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NASA NTRS2019

Coronagraphic Observations of the Lunar Sodium Exosphere January-June, 2017

In order to observe the lunar sodium exosphere out to one-half degree around the Moon, we designed, built and installed a small robotically controlled coronagraph at the Winer Observatory in Sonoita, Arizona. Observations are obtained remotely every available clear night from our home base at Goddard Space Flight Center or from Prescott, Arizona. We employ an Andover temperature-controlled 1.5-angstrom-wide narrow-band filter centered on the sodium D2 line, and a similar 1.5-angstrom filter centered blueward of the D2 line by 3 angstroms for continuum observations. Our data encompass lunations in 2015, 2016, and 2017, thus we have a long baseline of sodium exospheric calibrated images. During the course of three years we have refined the observational sequence in many respects. Therefore this paper only presents the results of the spring, 2017, observing season. We present limb profiles from the south pole to the north pole for many lunar phases. Our data do not fit any power of cosine model as a function of lunar phase or with latitude. The extended Na exosphere has a characteristic temperature of about 2250–6750 degrees Kelvin, indicative of a partially escaping exosphere. The hot escaping component may be indicative of a mixture of impact vaporization and a sputtered component.

Moon↗
NASA NTRS2019

Modeling Meteoroid Densities for Spacecraft Risk Assessment

This report describes the methodologies and algorithms that NASA’s Meteoroid Environment Office (MEO) currently utilizes to measure meteoroid densities. We discuss the needs for an accurate model for the meteoroid density distribution in its Meteoroid Engineering Model (MEM), and its potential implications for spacecraft design. The recently developed process is heavily derived from that of previous work, although subtle differences exist. A thorough comparison of the best-fit densities derived for sixty meteoroids in and with the process described here shows that discrepancies in final densities larger than a factor of two are measured for ∼ 20% of our test events. Such a level of discrepancy suggests that any density calculated using similar methods cannot be assumed to represent a unique fit to the data. Additional observational data for meteoroids beyond those utilized in this work will be essential for producing more reliable and repeatable density measurements.

Ehlert, Steven↗
NASA NTRSDate not supplied

Delamination Depth Imaging for Quasi-Static and Fatigue Load Testing Using Passive Thermography

Passive thermography is used to monitor small increases in temperature resulting from delamination damage formation in composite hat-stiffened panels during both quasi-static and fatigue loading. It has been observed that rapid damage formation produces heating. This is composed of two heat generation components. The first component is an instantaneous response due to an irreversible thermoelastic strain release. The second component is mechanical heating, at the interface of failure, due to fracture damage. This produces a transient rise in temperature as the heat diffuses to the surface. The first component defines the thermal start time for the transient response. A one-dimensional thermal model is fitted to the data pixel by pixel, to produce imagery of the damage depth. The results are compared to ultrasonic and X-ray CT data.

Passive thermography↗
NASA NTRS2019

Coronagraphic Observations of the Lunar Sodium Exosphere January-June, 2017

In order to observe the lunar sodium exosphere out to one-half degree around the Moon, we designed, built and installed a small robotically controlled coronagraph at the Winer Observatory in Sonoita, Arizona. Observations are obtained remotely every available clear night from our home base at Goddard Space Flight Centeror from Prescott, Arizona. We employ an Andover temperature-controlled 1.5 Å wide narrow-band filter centered on the sodium D2line, and a similar 1.5 Å filter centered blueward of the D2line by 3Åfor continuum observations. Our data encompass lunations in 2015, 2016, and 2017, thus we have a long baseline of sodium exospheric calibrated images. During the course of three years we have refined the observational sequence in many respects. Therefore this paper only presents the results of the spring, 2017, observing season. We present limb profiles from the south pole to the north pole for many lunar phases.Our data do not fit any power of cosine model as a function of lunar phase or with latitude. The extended Na exosphere has a characteristic temperature of about 2250 -6750 K, indicative of a partially escaping exosphere. The hot escaping component may be indicative of a mixture of impact vaporization and a sputtered component.

