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NASA NTRSDate not supplied

The BioSensor Instrument Beyond LEIA: a Versatile Platform for Lunar Biology

Introduction: The BioSensor is a deep-space-compatible automated microfluidic culturing instrument. While originally designed to measure the effects of deep space radiation on yeast growth for the BioSentinel mission, it has the potential to host a diverse range of life science experiments with single- and/or multi-celled organisms and can be adapted to interface with a diverse range of platforms in both crewed and uncrewed settings. It is therefore a leading candidate for hosting life sciences experimentation associated with a lunar surface habitat. BioSensor design: The function of the BioSensor is to monitor the growth and metabolic activity of samples in batch fluidic culture, without the need for crew involvement. The current configuration houses organisms in 16 wells within 16 microfluidic cards, accommodating a total of 256 samples, replicates, and controls. Each well has an optical system including three LEDs and a photodiode detector to measure absorbance at three wavelengths, enabling measurement of optical density, color change in dyes such as alamarBlue, and bioproduction of pigmented compounds. Organisms are loaded into fluidic wells and air-dried for storage during integration, launch, and transit, then activated by the introduction of culture medium from storage bags via manifolds that fill one card at a time. Temperature is controlled by individual card heaters, and timing of all activities (fluidics fills, optical measurements, temperatures) is directed by an experiment script. The self-contained BioSensor payload is roughly 4U in volume; with electrical/mechanical/thermal interface, e.g. for operation on ISS or a lunar lander, as well as a linear energy-transfer (LET) charged-particle radiation spectrometer, the entire system is closer to 6U. BioSentinel and LEIA: Flown on the ISS and in a deep-space free flyer for BioSentinel, the BioSensor has been modified for use in the LEIA mission, including improvements to reduce the sensitivity to lengthy launch delays. LEIA will monitor yeast growth in the radiation and reduced-gravity environment of the lunar surface no earlier than 2026, on a CLPS lander [4]. Changes include accommodating additional culture media and an additional LED color for a new biological assay (bioproduction of carotenoids-- dietary antioxidants), as well as modifications to the housing to allow late-load biology changeout and improved isolation between fluidics and electronics. Future prospects: Future work with the BioSensor, beyond LEIA, will include expanding the range and diversity of organisms and assays accommodated. Preliminary work has demonstrated the growth of Arabidopsis seedlings in BioSensor fluidic cards, including optical measurements of growth rate over time. Minor modifications could allow measurement of phenotypes related to photosynthetic capacity in both plants and cyanobacteria. The experimental capabilities of the BioSensor could be dramatically increased by introducing the capability for fluorescence measurements, and/or the design of novel biological assays using luminescence. The BioSensor can also be adapted for new platforms and experiment settings; in addition to free-flyer, ISS, and CLPS lander, a preliminary design concept has been developed for crewed deployment directly to the lunar surface. The instrument could be accommodated inside a lunar habitat, where its automated operation would make it an excellent candidate for experiments from fundamental investigations into the response of organisms to lunar surface conditions to applied-science purposes such as screening engineered strains of various organisms for bioproduction capability.

J A Lee↗

DOE OSTI2020

APOGEE Net: Improving the Derived Spectral Parameters for Young Stars through Deep Learning

Machine learning allows for efficient extraction of physical properties from stellar spectra that have been obtained by large surveys. The viability of machine-learning approaches has been demonstrated for spectra covering a variety of wavelengths and spectral resolutions, but most often for main-sequence (MS) or evolved stars, where reliable synthetic spectra provide labels and data for training. Spectral models of young stellar objects (YSOs) and low-mass MS stars are less well-matched to their empirical counterparts, however, posing barriers to previous approaches to classify spectra of such stars. In this work, we generate labels for YSOs and low-mass MS stars through their photometry. We then use these labels to train a deep convolutional neural network to predict logg, T {sub eff}, and Fe/H for stars with Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra in the DR14 data set. This “APOGEE Net” has produced reliable predictions of logg for YSOs, with uncertainties of within 0.1 dex and a good agreement with the structure indicated by pre-MS evolutionary tracks, and it correlates well with independently derived stellar radii. These values will be useful for studying pre-MS stellar populations to accurately diagnose membership and ages.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A synthetic Roman Space Telescope High-Latitude Time-Domain Survey: supernovae in the deep field

