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NASA NTRSDate not supplied

Retrospectives: Current State of Knowledge on the Intersection of Spaceflight Stressors and Microbial Risks to Crew and Craft

OVERVIEW The spaceflight environment has several unique stressors that affect the health of both the crew and the spacecraft. An area of continued, albeit incomplete, study is the interaction of these stressors on microbial populations inherent to both astronauts and spacecraft surfaces and systems. A primary concern is the potential for the spaceflight environment to perturb the phenotype of these populations towards negative outcomes for crew and craft. In order to effectively mitigate these potential risks, they must first be characterized. We performed a retrospective literature analysis to assess the current state of knowledge regarding the affects of ionizing radiation and elevated CO2 on relevant microbial populations. The results of these retrospectives will guide next steps in the decisions of what (if any) further studies should be pursued and to guide decisions of the need for countermeasures. STRESSORS Ionizing radiation. The health risk involved with increased exposure to cosmic radiation has been studied in crew for 35+ years, with human health and cancer risk being the main focus. However, space radiation could also affect both the resident microorganisms aboard the ISS and the normal, healthy astronaut microbiomes that are of direct concern for crew health. A retrospective review of over 250 publications was accomplished looking at the impact of cumulative ionizing radiation doses lower than 3 Gy (chronic or acute) on microbial populations. Elevated CO2. The health risk involved with elevated atmospheric CO2 in spacecraft, primarily focusing on human toxicological risks, is understudied. The current Spaceflight Maximum Allowance Concentration for 24-hour average CO2 is 0.4% (3 mm Hg), which is significantly higher than terrestrial levels (0.04%). Whether these elevated ambient CO2 levels aboard spacecraft influence the diversity and phenotypic responses of the resident microbial communities from both the spacecraft environment (air, surface, water) and crew members (gut, nasal, skin microbiomes) is not known. A retrospective review was accomplished looking at the impact of chronic CO2 exposure up to 0.7% (5 mm Hg) for up to 6 months and acute exposure up to 2.6% (20 mm Hg) for up to 24 hours. CONCLUSIONS: MICROBIOME OF THE BUILT ENVIRONMENT The microbiome of the built spacecraft environment has been sampled consistently over the course of human spaceflight and significant advancements have been made in identifying microbial populations on the ISS. The dominant source of microbes on spacecraft surfaces are human-derived. Once in the spacecraft built environment, the extreme environment selects for features that enhance survival. While efforts to understand potential antibiotic resistance and pathogenicity of ISS isolates is robust, there is little to no understanding of which spaceflight environmental stressors, to include ionizing radiation or elevated CO2, drive the evolutionary trajectory of spacecraft-associated microbial populations. CONCLUSIONS: MICROBE-HOST INTERACTIONS The host-microbiome field has emerged as an important factor in human health on Earth as well in spaceflight. The field is struggling with the complexity of the system under investigation as there is substantial taxonomic and functional heterogeneity in these communities, making it difficult to establish clear stimulus-response dynamics. Taxonomic characterization is the norm; however, the functional role of each community member is key to linking environmental perturbations to potential dysbiosis. For both ionizing radiation and elevated CO2, the likely target of the perturbation is the host tissue, not the microbes themselves.. Any resulting changes to the microbial community composition and/or function is likely a result of adapting to those changes in the host physiology. RECOMMENDATIONS Emphasize functional characterization as opposed to taxonomic characterization of microbial communities. Increase the number of investigations using chronic, spaceflight-relevant doses of ionizing radiation. MoBE studies should move away from observational studies towards predictive modeling of community dynamics. Continue to develop scale-down models, such as tissues-on-a-chip & defined microbial communities. Focus on the crew response to elevated CO2 over MoBE considerations. Assess how direct contact with the hypercapnic environment affects skin microbiome dynamics.

retrospective↗
NASA NTRS2012

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after

Shastry, Rohit↗
NASA NTRS2012

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after groove penetration.

