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NASA NTRS2015

Results of Lunar Impact Observations During Geminid Meteor Shower Events

Meteoroids are natural particles with origins from comets, asteroids, and planets from within the solar system. On average, 33 metric tons (73,000 lb) of meteoroids hit Earth everyday with velocities ranging between 20 and 72 km/s. However, the vast majority of these meteoroids disintegrate in the atmosphere and never make it to the ground. The Moon also encounters the same meteoroid flux, but has no atmosphere to stop them from striking the surface. At such speeds even a small meteoroid has incredible energy. A meteoroid with a mass of only 5 kg can excavate a crater over 9 m across, hurling 75 metric tons (165,000 lb) of lunar soil and rock on ballistic trajectories above the lunar surface. Meteoroids with particle sizes as small as 100 micrometer (1 Microgram) can do considerable damage to spacecraft in Earth's orbit and beyond. Impacts can damage thermal protection systems, radiators, windows, and pressurized containers. Secondary effects might include partial penetration or pitting, local deformation, and surface degradation that can cause a failure upon reentry. The speed, mass, density, and flux of meteoroids are important factors for design considerations and mitigation during operations. Lunar operations (unmanned and manned) are also adversely affected by the meteoroid flux. Ejecta from meteoroid impacts is also part of the lunar environment and must be characterized. Understanding meteoroid fluxes and the associated risk of meteoroids impacting spacecraft traveling in and beyond Earth's orbit is the objective of the Meteoroid Environment Office (MEO) located at Marshall Space Flight Center (MSFC). One of the MEO's programs is meteoroid impact monitoring of the Moon. The large collecting area of the night side of the lunar disk provides statistically significant counts of meteoroids that can provide useful information about the flux of meteoroids in the hundreds of grams to kilograms size range. This information is not only important for characterizing the lunar environment associated with larger lunar impactors, but also provides statistical data for verification and improving meteoroid prediction models. Current meteoroid models indicate that the Moon is struck by a sporadic meteoroid with a mass greater than 1 kg over 260 times per year. This number is very uncertain since observations for objects in this mass range are few. Factors of several times, higher or lower, are easily possible. Meteor showers are also present to varying degrees at certain times of the year. The Earth experiences meteor showers when encountering the debris left behind by comets, which is also the case with 2 the Moon. During such times, the rate of shower meteoroids can greatly exceed that of the sporadic background rate for larger meteoroids. Looking for meteor shower impacts on the Moon at about the same time as they occur on Earth will yield important data that can be fed into meteor shower forecasting models, which can then be used to predict times of greater meteoroid hazard on the Moon. The Geminids are one such meteor shower of interest. The Geminids are a major meteor shower that occur in December with a peak intensity occurring usually during the 13th and 14th of the month and appearing to come from a radiant in the constellation Gemini. The Geminids are interesting in that the parent body of the debris stream is an asteroid, which along with the Quadrantids, are the only major meteor showers not originating from a comet. The Geminids parent body, 3200 Phaethon, is about 5 km in diameter and has an orbit that has a 22deg inclination which intersects the main asteroid belt and has a perihelion less than half of Mercury's perihelion distance. Thus, its orbit crosses those of Mars, Earth, Venus, and Mercury. The Geminid debris stream is by far the most massive as compared to the others. When the Earth passes through the stream in mid-December, a peak intensity of approx. equal 120 meteors per hour can be seen. Because of the Geminids' relatively large intensity and unique origin, it is important to monitor and gain information about the Geminids so as to improve their forecasts and understand their contribution to the meteoroid environment in Earth's orbit and at the Moon. It is the purpose of this Technical Memorandum (TM) to document two lunar observing periods coinciding with the Geminid meteor showers that occurred in 2006 and 2010.