Lunar exosphere composition↗
NASA NTRS2021

Total X-ray Emission from the LMC Observed with HaloSat

We constrain the LMC’s global parameters by modeling the first soft X-ray (0.4–6.8 keV) observations of the entire Large Magellanic Cloud (LMC) produced in a single pointing with moderate spectral resolution by the HaloSat CubeSat. These data are best fit with the sum of two thermal plasma components in collisional ionization equilibrium and a power-law. We find cool (0.210±0.014keV) and hot (0.89±0.14keV) components. The LMC’s total X-ray luminosity is(1.08±0.14)×1039erg s−1.X-ray binaries make up a large fraction of the emission with a luminosity of(6.0±0.8)×1038ergs−1, followed by cool gas from superbubbles, supernovae, and diffuse emission with a luminosity of(3.0±0.3)×1038erg s−1. The hot gas from star formation contributes the smallest fraction, with a luminosity of(1.9±0.5)×1038erg s−1. We estimate the total volume of the cool gas to be between(0.2–1.2)×1010pc3and the hot gas to be between(1.0–5)×107pc3for filling factors off= 1and0.2. These volumes result in a total thermal energy for the cool gas between (1.4–3)×1054ergs for electron densities of 0.017–0.04 cm−3, and a thermal energy for the hot gas between (1.7–4)×1053ergs for electron densities of 0.12–0.3 cm−3. This yields cooling timescales for the cool and hot gas of(1.5–3)×108years and(1.8–6)×107years, respectively

LMC↗
NASA NTRS2018

High Performance Space Computing with System-on-Chip Instrument Avionics for Space-based Next Generation Imaging Spectrometers (NGIS).

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind stateof-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynq-based data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) for JPL’s Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).

Smith, Adam↗
NASA NTRS2018

High Performance Space Computing with System-on-Chip Instrument Avionics for Space-based Next Generation Imaging Spectrometers (NGIS).

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynq-based data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) for JPL’s Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).

Dolinar, Sam↗
NASA NTRS2020

Discovery of a Nearby Young Brown Dwarf Disk

We report the discovery of the youngest brown dwarf with a disk at 102 pc from the Sun, WISEA J120037.79−784508.3 (W1200−7845), via the Disk Detective citizen science project. We establish that W1200−7845 is located in the 3.7 (+4.6,-1.4) Myr old ε Cha association. Its spectral energy distribution (SED) exhibits clear evidence of an infrared (IR) excess, indicative of the presence of a warm circumstellar disk. Modeling this warm disk, we find the data are best fit using a power-law description with a slope α = −0.94, which suggests that it is a young, Class II type disk. Using a single blackbody disk fit, we find T(eff,disk)= 521 K and L(IR)/L(*) =0.14. The near-IR spectrum of W1200−7845 matches a spectral type of M6.0 γ ± 0.5, which corresponds to a low surface gravity object, and lacks distinctive signatures of strong Paβ or Brγ accretion. Both our SED fitting and spectral analysis indicate that the source is cool (T(eff) = 2784–2850 K), with a mass of 42–58 M(Jup), well within the brown dwarf regime. The proximity of this young brown dwarf disk makes the system an ideal benchmark for investigating the formation and early evolution of brown dwarfs.

Maria C. Schutte↗
NASA NTRS2020

An Unusual Transmission Spectrum for the Sub-Saturn KELT-11b Suggestive of a Subsolar Water Abundance

We present an optical-to-infrared transmission spectrum of the inflated sub-Saturn KELT-11b measured with the Transiting Exoplanet Survey Satellite (TESS), the Hubble Space Telescope (HST) Wide Field Camera 3 G141 spectroscopic grism, and the Spitzer Space Telescope (Spitzer) at 3.6 μm, in addition to a Spitzer 4.5 μm secondary eclipse. The precise HST transmission spectrum notably reveals a low-amplitude water feature with an unusual shape. Based on free-retrieval analyses with varying molecular abundances, we find strong evidence for water absorption. Depending on model assumptions, we also find tentative evidence for other absorbers (HCN, TiO, and AlO). The retrieved water abundance is generally ≲ 0.1× solar (0.001–0.7× solar over a range of model assumptions), several orders of magnitude lower than expected from planet formation models based on the solar system metallicity trend. We also consider chemical-equilibrium and self-consistent 1D radiative-convective equilibrium model fits and find that they, too, prefer low metallicities ([M/H] ≲ −2, consistent with the free-retrieval results). However, all of the retrievals should be interpreted with some caution because they either require additional absorbers that are far out of chemical equilibrium to explain the shape of the spectrum or are simply poor fits to the data. Finally, we find that the Spitzer secondary eclipse is indicative of full heat redistribution from KELT-11b's dayside to nightside, assuming a clear dayside. These potentially unusual results for KELT-11b's composition are suggestive of new challenges on the horizon for atmosphere and formation models in the face of increasingly precise measurements of exoplanet spectra.