ABSTRACT NASA will launch the Nancy Grace Roman Space Telescope (hereafter Roman) in the second half of this decade, which will allow for a generation-defining measurement of dark energy through multiple probes, including Type Ia supernovae (SNe Ia). To improve decisions on survey strategy, we have created the first simulations of realistic Roman images that include artificial SNe Ia injected as point sources in the images. Our analysis combines work done on Roman simulations for weak gravitational lensing studies as well as catalogue-level simulations of SN Ia samples. We have created a time series of images over 2 yr containing ∼1050 SNe Ia, covering a 1 deg2 subarea of a planned 5 deg2 deep survey. We have released these images publicly for community use along with input catalogues of all injected sources. We create secondary products from these images by generating coadded images and demonstrating recovery of transient sources using image subtraction. We perform first-use analyses on these images in order to measure galaxy detection efficiency, point source detection efficiency, and host-galaxy association biases. The simulated images can be found here at https://roman.ipac.caltech.edu/sims/SN_Survey_Image_sim.html.

Astronomy & Astrophysics↗

DOE OSTI2020

A Roadmap for Reaching the Potential of Brain-Derived Computing

Neuromorphic computing is a critical future technology for the computing industry, but it has yet to achieve its promise and has struggled to establish a cohesive research community. A large part of the challenge is that full realization of the potential of brain inspiration requires advances in both device hardware, computing architectures, and algorithms. This simultaneous development across technology scales is unprecedented in the computing field. This article presents a strategy, framed by market and policy pressures, for moving past these current technological and cultural hurdles to realize its full impact across technology. Achieving the full potential of brain-derived algorithms as well as post-complementary metal-oxide-semiconductor (CMOS) scaling neuromorphic hardware requires appropriately balancing the near-term opportunities of deep learning applications with the long-term potential of less understood opportunities in neural computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

The velocity-dependent J -factor of the Milky Way halo: does what happens in the galactic bulge stay in the galactic bulge?

Here, we consider the angular distribution of the photon signal which could arise from velocity-dependent dark matter annihilation within the Galactic bulge. We find that, for the case of Sommerfeld-enhanced annihilation, dark matter annihilation within the bulge is dominated by slow speed particles which never leave the bulge, allowing one to find a simple analytic relationship between the dark matter profile within the Galactic bulge and the angular distribution. On the other hand, for the case p- or d-wave annihilation, we find that the small fraction of high-speed particles which can leave the bulge provide a significant, often dominant, contribution to dark matter annihilation within the bulge. For these scenarios, fully understanding dark matter annihilation deep within the Galactic bulge, and the angular distribution of the resulting photon signal, requires an understanding of the dark matter profile well outside the bulge. We consider the Galactic Center excess in light of these results, and find that an explanation of this excess in terms of p-wave annihilation would require the dark matter profile within the bulge to have a much steeper profile than usually considered, but with uncertainties related to the behavior of the profile outside the bulge.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Photometry and astrometry with JWST – III. A NIRCam-Gaia DR3 analysis of the open cluster NGC 2506

ABSTRACT In the third paper of this series aimed at developing the tools for analysing resolved stellar populations using the cameras on board of the James Webb Space Telescope (JWST), we present a detailed multiband study of the 2 Gyr Galactic open cluster NGC 2506. We employ public calibration data sets collected in multiple filters to: (i) derive improved effective Point Spread Functions (ePSFs) for 10 NIRCam filters; (ii) extract high-precision photometry and astrometry for stars in the cluster, approaching the main sequence (MS) lower mass of ∼0.1 M⊙; and (iii) take advantage of the synergy between JWST and Gaia DR3 to perform a comprehensive analysis of the cluster’s global and local properties. We derived a MS binary fraction of ∼57.5 per cent, extending the Gaia limit (∼0.8 M⊙) to lower masses (∼0.4 M⊙) with JWST. We conducted a study on the mass functions (MFs) of NGC 2506, mapping the mass segregation with Gaia data, and extending MFs to lower masses with the JWST field. We also combined information on the derived MFs to infer an estimate of the cluster present-day total mass. Lastly, we investigated the presence of white dwarfs (WDs) and identified a strong candidate. However, to firmly establish its cluster membership, as well as that of four other WD candidates and of the majority of faint low-mass MS stars, further JWST equally deep observations will be required. We make publicly available catalogues, atlases, and the improved ePSFs.

