising potential for accurate and efficient modeling of high-dimensional nonlinear physical systems. However, it remains challenging to handle noisy data. Here, to enhance robustness against noise, we incorporate the weak-form estimation of nonlinear dynamics (WENDy) into gLaSDI. In the proposed weak-form gLaSDI (WgLaSDI) framework, an autoencoder and WENDy are trained simultaneously to discover intrinsic nonlinear latent-space dynamics of high-dimensional data. Compared with the standard sparse identification of nonlinear dynamics (SINDy) employed in gLaSDI, WENDy enables variance reduction and robust latent space discovery, therefore leading to more accurate and efficient reduced-order modeling. Furthermore, the greedy physics-informed active learning in WgLaSDI enables adaptive sampling of optimal training data on the fly for enhanced modeling accuracy. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including viscous and inviscid Burgers' equations, time-dependent radial advection, and the Vlasov equation for plasma physics. With data that contains 5%–10% Gaussian white noise, WgLaSDI outperforms gLaSDI by orders of magnitude, achieving 1%–7% relative errors. Compared with the high-fidelity models, WgLaSDI achieves 121 to 1779x speed-up.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2016

Biospecimen Retrieval from NASA's Rodent Research-1: Maximizing Science Return from Flight Missions

Rodent Research (RR)-1 was conducted to validate flight hardware, operations, and science capabilities that were developed to support long duration missions on the International Space Station. After 37 days in microgravity twenty mice were euthanized and frozen on orbit. Upon return to Earth the carcasses were dissected and yielded 32 different types of tissues from each mouse and over 3200 tissue aliquots. Many tissues were distributed to the Space Life and Physical Sciences (SLPS) Biospecimen Sharing Program (BSP) Principal Investigators (PIs) through the Ames Life Science Data Archive (ALSDA). A second round of dissections was performed to collect additional tissues from the remaining carcasses thawed for a second time for additional BSP PIs. Tissues retrieved included vaginal walls, aorta, pelvis, brown adipose tissue, tail, spine and forearms. Although the analyses are still in progress, some of the PIs have reported that the quality of the tissues was acceptable for their study. In a separate experiment we tested the RNA quality of the tissues that were dissected from frozen carcasses that were subjected to euthanasia, freezing, first and second thaw dissections. Timelines simulated the on-orbit RR-1 procedures to assess the quality of the tissues retrieved from the second thaw dissections. We analyzed the RIN values of select tissues including kidney, brain, white adipose tissue (WAT) and brown adipose tissue (BAT). Overall the RIN values from the second thaw were lower compared to those from the first by about a half unit; however, the tissues yielded RNA that are acceptable quality for some quantitative gene expression assays. Interestingly, RIN values of brain tissues were 8.4+/-0.6 and 7.9+/-0.7 from first and second round dissections, respectively (n5). Kidney and WAT yielded RIN values less than 8 but they can still be used for qPCR. BAT yielded higher quality RNA (8.2+/-0.5) than WAT (5.2+/-20.9), possibly due to the high fat content. Together, these data show that select tissues can be utilized for gene expression studies even if they are retrieved from carcasses that were subjected to at least two freezing and thawing processes; this further expands science return from valuable and infrequent rodent experiments in space.

rodents↗

NASA NTRS2016

Biospecimen Retrieval from NASA's Rodent Research-1: Maximizing Science Return from Flight Missions

Rodent Research (RR)-1 was conducted to validate flight hardware, operations, and science capabilities that were developed to support long duration missions on the International Space Station. After 37 days in microgravity twenty mice were euthanized and frozen on orbit. Upon return to Earth the carcasses were dissected and yielded 32 different types of tissues from each mouse and over 3200 tissue aliquots. Many tissues were distributed to the Space Life and Physical Sciences (SLPS) Biospecimen Sharing Program (BSP) Principal Investigators (PIs) through the Ames Life Science Data Archive (ALSDA). A second round of dissections was performed to collect additional tissues from the remaining carcasses thawed for a second time for additional BSP PIs. Tissues retrieved included vaginal walls, aorta, pelvis, brown adipose tissue, tail, spine and forearms. Although the analyses are still in progress, some of the PIs have reported that the quality of the tissues was acceptable for their study. In a separate experiment we tested the RNA quality of the tissues that were dissected from frozen carcasses that were subjected to euthanasia, freezing, first and second thaw dissections. Timelines simulated the on-orbit RR-1 procedures to assess the quality of the tissues retrieved from the second thaw dissections. We analyzed the RIN values of select tissues including kidney, brain, white adipose tissue (WAT) and brown adipose tissue (BAT). Overall the RIN values from the second thaw were lower compared to those from the first by about a half unit; however, the tissues yielded RNA that are acceptable quality for some quantitative gene expression assays. Interestingly, RIN values of brain tissues were 8.4+/-0.6 and 7.9+/-0.7 from first and second round dissections, respectively (n=5). Kidney and WAT yielded RIN values less than 8 but they can still be used for qPCR. BAT yielded higher quality RNA (8.2+/-0.5) than WAT (5.22+/-0.9), possibly due to the high fat content. Together, these data show that select tissues can be utilized for gene expression studies even if they are retrieved from carcasses that were subjected to at least two freezing and thawing processes; this further expands science return from valuable and infrequent rodent experiments in space.