Knicole D. Colón↗
NASA NTRS2019

High performance space computing with system-on-chip instrument avionics for space-based Next Generation Imaging Spectrometers (NGIS)

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynq-based data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) for JPL’s Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).

Dolinar, Sam↗
NASA NTRS2021

Examining Runner’s Outdoor Heat Exposure Using Urban Microclimate Modeling and GPS Trajectory Mining

It is important to quantify human heat exposure in order to evaluate and mitigate the negative impacts of heat on human well-being in the context of global warming. This study proposed a human-centric framework to examine human personal heat exposure based on anonymous GPS trajectories data mining and urban microclimate modeling. The mean radiant temperature (Tmrt) that represents the human body’s energy balance was used to indicate human heat exposure. The meteorological data and high-resolution 3D urban model generated from multispectral remotely sensed images and LiDAR data were used as inputs in urban microclimate modeling to map the spatio-temporal distribution of the Tmrt in the Boston metropolitan area. The anonymous human GPS trajectory data collected from fitness Apps was used to map the spatiotemporal distribution of human outdoor activities. By overlaying the anonymous GPS trajectories on the generated spatio-temporal maps of Tmrt, this study further examined the heat exposure of runners in different age-gender groups in the Boston area. Results show that there is no significant difference in terms of heat exposure for female and male runners. The female runners in the age of 45-54 are exposed to more heat than female runners of 18-24 and 25-34, while there is no significant difference among male runners. This study proposed a novel method to estimate human heat exposure, which would shed new light on mitigating the negative impacts of heat on human health.

Personal heat exposure↗
NASA NTRS2020

Operations Concept for Responding to Urgent Requests for NASA-ISRO Synthetic Aperture Radar (NISAR)

The NASA-ISRO Synthetic Aperture Radar, or NISAR, mission is an Earth-mapping radar observatory to be launched from Sriharikota (India) in 2022. This mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organization (ISRO). This spacecraft will carry two instruments that will operate at radar wavelengths (L and Sband) and will provide data for understanding changes in the Earth’s land surface. The scientific data from this mission will revolutionize our understanding of the causes and consequences of land surface changes on Earth, ranging from Solid Earth Deformation in the form of natural hazards like earthquakes, volcanic eruptions and landslides, to ecosystem disturbances, to changes in the cryosphere (measurements of polar ice caps, ice sheets and sea ice). A nominal Reference Observation Plan, that repeats roughly every 12-24 days, developed prior to launch by the NISAR Mission Planning team, in consultation with the Science Team, will form the basis of science data collection by the payload instruments onboard the NISAR observatory after launch. Scheduling of science observations for the mission requires accounting for limited spacecraft resources like onboard data storage, downlink capacity, energy/power, thermal limits and instrument duty cycles. In addition to nominal science data collection, the project has a Level 1 requirement to respond to requests for urgent data acquisition over disaster sites (natural or anthropogenic) by scheduling new acquisitions within 24 hrs of notification and delivering science data within 5 hours of data acquisition. This capability is to be exercised on a ‘best-efforts basis’. While the definition of what constitutes an ‘urgent request’, and how such requests would be submitted to the project, is within the domain of the Science Team, the Mission System team is responsible for developing the baseline operations concept and implementation approach for responding to such requests. Given the ‘best-efforts’ nature of this requirement, a few highlevel guidelines have been developed to help guide the formulation of the operations concept, and are presented in this paper. Requests for urgent response data will be accommodated following the guiding principle of minimal to no impact on nominal science and planned engineering activities. No change in satellite orbit or attitude will be made for urgent response. Restricting response approaches to only changing the downlink and/or ground processing priority for existing observations, and adding new observations only in areas where NISAR will not be nominally imaging, allows for minimal impact on the Reference science Observation Plan. No instrument mode changes will be allowed for urgent response (except for high-priority requests), and no new observations that impact either planned science or engineering activities will be scheduled. Additionally, data requests must fit within the available project resource margins (both spacecraft and ground resources are to be evaluated). Both JPL and ISRO will be involved at various steps of the implementation, irrespective of whether the urgent request is for L-SAR (NASA instrument) or S-SAR (ISRO instrument) or a joint dataset.