Nardiello, D. (ORCID:0000000311493659)↗

DOE OSTI2023

AEflow (Autoencoder fluid flow compression network) [SWR-22-29]

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

King, Ryan↗

DOE OSTI2020

Building high throughput permissioned blockchain fabrics: challenges and opportunities

Since the introduction of Bitcoin---the first widespread application driven by blockchains---the interest in the design of blockchain-based applications has increased tremendously. At the core of these applications are consensus protocols that securely replicate client requests among all replicas, even if some replicas are Byzantine faulty. Unfortunately, these consensus protocols typically have low throughput, and this lack of performance is often cited as the reason for the slow wider adoption of blockchain technology. Consequently, many works focus on designing more efficient consensus protocols to increase throughput of consensus. We believe that this focus on consensus protocols only explains part of the story. To investigate this belief, we raise a simple question: Can a well-crafted system using a classical consensus protocol outperform systems using modern protocols? In this tutorial, we answer this question by diving deep into the design of blockchain systems. Further, we take an in-depth look at the theory behind consensus, which can help users select the protocol that best-fits their requirements. Finally, we share our vision of high-throughput blockchain systems that operate at large scales.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Semisupervised Learning for Seismic Monitoring Applications

The impressive performance that deep neural networks demonstrate on a range of seismic monitoring tasks depends largely on the availability of event catalogs that have been manually curated over many years or decades. However, the quality, duration, and availability of seismic event catalogs vary significantly across the range of monitoring operations, regions, and objectives. Semisupervised learning (SSL) enables learning from both labeled and unlabeled data and provides a framework to leverage the abundance of unreviewed seismic data for training deep neural networks on a variety of target tasks. We apply two SSL algorithms (mean-teacher and virtual adversarial training) as well as a novel hybrid technique (exponential average adversarial training) to seismic event classification to examine how unlabeled data with SSL can enhance model performance. In general, we find that SSL can perform as well as supervised learning with fewer labels. We also observe in some scenarios that almost half of the benefits of SSL are the result of the meaningful regularization enforced through SSL techniques and may not be attributable to unlabeled data directly. Lastly, the benefits from unlabeled data scale with the difficulty of the predictive task when we evaluate the use of unlabeled data to characterize sources in new geographic regions. Finally, in geographic areas where supervised model performance is low, SSL significantly increases the accuracy of source-type classification using unlabeled data.

58 GEOSCIENCES↗

NASA NTRS1979

Autonomy in space navigation

The potential development of autonomous onboard navigation systems for future space missions is discussed. Motivations for autonomy in the near-earth satellite program and in deep-space navigation are examined, emphasizing lower mission-operation costs for the first, and reduction of ground-system complexity as well as encounter accuracy for the latter. Uses of navigation parameters by the Information Adaptive System, including sensor-pointing computation and image correction, are noted, as are the accuracy parameters of the NAVSTAR Global Positioning System. The role of autonomous onboard navigation in contact exploration of Neptune's and Uranus's satellites as well as in such extreme-high-velocity encounters as those with retrograde comets is investigated. The Automated Optical Navigation program is described

Jordan, J. F.↗

NASA NTRS1989

Far-infrared emission in the Rho Ophiuchi region - A comparison with molecular gas emission and visual extinction

The dust characteristics of a 40 arcmin x 40 arcmin section of the Rho Ophiuchi molecular clouds complex revealed by the IRAS satellite are compared with both molecular line and deep star count data for the region. The data reveal the cloud to be clearly visible at 12 and 25 microns, as well as at 60 and 100 microns. Modeling the infrared emission from the cloud as being due to two populations of dust grains, the short-wavelength emission is found not to reflect the internal structure of the molecular cloud. The 60 micron opacity determined using a single grain emission model correlates reasonably well with (C-13)O column density and visual extinction up to roughly 5 mag. The cloud edges appear to be heated by the interstellar radiation field. The far-infrared luminosity to mass ratio for the region is determined to be 0.9 solar luminosity/solar mass, a value much smaller than the average ratio for the inner Galaxy.