Shastry, Rohit↗
NASA NTRSDate not supplied

Uncovering Hazards Using a Multi-Objective Optimization to Explore the Faulty State-Space

Considering resilience when designing complex engineered systems is crucial to ensure the system is safe under unexpected hazardous scenarios. Traditional risk-based approaches, such as Failure Modes and Effects Analysis (FMEA) are useful for designing the system to mitigate hazardous scenarios that can be identified by the designer, but often require experience or prior knowledge of system failures to generate. More recently, researchers have developed simulation tools that enable the designer to model large sets of hazardous scenarios (driven by both internal faults and external factors) through simulation. While these tools enable a wider scope of fault modes to be evaluated (e.g., by injecting combined set of fault modes or injecting modes at different times), the resulting assessments (like FMEA) still require knowledge of the specific modes to be evaluated. However, failure to analyze a wide variety of fault scenarios can lead to an incomplete picture of the system resilience, especially to "surprise events'' which may be difficult for the designer to identify and predict beforehand. To overcome this challenge, previous work developed a fault sampling approach for resilience simulations which would procedurally-generate a wide variety of potential faults by systematically perturbing the health states of the system. While the resulting fault modes generated covered a much larger space hazards than would be otherwise considered (and identified many unique failure trajectories which would not have otherwise been identified), it also significantly increased the computational cost of the analysis and resulted in the simulation and analysis of a large set of essentially duplicate scenarios. Additionally, as the number of dimensions in the faulty state-space increases, the full elaboration of possible modes becomes computationally infeasible, justifying the use of a more targeted search. To resolve this limitation, this work proposes the use of a multiobjective optimization algorithm to search the health state space for potential fault modes that are both (1) hazardous and (2) unique. To solve this type of problem, this work proposes the use of a cooperative co-evolutionary algorithm. To demonstrate this approach, it will be applied to a model of an autonomous rover which uses line markings to navigate, focusing on potential hazards in the drive system which could cause the rover to crash. To determine the merit of the approach, it will further be compared with the previously-presented range elaboration approach and a random mode generation approach on the basis of computational efficiency and found modes.

Resilience↗
NASA NTRS2022

Thermal Imaging of Dust Hiding the Black Hole in NGC 1068

In the widely accepted ‘unified model’1 solution of the classification puzzle of active galactic nuclei, the orientation of a dusty accretion torus around the central black hole dominates their appearance. In ‘type-1’ systems, the bright nucleus is visible at the centre of a face-on torus. In ‘type-2’ systems the thick, nearly edge-on torus hides the central engine. Later studies suggested evolutionary effects2 and added dusty clumps and polar winds3 but left the basic picture intact. However, recent high-resolution images4 of the archetypal type-2 galaxy NGC 10685,6, suggested a more radical revision. The images displayed a ring-like emission feature that was proposed to be hot dust surrounding the black hole at the radius where the radiation from the central engine evaporates the dust. That ring is too thin and too far tilted from edge-on to hide the central engine, and ad hoc foreground extinction is needed to explain the type-2 classification. These images quickly generated reinterpretations of the dichotomy between types 1 and 27,8. Here we present new multi-band mid-infrared images of NGC 1068 that detail the dust temperature distribution and reaffirm the original model. Combined with radio data ( J.F.G. and C.M.V.I., manuscript in preparation), our maps locate the central engine that is below the previously reported ring and obscured by a thick, nearly edge-on disk, as predicted by the unified model. We also identify emission from polar flows and absorbing dust that is mineralogically distinct from that towards the Milky Way centre.