Sharma, Priyanka↗
NASA NTRS2021

Are Compton-thin AGNs Globally Compton Thin?

We select eight nearby active galactic nuclei (AGNs) which, based on previous work, appear to be Compton-thin in the line of sight. We model with MYTORUS their broadband X-ray spectra from 20 individual observations with Suzaku, accounting self-consistently for Fe Kα line emission, as well as direct and scattered continuum from matter with finite column density and solar Fe abundance. Our model configuration allows us to measure the global, out of the line of sight, equivalent hydrogen column density separately from that in the line of sight. For 5 out of 20 observations (in 3 AGNs) we find that the global column density is in fact ≳1.5 × 1024 per sq.cm, consistent with the distant scattering matter being Compton-thick. For a fourth AGN, two out of five observations are also consistent with being Compton-thick, although with large errors. Some of these AGNs have been reported to host relativistically broadened Fe Kα emission. Based on our modeling, the Fe Kα emission line is not resolved in all but two Suzaku observations, and the data can be fitted well with models that only include a narrow Fe Kα emission line.

P. Tzanavaris↗
NASA NTRSDate not supplied

P52D-1583 - Further Improvements to Constraints on Titan’s Atmospheric n-Butane, via Ground-Based Observations

We have acquired high spectral resolution ground-based observations of Titan in the mid-infrared from NASA Infrared Telescope Facility’s Texas Echelon Cross Echelle Spectrograph instrument , designed to constrain the abundances of new molecules within Titan’s atmosphere. The target molecule for this work, n-butane (n-C H ), though predicted by photochemical models of Titan’s atmosphere , has never been detected. Using the NEMESIS radiative transfer code , we retrieved a disk-averaged temperature profile for Titan by modeling CH emission in the 1248 cm region. Using this temperature profile, we then retrieved disk-averaged profiles of ethene (C H ), propane (C H ), and propene (C H ) in the 956 and 965 cm regions, which are also home to the strong and vibrational features of n-butane. We used an n-butane pseudoline list from JPL in order to systematically introduce a range of n-butane mixing ratios into the model, to constrain the molecule’s abundance based on the model’s changing fit to the data. We derive 3-confidence upper limits at an altitude of 150 km of 48 and 31 ppb for n-butane, via the and bands in the 956 and 965 cm regions, respectively. These are significantly tighter upper limits when compared to the ~300 ppb upper limit found in our recent work which used the same methodology but on much lower resolution limb data collected by the Cassini spacecraft. Upper limits on gas abundances are important for continued improvement of photochemical models of Titan’s atmosphere, which is understood to be an important analog for the prebiotic Earth atmosphere . They are also important for understanding the composition of Titan’s lakes and seas, which are likely to contain these larger hydrocarbons . Finally, as larger molecules like C ’s are thought to be able to serve as formation sites for building haze particles, constraining their abundances is important for understanding the process of haze formation at Titan and at Earth Ref: [1] J. H. Lacy, et al., PASP, 2002. [2] Y.L. Yung, et al., ApJS, 1984. [3] M. Dobrijevic, et al., Icarus, 2021. [4] P. G. J. Irwin et al., JQSRT, 2008. [5] K. Sung, et al., JQSRT, 2020. [6] B. L. Steffens, et al., PSJ, 2022. [7] Clarke & Ferris, Origins Life Evol. Biosphere, 1997. [8] D. Cordier, et al., ApJ, 2008. [9] D. B. Curtis, et al., JPCA, 2005.

Brendan Steffens↗
NASA NTRSDate not supplied

Micrometeoroid and Orbital Debris (MMOD) Testing, Ballistic Limit Definition and Risk Assessment of the Exploration Extravehicular Mobility Unit (xEMU)