Jarrett, T. H.↗

NASA NTRS1997

Global Troposphere Experiment Project

For the Global Troposphere Experiment project Pacific Exploratory Measurements West B (PEM West B), we made determinations of sulfur dioxide (SO2) and dimethyl sulfide (DMS) using gas chromatography-mass spectrometry with isotopically labelled internal standards. This technique provides measurements with precision of 1 part-per-trillion by volume below 20 pptv and 1% above 20 pptv. Measurement of DMS and SO2 were performed with a time cycle of 5-6 minutes with intermittent zero checks. The detection limits were about 1 pptv for SO2 and 2 pptv for DMS. Over 700 measurements of each compound were made in flight. Volcanic impacts on the upper troposphere were again found as a result of deep convection in the tropics. Extensive emission of SO2 from the Pacific Rim land masses were primarily observed in the lower well-mixed part of the boundary layer but also in the upper part of the boundary layer. Analyses of the SO2 data with aerosol sulfate, beryllium-7, and lead-210 indicated that SO2, contributed to half or more of the observed total oxidized sulfur (SO2 plus aerosol sulfate) in free tropospheric air. Cloud processing and rain appeared to be responsible for lower SO2 levels between 3 and 8.5 km than above or below this region. During both phases of PEM-West, dimethyl sulfide did not appear to be a major source of sulfur dioxide in the upper free troposphere over the western Pacific Ocean. In 1991 the sources Of SO2 at high altitude appeared to be both anthropogenic and volcanic with an estimated 1% being solely from DMS. The primary difference for the increase in the DMS source was the very low concentration of SO2 at high altitude. In the midlatitude region near the Asian land masses, DMS in the mixed layer was lower than in the tropical region of the western Pacific. Convective cloud systems near volcanoes in the tropical convergence in the western Pacific troposphere were a major source of SO2 at high altitudes during PEM-West B. High levels of SO2 were observed in several instances with large number concentrations of ultrafine CN above 9 km in the tropical convergence zone. Conversion of SO2, by OH to SO3 and subsequently to sulfuric acid may have been enhanced by lightning-produced NO levels exceeding 1 part per billion. Coupling of strong convection and volcanic sources of SO2 apparently is an important source of new particle formation at high altitude in the tropical convergence zone.

Bandy, Alan R.↗

NASA NTRS2007

Entry, Descent, and Landing Operations Analysis for the Genesis Entry Capsule

On September 8, 2004, the Genesis spacecraft returned to Earth after spending 29 months about the sun-Earth libration point (L1) collecting solar wind particles. Four hours prior to Earth arrival, the sample return capsule containing the samples was released for entry and subsequent landing at the Utah Test and Training Range. This paper provides an overview of the entry, descent, and landing trajectory analysis that was performed during the mission operations phase leading up to final approach to Earth. The final orbit determination solution produced an inertial entry flight-path angle of -8.002 deg (which was the desired nominal value) with a 3-sigma error of +/-0.0274 deg (a third of the requirement). The operations effort accurately delivered the entry capsule to the desired landing site. The final landing location was 8.3 km from the target, and was well within the allowable landing area. Overall, the Earth approach operation procedures worked well and there were no issues (logistically or performance based) that arose. As a result, the process of targeting a capsule from deep space and accurately landing it on Earth was successfully demonstrated.

Desai, Prasun N.↗

NASA NTRSDate not supplied

Assessing the Feasibility of using PlanetScope Data for Air Quality Applications

Planet is a commercial company known for having one of the largest operational smallsat satellite constellations. This constellation comprises over 120 3U CubeSats called Doves (equipped with a sensor called PlanetScope), which combined, are able to image the entire Earth’s surface daily at a high 3-meter spatial resolution. With Planet data becoming more readily available to scientists due to NASA’s Commercial Smallsat Data Acquisition Program (CSDAP), this study investigates the feasibility of utilizing Planet data to conduct scientific analyses with an emphasis on air quality research. This study offers a comparison of PlanetScope data with MODIS over a variety of land cover types, as well as in response to varying PM2.5 conditions. It also investigates the feasibility of utilizing PlanetScope data for estimating PM2.5 concentrations using deep learning

Jeanne Le Roux↗

NASA NTRS2018

Autonomous Small Body Mapping and Spacecraft Navigation

Current methods for pose and shape estimation of small bodies, such as comets and asteroids, rely on extensive ground support and signiﬁcant use of radiometric measurements using the Deep Space Network. The Stereo-Photoclinometry (SPC) technique is currently used to provide detailed topological information about a small body as well as its absolute orientation and position. While this technique has produced very accurate estimates, the core algorithm cannot be run in real-time and requires a team of scientists on the ground who must communicate with the spacecraft in order to oversee SPC operations. Autonomous onboard navigation addresses these limitations by eliminating the need for human oversight. In this paper, we present an optimization-based estimation algorithm for navigation that allows the spacecraft to autonomously approach and maneuver around an unknown small body by mapping its geometric shape, estimating its orientation, and simultaneously determining the trajectory of the center of mass of the small body. We show the eﬀectiveness of the proposed algorithm using simulated data from a previous ﬂight mission to Comet 67P.