Violeta Gamez Rosas↗
NASA NTRS2014

Water Transport and the Evolution of CM Parent Bodies

Extraterrestrial water-bearing minerals are of great importance both for understanding the formation and evolution of the solar system and for supporting future human activities in space. Asteroids are the primary source of meteorites, many of which show evidence of an early heating episode and varying degrees of aqueous alteration. The origin and characterization of hydrated minerals (minerals containing H2O or OH) among both the main-belt and near-earth asteroids is important for understanding a wide range of solar system formation and evolutionary processes, as well as for planning for human exploration. Current hypotheses postulate asteroids began as mixtures of water ice and anhydrous silicates. A heating event early in solar system history was then responsible for melting the ice and driving aqueous alteration. The link between asteroids and meteorites is forged by reflectance spectra, which show 3-μm bands indicative of bound OH or H2O on the C-class asteroids, which are believed to be the parent bodies of the carbonaceous chondrites in our collections. The conditions at which aqueous alteration occurred in the parent bodies of carbonaceous chondrites are thought to be well-constrained: at 0-25 C for less than 15 Myr after asteroid formation. In previous models, many scenarios exhibit peak temperatures of the rock and co-existing liquid water in more than 75 percent of the asteroid's volume rising to 150 C and higher, due to the exothermic hydration reactions triggering a thermal runaway effect. However, even in a high porosity, water-saturated asteroid very limited liquid water flow is predicted (distances of 100's nm at most). This contradiction has yet to be resolved. Still, it may be possible for water to become liquid even in the near-surface environment, for a long enough time to drive aqueous alteration before vaporizing or freezing then subliming. Thus, we are using physics- and chemistry-based models that include thermal and fluid transport as well as the effects of relevant chemical reactions, to investigate whether formation of hydrated minerals can occur in the surface and near-surface environments of carbonaceous type asteroids. These models will elucidate how the conditions within the parent body that cause internal aqueous alteration play themselves out at the asteroid's surface. We are using our models to determine whether the heat budget of 20-100-km bodies is sufficient to bring liquid water to the near-surface and cause mineral alteration, or whether additional heat input at the surface (i.e, by impacts) is needed to provide a transient liquid water source for mineral hydration without large- scale liquid water transport.

Coker, R.↗
DOE OSTI2024

Machine learning assisted search for Fe–Co–C ternary compounds with high magnetic anisotropy

We employ a machine learning (ML)-guided framework to explore rare earth free magnetic materials, specifically focusing on Fe–Co–C ternary compounds for potential use in permanent magnets. Utilizing a specifically trained crystal graph convolutional neural network model, we efficiently screen a vast space of nearly a million substitutional structures to select 620 promising structures for further investigation by first-principles calculation. We predict five low-energy metastable Fe–Co–C compounds with formation energy less than 150 meV/atom above the convex hull. These compounds exhibit high magnetization (Js > 1.0 T) and significant magnetic anisotropy (K1 > 1.0 MJ/m3), making them promising candidates for permanent magnet applications. The phonon calculations indicate these compounds are dynamically stable. Our ML-guided framework demonstrates the utility of rapidly identifying novel materials with tailored magnetic properties.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Asymptotic Giant Branch stars as a source of short-lived radioactive nuclei in the solar nebula