Suggs, R. J.↗
NASA NTRS2018

A Risk Analysis Tool for Estimating the Risk of Electrical Failures Due to Human Induced Defects

Aerospace electrical systems are required to withstand and adequately operate in extremely harsh environments that include, for example, high radiation exposure, temperature extremes, intense vibrational stress and drastic temperature cycling. The nature of aerospace electronics also demands high reliability since, with very few exceptions, there is no chance for hardware servicing or repairs. Common risk mitigation techniques for this type of situation are to perform a Reliability Analysis of the system throughout the development cycle, and to use electrical components that are regarded as “high reliability” because of additional controls and requirements applied in their design, manufacturing and testing. Unfortunately, studies have shown that even though these techniques are used, many systems fail to meet mission requirements well before the predicted lifetimes. This paper presents the analysis of failures of electrical parts, experienced during various stages of system development, at NASA Goddard Space Flight Center, Greenbelt MD, between the years 2001 and 2013. These components were subjected to qualification, screening and testing in which the goal was to ensure that the components would survive the stresses of the mission. The analysis categorizes failures by part type and failure mechanisms. One of the results of the analysis was the realization that a surprising proportion of failures experienced during system integration and testing were caused by human error (i.e. human induced defect). Further analysis included the determination of root failure mechanisms and any influencing factors contributing to these failures. The major causes of these defects were attributed to electrostatic damage (ESD), electrical overstress (EOS), mechanical overstress (MOS), and thermal overstress (TOS). Finally, the study proposes a risk analysis tool which incorporates these major causes for the failures, termed error-producing conditions (EPCs), and a proportionality factor representing the number of each type of failure that has occurred at the facility under study. These factors are quantified and used to communicate the risk of human induced defects for the assembly, integration and testing of space hardware based on the system’s electrical parts list. The new risk identification can trigger risk-mitigating actions more effectively, based on the presence of component categories or other hazardous conditions that have a history of failure due to human error.