A well-known hazard associated with exposure to the space environment is the risk of failure due to an impact from a micrometeoroid and orbital debris (MMOD) particle. As NASA prepares to return astronauts to the moon with the Artemis program, the next generation of spacesuit is in development to support future extravehicular activities (EVAs.) An MMOD impact to the spacesuit is of great concern as a large leak could prevent an astronaut from safely reaching an airlock in time resulting in a loss of life. The exploration extravehicular mobility unit (xEMU) must meet MMOD requirements for multiple environments including those in low earth orbit (LEO) as well as the meteoroid and secondary lunar regolith ejecta environments found on the lunar surface. The subject of this paper is an internal xEMU configuration design developed by NASA Johnson Space Center (JSC) personnel. The xEMU shares similarities with the legacy Extravehicular Mobility Unit (EMU) spacesuit that is currently used for ISS EVAs, however differences in the layup (e.g., materials, thicknesses, and layers) of the fabric environmental protection garment (EPG), portable life support system (xPLSS) and helmet required an extensive test program to determine ballistic performance. Over 100 hypervelocity impact (HVI) tests were performed by the NASA/JSC HVIT and White Sands Test Facility (WSTF) teams on the xEMU EPG, xPLSS and helmet to generate ballistic limit equations (BLEs) for MMOD impacts. Additionally, over 50 low speed tests (< 1km/s) were performed by the NASA/JSC HVIT and Southwest Research Institute (SwRI) teams on the xEMU EPG, xPLSS and helmet to generate BLEs for lunar ejecta impacts. Post testing, ballistic limit equations (BLEs) used to define the performance of the various regions on the xEMU spacesuit were developed from a generic set of BLEs. The HVI and low speed testing was performed to establish a physical basis for the equations with the coefficients and exponents of the generic BLEs adjusted to fit the test data. The xEMU BLEs were added to the NASA/JSC software application used for spacecraft MMOD risk assessments (BUMPER-3). A finite element model (FEM) of the xEMU spacesuit, which defines the size and shape of the spacesuit as well as the locations of the various shielding configurations, was created based on a solid model provided by the xEMU program office. Using the FEM file and added xEMU BLEs, BUMPER-3 assessments of the xEMU spacesuit for probability of no penetration (PNP) were performed. For the LEO assessment of a typical ISS EVA, the orbital debris and meteoroids environments were defined using the latest engineering models, ORDEM 3.2 and MEM-3 respectively. The lunar surface assessment again used the MEM-3 engineering model to define the meteoroid environment along with the current released lunar surface ejecta model, NASA SP-8013 (developed during the Apollo Program). The Space Team in the Natural Environments Branch at Marshall Space Flight Center (MSFC) will soon release the new Lunar Meteoroid Ejecta Engineering Model (LMEEM), at which time the xEMU lunar surface EVA will be reassessed. Assessment of the MMOD risk for an 8-hour, 2-person EVA in both LEO and on the lunar surface showed that the xEMU spacesuit meets the program technical requirement of 1 in 2500 failure odds. Similar to the legacy EMU spacesuit, the majority of the MMOD risk (96% of the LEO EVA risk and 99% of the lunar surface EVA risk) is concentrated in regions of xEMU that are comprised primarily of softgoods (arms, legs, and gloves) rather than the hardgoods (xPLSS, hard upper torso and helmet).

Micrometeoroid↗
NASA NTRSDate not supplied

Micrometeoroid and Orbital Debris (MMOD) Testing, Ballistic Limit Equation Definition and Risk Assessment of the Exploration Extravehicular Mobility Unit (xEMU)