We carried out a theoretical evaluation of the contribution of Asymptotic Giant Branch (AGB) stars to some short-lived (10(exp 6) less than or equal to Tau-bar less than or equal to 2 x 10(exp 7) yr) isotopes in the Interstellar Medium (ISM) and in the early solar system using stellar model calculations for thermally pulsing evolutionary phases of low-mass stars. The yields of s-process nuclei in the convective He-shell for different neutron exposures tau(sub 0) were obtained, and AGB stars were shown to produce several radioactive nuclei (especially Pd-107, Pb-205, Fe-60, Zr-93, Tc-99, Cs-135, and Hf-182) in diferent amounts. Assuming either contamination of the solar nebula from a single AGB star or models for continuous injection and mixing from many stars into the ISM, we calculate the ratios of radioactive to stable nuclei at the epoch of the Sun's formation. The dilution factor between the AGB ejecta and the early solar system matter is obtained by matching the observed Pd-107/Pd-108 and depends on the value of tau(sub 0). It is found that small masses M(sub He) of He-shell material (10(exp -4)-10(exp -7) solar mass) enriched in s-process nuclei are sufficient to contaminate 1 solar mass of the ISM to produce the Pd-107 found in the early solar system. Predictions are made for all of the other radioactive isotopes. The optimal model to explain several observed radioactive species at different states of the proto-solar nebula involves a single AGB star with a low neutron exposure (tau(sub 0) = 0.03 mbarn(sup -1)) which contaminated the cloud with a dilution factor of M(sub He)/solar mass approximately 1.5 x 10(exp -4). This will also contribute newly synthesized stable s-process nuclei in the amount of approximately 10(exp -4) of their abundances already present in the proto-solar cloud. Variations in the degree of homogenization (approximately 30%) of the injected material may account for some of the small general isotopic anomalies found in meteorites. It is also found that Fe-60 is produced in small but significant quantities that may be sufficient to explain the observations if the time elapsed delta from the contamination of the ISM to the formation of protoplanetary bodies is not higher than delta = 5 x 10(exp 6) yr. If delta is longer, up to 10 x 10(exp 6) yr, this would require the single AGB star to experience enhanced neutron densities (n(sub n) approximately 3 x 10(exp 9)n/cu cm) in the s-processing zone in order to compensate for the branching at Fe-59. The alternative model of long-term continuous ejection of matter from many AGB stars does not appear to match the observations. We also estimate the Al-26 production from the H-shell and find that the Al-26 abundance in the early solar system may be readily explained in a self-consistent manner. Moreover, Al-26 from AGB stars may contribute substantially to the galactic Al-26 gamma-source, while no significant gamma-flux from Co-60 (deriving from Fe-60 decay) is to be expected.

Wasserburg, G. J.↗
NASA NTRS1999

Integrated Modeling Tools for Thermal Analysis and Applications

Integrated modeling of spacecraft systems is a rapidly evolving area in which multidisciplinary models are developed to design and analyze spacecraft configurations. These models are especially important in the early design stages where rapid trades between subsystems can substantially impact design decisions. Integrated modeling is one of the cornerstones of two of NASA's planned missions in the Origins Program -- the Next Generation Space Telescope (NGST) and the Space Interferometry Mission (SIM). Common modeling tools for control design and opto-mechanical analysis have recently emerged and are becoming increasingly widely used. A discipline that has been somewhat less integrated, but is nevertheless of critical concern for high precision optical instruments, is thermal analysis and design. A major factor contributing to this mild estrangement is that the modeling philosophies and objectives for structural and thermal systems typically do not coincide. Consequently the tools that are used in these discplines suffer a degree of incompatibility, each having developed along their own evolutionary path. Although standard thermal tools have worked relatively well in the past. integration with other disciplines requires revisiting modeling assumptions and solution methods. Over the past several years we have been developing a MATLAB based integrated modeling tool called IMOS (Integrated Modeling of Optical Systems) which integrates many aspects of structural, optical, control and dynamical analysis disciplines. Recent efforts have included developing a thermal modeling and analysis capability, which is the subject of this article. Currently, the IMOS thermal suite contains steady state and transient heat equation solvers, and the ability to set up the linear conduction network from an IMOS finite element model. The IMOS code generates linear conduction elements associated with plates and beams/rods of the thermal network directly from the finite element structural model. Conductances for temperature varying materials are accommodated. This capability both streamlines the process of developing the thermal model from the finite element model, and also makes the structural and thermal models compatible in the sense that each structural node is associated with a thermal node. This is particularly useful when the purpose of the analysis is to predict structural deformations due to thermal loads. The steady state solver uses a restricted step size Newton method, and the transient solver is an adaptive step size implicit method applicable to general differential algebraic systems. Temperature dependent conductances and capacitances are accommodated by the solvers. In addition to discussing the modeling and solution methods. applications where the thermal modeling is "in the loop" with sensitivity analysis, optimization and optical performance drawn from our experiences with the Space Interferometry Mission (SIM), and the Next Generation Space Telescope (NGST) are presented.