Majewicz, Peter J.↗
NASA NTRS2007

Large Solar-Rejection Filter

NASA utilized Image Intensified Video Cameras for ATV data acquisition from a jet flying at 12.8 km. Afterwards the video was digitized and then analyzed with a modified commercial software package, Image Systems Trackeye. Astrometric results were limited by saturation, plate scale, and imposed linear plate solution based on field reference stars. Time-dependent fragment angular trajectories, velocities, accelerations, and luminosities were derived in each video segment. It was evident that individual fragments behave differently. Photometric accuracy was insufficient to confidently assess correlations between luminosity and fragment spatial behavior (velocity, deceleration). Use of high resolution digital video cameras in future should remedy this shortcoming. A scenically accurate description of matter interpreted as a substance made up of corpuscular constituents was established during the course of the 19th century. In this description, atoms--the building blocks of the matter--form molecules. The properties of the molecules were described by chemistry or thermodynamics depending on what characteristics of the matter were investigated. In both theories, the molecules can dissociate to atoms when the kinetic energies of the atoms exceed the strength of the chemical bonds. The number of atoms is always preserved in a closed system. This is not true, however, when the matter takes up much higher energies at relativistic scales. New particles can be produced at the expense of the kinetic energy. The number of particles is no longer preserved. There are other conserved quantities, however, these quantities, the charge, baryon number, lepton number, are associated with particles that are considered elementary today. The properties and behavior of these elementary particles is the subject of Particle Physics or High Energy Physics. Practice Page: A crewmember touching a positively charged surface was thought to be galvanically isolated from the vehicle ground analogous to a bird on a high voltage power wire. Recent analysis confirms that positive floating potentials, ionospheric currents to the EVA suit, can be hazardous. The analysis is wrong in that the ionospheric plasma itself can close the circuit. Parametric analysis of very low voltage exposures (2 to 15 volts) could cause pain and/or involuntary muscle tetani or spinal cord shock. NASA worked with the Naval Health Research Center Detachment Directed Energy Bioeffects Laboratory to examine the affects electrical hazards could have on extravehicular activity using two models. The results of the two computational models were combined to predict areas of the body in which neurons of different diameters would be excited. They predicted that physiologically active current could be conducted across the crew member causing catastrophic hazards. Future work to analyze additional current paths was proposed. The FUSE spectrum of BB Dor, observed in a high state, is modeled with an accretion disk with a very low inclination (possibly lower than 10 degrees). Assuming an average WD mass of 0.8 solar mass leads to a distance of the order of approximately 650pc, consistent with the extremely low galactic reddening in its direction, and a mass accretion rate of 10 (exp -9) solar mass a year. The spectrum presents some broad and deep silicon and sulfur absorption lines, indicating that these elements are over-abundant: silicon is 3 times solar, and sulfur is 20 times solar. The FUSE spectrum of BB Dor, observed in a high state, is modeled with an accretion disk with a very low inclination (possibly lower than 10 degrees). Assuming an average WD mass of 0.8 solar mass leads to a distance of the order of approximately 650pc, consistent with the extremely low galactic reddening in its direction, and a mass accretion rate of 10 (exp -9) solar mass a year. The spectrum presents some broad and deep silicon and sulfur absorption lines, indicating that these elements are over-abundant: silicon is times solar, and sulfur is 20 times solar. From its previously observed optical emission lines, P831-57 (WD 0334 6400 or Ret 1 in A Catalog and Atlas of Cataclysmic Variables: Living Edition) has been suspected to contain an accretion disk associated with a companion star in orbit around a subdwarf star with a temperature T is greater than 21,000K. P831-57 has therefore been classified as a nova-like. However, our present observations show it to be a DA + dMe binary. The analysis of its Far Ultraviolet Spectroscopic Explorer (FUSE) spectrum (continuum and lines) reveal an average mass white dwarf (Log(g) approximately equals 7.8 plus or minus 0.1)with a temperature T approximately equals 37,000 plus or minus 500K, an extremely low projected rotational velocity, and a distance of about 115 plus or minus 5pc. The photosphere contains C, N, Si, and S (at about 1% of solar abundances). The dMe star is seen as a flux excess in near-infrared photometry and appears to show occasional flaring of about one magnitude as seen in the Harvard plates. There is no evidence of periodic variability in the spectroscopic or photometric data. We find no evidence of a an accretion disk, instead we find evidence of wind accretion as the stellar carbon abundance (N(C)/N(H) = 2.5 x 10 (exp -6) is about ten times larger than predicted by radiative levitation for such a gravity and temperature. The power needs and solutions for the space exploration and lunar mobility program are discussed. Long term missions in space and on the lunar surface require high energy batteries. Rechargeable batteries for mobility systems and portable utility pallet are needed for successful exploration missions. Nanomaterial usage increases the energy density of the cells apart from increasing the power density. The symptoms and threats from acute mountain sickness (AMS) are discussed. The underlying assumptions concerning spacecraft atmosphere mean there is a potential risk to astronauts. The baseline worst case scenario is about 25% based on direct ascent to 8.0 psia with 32% O2. The practical mitigation approach is a staged depressurization scheme. Due to the uncertainty about potential AMS risk the flight surgeon should prepare, focused research should proceed, and current analytical efforts should continue. This slide presentation reviews the threat astronauts face from acute mountain sickness (AMS). The incidence of AMS is highly variable and the risk to astronauts is unclear. However, the potential risk is higher than current EAAs suggest and precautions should be implemented. Due to the uncertain nature of the risk flight surgeons should prepare, and focused research should proceed. Quasiparticle tunneling can be understood at low temperatures using a non-equilibrium kinetic theory. Low-temperature tunneling can be suppressed using existing techniques: island-lead gap engineering, lead cooling with SIN junctions, and quasiparticle traps. The slide presentation reviews the science goals and mission planning for the proposed Jupiter System Observer (JSO). The spacecraft would accommodate 9 instruments making the instrument payload more capable than any previously flown to Jupiter. The would-be mission includes study programs for Jupiter's satellites, interior, magnetosphere and atmosphere. The power needs and solutions for the space exploration and lunar mobility program are discussed. Long term missions in space and on the lunar surface require high energy batteries. Rechargeable batteries for mobility systems and portable utility pallet are needed for successful exploration missions. Nanomaterial usage increases the energy density of the cells apart from increasing the power density. This slide presentation reviews the power requirements for the space exploration and the lunar surface mobility programs. It includes information about the specifications for high energy batteries and the power requirements for lunar rovers,

Roberts, William↗
NASA NTRSDate not supplied

Wildfire Segmentation From Remotely Sensed Data Using Quantum-Compatible Conditional Vector Quantized-Variational Autoencoders