rodent↗

DOE OSTI2022

Crystallography of hyperbolic lattices

Hyperbolic lattices are a revolutionary platform for tabletop simulations of holography and quantum physics in curved space and facilitate efficient quantum error correcting codes. Their underlying geometry is non-Euclidean, and the absence of Bloch's theorem precludes the straightforward application of the often indispensable energy band theory to study model Hamiltonians on hyperbolic lattices. Motivated by recent insights into hyperbolic band theory, we initiate a crystallography of hyperbolic lattices. Here we show that many hyperbolic lattices feature a hidden crystal structure characterized by unit cells, hyperbolic Bravais lattices, and associated symmetry groups. Using the mathematical framework of higher-genus Riemann surfaces and Fuchsian groups, we derive a list of example hyperbolic {p,q} lattices and their hyperbolic Bravais lattices, including five infinite families and several graphs relevant for experiments in circuit quantum electrodynamics and topolectrical circuits. This dramatically simplifies the computation of energy spectra of tight-binding Hamiltonians on hyperbolic lattices, from exact diagonalization on the graph to solving a finite set of equations in terms of irreducible representations. The significance of this achievement needs to be compared to the all-important role played by conventional Euclidean crystallography in the study of solids. We exemplify the high potential of this approach by constructing and diagonalizing finite-dimensional Bloch wave Hamiltonians.

2-dimensional systems↗

NASA NTRS1982

Idealized dynamic grid computation of physical systems

The construction and utility of an idealized computational space for finite-difference computation of physical systems are considered. All computations are performed in tau space, which at any instant represents the dynamic grid of a subject physical system appropriately stretched into a uniform, orthogonal grid. A strain field model of physical system is described, including the sample computation of strain density fields. Dynamic grid generation using invariant-mapping is addressed, and the tau computational space is considered, including a grid dynamism constraint, a grid orthogonality constraint, and a grid smoothness constraint. The detailed tau computational space method is presented and illustrated with two sample problems.

Anyiwo, J. C.↗

DOE OSTI2025

Testing gravitational physics by combining DESI DR1 and weak lensing datasets using the E_G estimator

The action of gravitational physics across space-time creates observable signatures in the behaviour of light and matter. We perform combined-probe studies using data from the Baryon Oscillation Spectroscopic Survey (BOSS) and Dark Energy Spectroscopic Instrument survey Data Release 1 (DESI-DR1), in combination with three existing weak lensing surveys, the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper Suprime-Cam Survey (HSC), to test and constrain General Relativity (GR) in the context of the standard model of cosmology (LCDM). We focus on measuring the gravitational estimator statistic, E_G, which describes the relative amplitudes of weak gravitational lensing and galaxy velocities induced by a common set of overdensities. By comparing our amplitude measurements with their predicted scale- and redshift-dependence within the GR+LCDM model, we demonstrate that our results are consistent with the predictions of the Planck cosmology. The redshift span of the DESI dataset allows us to perform these E_G measurements at the highest redshifts achieved to date, z ~ 1.

cosmology↗

DOE OSTI2026

Infinite matrix product states for (1 + 1)-dimensional gauge theories

We present a matrix product operator construction that allows us to represent the lattice Hamiltonians of (abelian or non-abelian) gauge theories in a local and manifestly translation-invariant form. In particular, we use symmetric matrix product states and introduce link-enhanced matrix product operators (LEMPOs) that can act on both the physical and virtual spaces of the matrix product states. This construction allows us to study Hamiltonian lattice gauge theories on infinite lattices. As examples, we show how to implement this method to study the massless and massive one-flavor Schwinger model and adjoint QCD 2 .

confinement↗

DOE OSTI2023

Effective field theories as Lagrange spaces

We present a formulation of scalar effective field theories in terms of the geometry of Lagrange spaces. The horizontal geometry of the Lagrange space generalizes the Riemannian geometry on the scalar field manifold, inducing a broad class of affine connections that can be used to covariantly express and simplify tree-level scattering amplitudes. Meanwhile, the vertical geometry of the Lagrange space characterizes the physical validity of the effective field theory, as a torsion component comprises strictly higher-point Wilson coefficients. Imposing analyticity, unitarity, and symmetry on the theory then constrains the signs and sizes of derivatives of the torsion component, implying that physical theories correspond to a special class of vertical geometry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