Milman, Mark H.↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗
NASA NTRS2019

A Giant Impact as the Likely Origin of Different Twins in the Kepler-107 Exoplanet System

Measures of exoplanet bulk densities indicate that small exoplanets with radius less than 3 Earth radii (R(sub ⊕)) range from low-density sub-Neptunes containing volatile elements to higher-density rocky planets with Earth-like or iron-rich (Mercury-like) compositions. Such astonishing diversity in observed small exoplanet compositions may be the product of different initial conditions of the planet-formation process or different evolutionary paths that altered the planetary properties after formation. Planet evolution may be especially affected by either photoevaporative mass loss induced by high stellar X-ray and extreme ultraviolet (XUV) flux or giant impacts. Although there is some evidence for the former, there are no unambiguous findings so far about the occurrence of giant impacts in an exoplanet system. Here, we characterize the two innermost planets of the compact and near-resonant system Kepler-107 (ref. 9). We show that they have nearly identical radii (about 1.5–1.6R(sub ⊕)), but the outer planet Kepler-107 c is more than twice as dense (about 12.6 g cm–3) as the innermost Kepler-107 b (about 5.3 g cm−3). In consequence, Kepler-107 c must have a larger iron core fraction than Kepler-107 b. This imbalance cannot be explained by the stellar XUV irradiation, which would conversely make the more-irradiated and less-massive planet Kepler-107 b denser than Kepler-107 c. Instead, the dissimilar densities are consistent with a giant impact event on Kepler-107 c that would have stripped off part of its silicate mantle. This hypothesis is supported by theoretical predictions from collisional mantle stripping, which match the mass and radius of Kepler-107 c.

Bonomo, Aldo S.↗
NASA NTRS2014

End-of-Test Performance and Wear Characterization of NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test

The NASA's Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to quantify the thruster propellant throughput capability. Testing was recently completed in February 2014, with the thruster accumulating 51,184 hours of operation, processing 918 kg of xenon propellant, and delivering 35.5 MN-s of total impulse.As part of the test termination procedure, a comprehensive performance characterization was performed across the entire NEXT throttle table. This was performed prior to planned repairs of numerous diagnostics that had become inoperable over the course of the test. After completion of these diagnostic repairs in November 2013, a comprehensive end-of-test performance and wear characterization was performed on the test article prior to exposure to atmosphere. These data have confirmed steady thruster performance with minimal degradation as well as mitigation of numerous life limiting mechanisms encountered in the NSTAR design. Component erosion rates compare favorably to pretest predictions based on semi-empirical models used for the thruster service life assessment. Additional data relating to ion beam density profiles, facility backsputter rates, facility backpressure effects on thruster telemetry, and modulation of the neutralizer keeper current are presented as part of the end-of-test characterization. Presently the test article for the NEXT LDT has been exposed to atmosphere and placed within a clean room environment, with post-test disassembly and inspection underway.