Bhaskaran, Shyamkumar↗

NASA NTRS2020

Evolution of the Preliminary Fault Management Architecture and Design for the Psyche Mission

The Psyche Mission presents the first opportunity toexplore the largest metal asteroid in the solar system, (16)Psyche, which is believed to be the exposed core of a largerplanetesimal that was stripped of its rocky mantle throughmultiple collisions during early solar system formation. Themission was selected in January 2017 for a 2022 launch as partof NASA’s Discovery Program and is uniquely enabled by theintegration of a Solar Electric Propulsion (SEP) Chassisdelivered by Maxar Space Solutions with JPL’s core deepspace avionics, flight software, and fault managementarchitectures. One of the key design tasks is the development ofa fault management system capable of being responsive to theunique elements of the combined JPL and Maxar spacecraftarchitecture. This new design leverages the strengths of eachorganization, with Maxar delivering its well-proven highvoltage power bus and low-thrust electric propulsionsubsystem from its GEO communications satellite product line,and JPL delivering its deep space mission expertise and thehardware and software most critical to deep space missiondesign. The development of a robust low-thrust mission andthe integration of design philosophies and hardware from twoorganizations is not without its challenges though.A key challenge in the development of the Psyche faultmanagement architecture and design is in the integration ofdesign philosophies and hardware from JPL and Maxar. Atthe architecture level, Maxar GEO communications satellitesare developed under the premise of highly responsive groundin the loop for the resolution of anomalies, and theimplementation takes a fail-operational approach to minimizedown time for its customers. In contrast, a deep space missionmust be able to maintain safety with long periods of groundcommunication outage. Additionally, with no time-criticalevents after launch, the Psyche spacecraft will generally failsafe in the presence of anomalous conditions; specialconsideration is being given to this approach, however, tominimize the loss of electric propulsion thrust time, which iscritical to low-thrust missions. At the hardware level, thedetailed definition of interfaces between JPL and Maxarhardware presents a unique challenge in the development andflowdown of fault management requirements, the developmentand implementation of fault monitors and responses, and thedevelopment and verification of fault containment boundaries.This paper describes the evolution of the Psyche faultmanagement architecture and design from the concept studyinto the preliminary design phase, with a focus on the uniquechallenges associated with flying GEO communicationssatellite hardware in deep space, implementing a robust lowthrust mission, and the integration of design philosophies andhardware from JPL and Maxar. Details regarding how thesechallenges are addressed in the fault management design inorder to maximize heritage, leverage the strengths of eachorganization, and minimize risk across the design are alsodiscussed.

Marsh, Danielle↗

DOE OSTI2024

Process Improvement For Pu-238 Production at Idaho National Laboratory

Idaho National Laboratory (INL) has supported the production of Pu-238 for future NASA deep space missions since 2017. Over this time, INL has worked to improve the qualification process of Pu-238 production targets as well as improve processes related to the shipping, storage, irradiation, and storage of Pu-238 production targets. Qualification of Pu-238 production targets began with flux measurements and scoping analysis to provide fundamental data to confirm the impacts on the operation of the Advanced Test Reactor (ATR), Fig1. Later, initial production targets were irradiated in ATR’s I-7 position, and then the South Flux Trap (SFT). A modified target design was then implemented which would use the full length of the ATR core and increase Pu-238 production. While working to improve and streamline the qualification of the Pu-238 production targets, INL worked to improve multiple operational aspects of the Pu-238 production process. These changes include updating procedures to streamline operations, supporting modification of shipping containers to contain five rather than one production target, reviewing target receipt procedures and changing work flow to provide flexibility in target receipt, and designing and fabricating support equipment for the storage and internal transfer of production targets

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Process Improvements For Pu-238 Production at Idaho National Laboratory

07 ISOTOPE AND RADIATION SOURCES↗