Wildfires represent a critical environmental hazard with multifaceted implications for ecosystems, communities, and public health [1]. The escalating frequency and intensity of wildfires globally have intensified the urgency for robust segmentation methodologies to facilitate effective mitigation, response, and recovery strategies [2]. Accurate wildfire segmentation is pivotal for delineating fire boundaries, assessing progression patterns, and prioritizing resource allocation during emergency scenarios. Furthermore, precise segmentation enables stakeholders, including policymakers, environmental scientists, and emergency responders, to formulate evidence-based strategies, thereby minimizing socio-economic disruptions and ecological degradation. Consequently, advancing wildfire segmentation techniques through innovative technological interventions remains a paramount research imperative. Although foundational in wildfire segmentation, traditional deterministic models exhibit inherent limitations that compromise their efficacy in dynamic and uncertain environments. These models often operate on rigid algorithms prioritizing deterministic classifications, thereby overlooking the inherent complexities and uncertainties associated with wildfire behavior and satellite data variability. Such deterministic frameworks tend to produce oversimplified representations that fail to capture the intricate nuances of evolving fire dynamics, spatial heterogeneity, and environmental interactions [1]. Consequently, the deterministic approach’s propensity for uncertainty collapsing [1, 3] hampers the accuracy, reliability, and applicability of segmentation outcomes in real-world scenarios. Contrastingly, stochastic models offer a more nuanced and adaptable framework for wildfire segmentation. By integrating probabilistic elements into the modeling paradigm, stochastic approaches, particularly probabilistic approaches such as variational auto encoders (VAEs) [4], facilitate comprehensive uncertainty assessment, enabling researchers to quantify and incorporate uncertainties into segmentation outcomes effectively. This probabilistic nature empowers stochastic models to encapsulate variability, account for data inconsistencies, and adapt to evolving environmental conditions, enhancing segmentation accuracy, reliability, and robustness. Embracing stochastic methodologies thus catalyzes advancements in wildfire science by fostering a more holistic, adaptive, and resilient segmentation framework. Despite VAEs demonstrating significant promise in various applications, they come with inherent limitations that have garnered attention within the machine learning community. One of the primary drawbacks lies in their reliance on static priors, which essentially assume a fixed distribution for latent variables, thereby limiting the model’s flexibility to capture complex data structures effectively [5]. This static nature leads to suboptimal representations, especially when dealing with complex and high-dimensional data. Additionally, VAEs often struggle with generating sharp and realistic samples, a phenomenon commonly referred to as mode collapse [5, 7, 6]. Furthermore, the optimization process in VAEs, which involves balancing the reconstruction loss and the regularization term, can sometimes be challenging to fine-tune [7]. In recent efforts to address these shortcomings, alternative approaches like Vector Quantized Variational Auto encoders(VQ-VAEs) [7], address the challenges by incorporating discrete latent variables and leveraging techniques that enhance the quality and diversity of generated samples while maintaining efficient training dynamics. VQ-VAEs propose a dynamic prior distribution generation mechanism that diverges from the static priors commonly associated with traditional VAEs. This dynamic approach allows for more adaptive and context-aware latent variable representations, thereby potentially capturing complex data structures more effectively. Unlike autoregressive prior models such as PixelCNN, which, despite their ability to model dependencies across data dimensions, suffer from significant computational inefficiencies and lack flexibility in handling diverse datasets. In our work, we propose to use a generative quantum-compatible approach to help alleviate the shortcomings of autoregressive prior model in VQ-VAEs. Restricted Boltzmann Machines (RBMs) are a viable alternative prior model that can learn prior distributions in a faster and more flexible manner. In this research endeavor, we meticulously curate a state-of-the-art dataset leveraging satellite MODIS data in conjunction with VIIRS fire masks, derived from Fire Radiative Power (FRP), thereby encapsulating diverse wildfire scenarios and environmental contexts. We developed a conditional VQ-VAE architecture with the RBM prior model that is trained in a supervised manner for segmenting wildfire masks. This innovative approach synergistically harnesses deep learning capabilities, enabling the generation of segmentation maps characterized by heightened precision, granularity, and contextual relevance. Furthermore, replacing the autoregressive prior learning method proposed by the original VQ-VAE with a prior density approximation via quantum-compatible RBM facilitates expedited inference processes, augments flexibility in prior sampling, optimizes computational efficiency and establishes a groundbreaking benchmark in wildfire segmentation methodologies.