wear tests↗
NASA NTRS2009

NEXT Long-Duration Test Neutralizer Performance and Erosion Characteristics

The NASA's Evolutionary Xenon Thruster (NEXT) program is developing the next-generation ion propulsion system with significant enhancements beyond the state-of-the-art to provide future NASA science missions with enhanced capabilities at a low total development cost. A Long-Duration Test (LDT) was initiated in June 2005, to verify the NEXT propellant throughput capability to a qualification-level of 450 kg, 1.5 times the anticipated throughput requirement of 300 kg per thruster based on mission analyses. As of September 2, 2009, the thruster has accumulated 24,400 hr of operation with extensive durations at the following input powers: 6.9, 4.7, 1.1, and 0.5 kW. The thruster has processed 434 kg of xenon, surpassing the NASA Solar Technology Application Readiness (NSTAR) program thruster propellant throughput demonstrated during the extended life testing of the Deep Space 1 flight spare ion thruster and approaching the NEXT development qualification throughput goal of 450 kg. The NEXT LDT has demonstrated a total impulse of 16.1 10(exp 6zzz0 N s; the highest total impulse ever demonstrated by an ion thruster. A reduction in neutralizer flow margin has been the only appreciable source of thruster performance degradation. The behavior of the neutralizer is not easily predicted due to both erosion and deposition observed in previous wear tests. Spot-to-plume mode transition flow data and in-situ erosion results for the LDT neutralizer are discussed. This loss of flow margin has been addressed through a combination of a design change in the prototype-model neutralizer to increase flow margin at low emission current and to update the NEXT throttle table to ensure adequate flow margin as a function of propellant throughput processed. The new throttle table will be used for future LDT operations. The performance of the NEXT LDT neutralizer is consistent with that observed for long-life hollow cathodes. The neutralizer life-limiting failure modes are progressing as expected and the neutralizer data indicate none of the neutralizer failures are imminent.

Herman, Daniel A.↗
DOE OSTI2024

Characterizing suburban soil and microbial properties along a soil age chronosequence

Abstract Rapid urbanization is drastically altering ecosystem processes in landscapes around the world. In particular, suburban residential neighborhoods comprise novel ecosystems with water and nutrient inputs that differ greatly from the surrounding land area. These impacts generate concern over the sustainability of urban ecosystems, especially whether they will be characterized by net carbon gain or loss over time. To address this knowledge gap, we established a chronosequence of residential yards in Southern California to test how urban soils change after development. We predicted that urbanized soils would experience shifts in physical characteristics and microbial function over time consistent with ecological succession theory, but residential soils would maintain novel moisture and nutrient regimes compared to undeveloped soils, never “recovering” to a pre‐developed state. We compared different vegetation types to quantify impacts of homeowner landscaping choices and characterized yard soils and their microbial communities. We found that yard soils were nutrient‐ and moisture‐enriched compared to an adjacent undeveloped ecosystem, and turfgrass was associated with higher levels of water and nitrogen. Despite high respiration rates, yard soils accumulated carbon and nitrogen over time. We conclude that suburban residential soils comprise dynamic and heterogeneous ecosystems that are highly influenced by landscaping choices and management practices, and warrant closer study at small management‐relevant scales.

Suratt, Andie [Department of Ecology and Evolution↗
NASA NTRS2011

Thoughts Without Content are Empty, Intuitions Without Concepts are Blind - Determinism and Contingency Revisited

Was the emergence of life a predictable outcome of chemical evolution on earth? Could evolution produce life very different from ours? These are one of the oldest questions in the field of the origin of life that not only have broad philosophical implications but also impact how we approach the problem from the methodological standpoint. Framing the issue in terms of the dichotomy between contingency and determinism is not a fortunate because these two terms in their conventional meaning are neither mutually exclusive nor jointly exhaustive. Determinism, represented in natural sciences by Newtonian physics, relies on the assumption that every event is causally determined by a chain of previous events. In the context of the origin of life it means that once the initial conditions on the early earth have been specified further evolution follows inevitably. Considering uncertainties about conditions on the prebiotic earth, many plausible sets of initial conditions can be defined, each followed by a separate deterministic trajectory. This conventional understanding of determinism does not admit contingency. Further, it has no implications for evaluating how many sets of initial conditions lead to the emergence of life. It appears that a better framing of the problem is as follows: given plausible sets of initial conditions on the early earth how probable and broadly spread are evolutionary trajectories that lead to life? Instead of undertaking an impossible task of specifying microscopic initial conditions for all components of the system one uses a reduced representation of this system and specify only a small set of essential macroscopic parameters, values (or ranges of values) of which can be identified, inferred or estimated from experiment, theory or historical record. The following evolutionary trajectories are still governed by laws of physics and chemistry but become probabilistic and "contingency" is admitted as variations in other variables in the system. A similar reasoning is common in other fields of science, for example in statistical mechanics. Some trajectories lead to life, perhaps in different forms, whereas others do not. Of our true interest is the ratio of these two outcomes. The issue of determinism does not directly enter the picture. The debate about the likelihood of the emergence of life is quite old. One view holds that the origin of life is an event governed by chance, and the result of so many random events (contingencies) is unpredictable. This view was eloquently expressed by Monod. In his book "Chance or Necessity" he argued that life was a product of "nature's roulette." In an alternative view, expressed in particular by deDuve and Morowitz, the origin of life is considered a highly probable or even inevitable event (although its details need not be determined in every respect). Only in this sense the origin of life can be considered a "deterministic event".