A well-known hazard associated with exposure to the space environment is the risk of failure due to an impact from a micrometeoroid and orbital debris (MMOD) particle. As NASA prepares to return astronauts to the moon with the Artemis program, the next generation of spacesuit is in development to support future extravehicular activities (EVAs.) An MMOD impact to the spacesuit is of great concern as a large leak could prevent an astronaut from safely reaching an airlock in time resulting in a loss of life. The exploration extravehicular mobility unit (xEMU) must meet MMOD requirements for multiple environments including those in low earth orbit (LEO) as well as the meteoroid and secondary lunar regolith ejecta environments found on the lunar surface. The subject of this paper is an internal xEMU configuration design developed by NASA Johnson Space Center (JSC) personnel. This paper will expand on the hypervelocity impact (HVI) testing and ballistic limit equation (BLE) definition work that was partially presented at the 2nd International Orbital De-bris (IOC-II) Conference held in Sugar Land, TX in December 2023. The xEMU shares similarities with the legacy Extravehicular Mobility Unit (EMU) spacesuit that is currently used for ISS EVAs, however differences in the layup (e.g., materials, thicknesses, and layers) of the fabric environmental protection garment (EPG), portable life support system (xPLSS) and helmet required an extensive test program to determine ballistic performance. Over 100 hypervelocity impact (HVI) tests were performed by the NASA/JSC HVIT and White Sands Test Facility (WSTF) teams on the xEMU EPG, xPLSS and helmet to generate ballistic limit equations (BLEs) for MMOD impacts. Additionally, over 50 low speed tests (< 1km/s) were performed by the NASA/JSC HVIT and Southwest Research Institute (SwRI) teams on the xEMU EPG, xPLSS and helmet to generate BLEs for lunar ejecta impacts. Post testing, ballistic limit equations used to define the performance of the various regions on the xEMU spacesuit were developed from a generic set of BLEs. The HVI and low speed testing was performed to establish a physical basis for the equations with the co-efficients and exponents of the generic BLEs adjusted to fit the test data. The xEMU BLEs were added to the NASA/JSC software application used for space-craft MMOD risk assessments (BUMPER-3). A finite element model (FEM) of the xEMU spacesuit, which defines the size and shape of the spacesuit as well as the locations of the various shielding configurations, was created based on a solid model provided by the xEMU program office. Using the FEM file and added xEMU BLEs, BUMPER-3 assessments of the xEMU spacesuit for probability of no penetration (PNP) were performed. For the LEO assessment of a typical ISS EVA, the orbital debris and meteoroids environments were defined using the latest engineering models, ORDEM 3.2 and MEM-3 respectively. The lunar sur-face assessment again used the MEM-3 engineering model to define the meteoroid environ-ment along with the current released lunar surface ejecta model, NASA SP-8013 (developed during the Apollo Program). The Space Team in the Natural Environments Branch at Mar-shall Space Flight Center (MSFC) will soon release the new Lunar Meteoroid Ejecta Engineering Model (LMEEM), at which time the xEMU lunar surface EVA will be reassessed. Assessment of the MMOD risk for an 8-hour, 2-person EVA in both LEO and on the lunar surface showed that the xEMU spacesuit meets the program technical requirement of 1 in 2500 failure odds. Similar to the legacy EMU spacesuit, the majority of the MMOD risk (96% of the LEO EVA risk and 99% of the lunar surface EVA risk) is concentrated in regions of xEMU that are comprised primarily of softgoods (arms, legs, and gloves) rather than the hardgoods (xPLSS, hard upper torso and helmet).

Micrometeoroid↗
NASA NTRS2023

Mitigating Worst-Case Exozodiacal Dust Structure in High-Contrast Images of Earth-Like Exoplanets

Detecting Earth-like exoplanets in direct images of nearby Sun-like systems brings a unique set of challenges that must be addressed in the early phases of designing a space-based direct imaging mission. In particular, these systems may contain exozodiacal dust, which is expected to be the dominant source of astrophysical noise. Previous work has shown that it may be feasible to subtract smooth, symmetric dust from observations; however, we do not expect exozodiacal dust to be perfectly smooth. Exozodiacal dust can be trapped into mean-motion resonances with planetary bodies, producing large-scale structures that orbit in lock with the planet. This dust can obscure the planet, complicate noise estimation, or be mistaken for a planetary body. Our ability to subtract these structures from high-contrast images of Earth-like exoplanets is not well understood. In this work, we investigate exozodi mitigation for Earth–Sun-like systems with significant mean-motion resonant disk structures. We find that applying a simple high-pass filter allows us to remove structured exozodi to the Poisson noise limit for systems with inclinations <60° and up to 100 zodis. However, subtracting exozodiacal disk structures from edge-on systems may be challenging, except for cases with densities <5 zodis. For systems with three times the dust of the solar system, which is the median of the best fit to survey data in the habitable zones of nearby Sun-like stars, this method shows promising results for mitigating exozodiacal dust in future Habitable Worlds Observatory observations, even if the dust exhibits significant mean-motion resonance structure.

Miles H. Currie↗
DOE OSTI2022

On Feature, Classifier and Detector Fusers for U-235 Signatures Using Gamma Spectral Counts

Three types of information fusion strategies are studied to assess the performance of classifiers for detecting low-level U-235 radiation sources, using features obtained from gamma spectra of NaI detectors. These three strategies are based on using two spectral region features, fusing eight classifiers of diverse designs, and fusing multiple detectors located at different positions around the source. The inner, middle and outer groups of detectors, within a formation of two concentric circles and a spiral of 21 detectors, are identified based on their distance to the source, which is located at the center. This study provides two main qualitative insights into this classification task. First,the fusion of detectors leads to an overall improved classification performance, least in the inner group, most in the outer group, and in between for the middle group. Second, several classifiers and fusers achieve lower training error which does not translate to lower generalization error, indicating their over-fitting to training data.

Rao, Nageswara↗