quantum machine learning↗
NASA NTRS2011

Why Atens Enjoy Enhanced Accessibility For Human Space Flight

In the context of human space flight (HSF), the concept of near-Earth object (NEO) accessibility is highly subjective. Whether or not a particular NEO is accessible critically depends on mass, performance, and reliability of interplanetary HSF systems yet to be designed. Such systems would certainly include propulsion and crew life support with adequate shielding from both solar flares and galactic cosmic radiation. Equally critical architecture options are relevant to NEO accessibility. These options are also far from being determined and include the number of launches supporting an HSF mission, together with whether or not consumables are to be pre-emplaced at the destination. Until the unknowns of HSF to NEOs come into clearer focus, the notion of relative accessibility is of great utility. Imagine a group of NEOs, each with nearly equal HSF merit determined from their individual characteristics relating to crew safety, scientific return, resource utilization, and planetary defense. The more accessible members of this group are more likely to be explored first. A highly accessible NEO could conceivably be deferred in favor of a less accessible HSF destination because the latter is more accessible during a programmatically desirable launch compliant mission trajectory solutions detected in association with a specific NEO. The known NEO population is then surveyed to illustrate in which regions of heliocentric semi-major axis, eccentricity, and inclination (a, e, i) space NEOs with large n values are mapped. The (a, e, i) mapping is also formatted such that membership in each of four NEO orbit classifications, as defined below, is evident. Amors have orbits everywhere superior to (outside of) Earth's. An Amor is therefore defined to have perihelion between 1.017 astronomical units (AU) and the maximum NEO value of 1.3 AU. As of 0 hrs Universal Time on 1 January 2011 (UT epoch 2011.0), Amors numbered 2855 in the Jet Propulsion Laboratory (JPL) Small-Body Database (SBDB), comprising 37.7% of known NEOs. Apollos have orbits crossing Earth's with periods greater than Earth's. An Apollo is therefore defined to have perihelion less than 1.017 AU and a greater than 1.0 AU. As of 2011.0 UT, Apollos numbered 4080 in the SBDB, comprising 53.9% of known NEOs. Atens have orbits crossing Earth's with periods less than Earth's. An Aten is therefore defined to have aphelion greater than 0.983 AU and a less than 1.0 AU. As of 2011.0 UT, Atens numbered 618 in the SBDB, comprising 8.2% of known NEOs. Atiras have orbits everywhere inferior to (inside of) Earth's. An Atira is therefore defined to have aphelion less than 0.983 AU. As of 2011.0 UT, Atiras numbered 11 in the SBDB, comprising 0.1% of known NEOs. It is no surprise that the largest n values are chiefly associated with Apollos and Atens. Because these orbits cross Earth's, distance to be covered in a given round trip mission time delta-t can be far less than is possible for Amors or Atiras . This delta-t or the sum of mission propulsive impulse magnitudes delta-v can more frequently be minimized to enhance NHATS compliance for Apollos and Atens than is generally the case for Amors and Atiras. A less intuitive trend in NHATS results is that Atens nearly outnumber the more numerous Apollos among the most compliant NEOs as measured by n. This trend is completely out of proportion to the degree Atens are represented among the known NEO population. A theory based on geocentric NEO dynamics is presented by this paper to explain why Atens enjoy inherently greater accessibility than do Apollos. Another trend evident from mapping into (a, e, i) space is the dearth of known NEOs at low e when a < 1 AU. Underrepresentation of Atens and Atiras in the NEO catalog is at least in part attributable to observing exclusively from a perspective near Earth. Generally inferior Aten and Atira orbits are rarely, if ever, in Earth's night sky. Until a comprehensive NEO survey is conducted from an appropriateegion remote from Earth, the theory developed in this paper indicates a substantial fraction of the most accessible NEOs will remain unknown. season. Such a season is really yet another undetermined HSF architecture option. A launch season's duration will likely be measured in weeks, and it will be utilized at an indeterminate point almost certainly more than a decade in the future when HSF programmatic maturity is sufficient. Furthermore, current knowledge of the NEO population relevant to HSF is far from complete. In the 100-m-diameter class of greatest interest, only a few percent of the estimated NEO population is known [2, Figure 2.4]. Therefore, any known, lost, or fictitious NEO in a highly accessible orbit is a potential HSF destination of merit. Even if lost, fictitious, small, or hazardous, such a potential target (or another in a similar orbit) may ultimately prove to be an early HSF destination when the pertinent NEO population is more thoroughly catalogued and NEO orbits are more thoroughly maintained at high accuracy. This paper first reviews methodology and pertinent results from NASA-sponsored research performed in late 2010 and dubbed NEO HSF Accessible Targets Study (NHATS, pronounced as "gnats"). A useful accessibility metric developed during this study is n, the tally of NHATS-

Barbee, Brent↗