Pohorille, Andrew↗
NASA NTRS2001

Automating Trend Analysis for Spacecraft Constellations

Spacecraft trend analysis is a vital mission operations function performed by satellite controllers and engineers, who perform detailed analyses of engineering telemetry data to diagnose subsystem faults and to detect trends that may potentially lead to degraded subsystem performance or failure in the future. It is this latter function that is of greatest importance, for careful trending can often predict or detect events that may lead to a spacecraft's entry into safe-hold. Early prediction and detection of such events could result in the avoidance of, or rapid return to service from, spacecraft safing, which not only results in reduced recovery costs but also in a higher overall level of service for the satellite system. Contemporary spacecraft trending activities are manually intensive and are primarily performed diagnostically after a fault occurs, rather than proactively to predict its occurrence. They also tend to rely on information systems and software that are oudated when compared to current technologies. When coupled with the fact that flight operations teams often have limited resources, proactive trending opportunities are limited, and detailed trend analysis is often reserved for critical responses to safe holds or other on-orbit events such as maneuvers. While the contemporary trend analysis approach has sufficed for current single-spacecraft operations, it will be unfeasible for NASA's planned and proposed space science constellations. Missions such as the Dynamics, Reconnection and Configuration Observatory (DRACO), for example, are planning to launch as many as 100 'nanospacecraft' to form a homogenous constellation. A simple extrapolation of resources and manpower based on single-spacecraft operations suggests that trending for such a large spacecraft fleet will be unmanageable, unwieldy, and cost-prohibitive. It is therefore imperative that an approach to automating the spacecraft trend analysis function be studied, developed, and applied to missions such as DRACO with the intent that mission operations costs be significantly reduced. The goal of the Constellation Spacecraft Trend Analysis Toolkit (CSTAT) project is to serve as the pathfinder for a fully automated trending system to support spacecraft constellations. The development approach to be taken is evolutionary. In the first year of the project, the intent is to significantly advance the state of the art in current trending systems through improved functionality and increased automation. In the second year, the intent is to add an expert system shell, likely through the adaptation of an existing commercial-off-the-shelf (COTS) or government-off-the-shelf (GOTS) tool to implement some level of the trending intelligence that humans currently provide in manual operations. In the third year, the intent is to infuse the resulting technology into a near-term constellation or formation-flying mission to test it and gain experience in automated trending. The lessons learned from the real missions operations experience will then be used to improve the system, and to ultimately incorporate it into a fully autonomous, closed-loop mission operations system that is truly capable of supporting large constellations. In this paper, the process of automating trend analysis for spacecraft constellations will be addressed. First, the results of a survey on automation in spacecraft mission operations in general, and in trending systems in particular will be presented to provide an overview of the current state of the art. Next, a rule-based model for implementing intelligent spacecraft subsystem trending will be then presented, followed by a survey of existing COTS/GOTS tools that could be adapted for implementing such a model. The baseline design and architecture of the CSTAT system will be presented. Finally, some results obtained from initial software tests and demonstrations will be presented.

Davis, George↗