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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of High-Temperature Martensitic Steels for Heavy-Duty Diesel Piston Applications

Five different commercially available high-temperature martensitic steels were evaluated for use in a heavy-duty diesel engine piston application and compared to existing piston alloys 4140 and microalloyed steel 38MnSiVS5 (MAS). Finite element analyses (FEA) were performed to predict the temperature and stress distributions for severe engine operating conditions of interest, and thus aid in the selection of the candidate steels. Complementary material testing was conducted to evaluate the properties relevant to the material performance in a piston. The elevated temperature strength, strength evolution during thermal aging, and thermal property data were used as inputs into the FEA piston models. Additionally, the long-term oxidation performance was assessed relative to the predicted maximum operating temperature for each material using coupon samples in a controlled-atmosphere cyclic-oxidation test rig. A current commercial steel piston alloy, quenched and tempered martensitic steel 4140, was tested in a single-cylinder research engine for a baseline oxidation and mechanical performance assessment using an abbreviated (50h) durability test plan. The predicted suitability of a candidate piston material in an engine is primarily based on its elevated temperature strength, oxidation resistance, and the complex influence of thermal conductivity, the latter of which is substantially lower for the candidate materials considered in this research relative to the traditional alloys. Although the lower thermal conductivity causes the candidate alloys to operate in higher temperature ranges under identical engine operating conditions and piston geometries, increasing the likelihood of partially or completely negating their strength and oxidation resistance advantages relative to 4140 and MAS steels, this evaluation indicates that several of the candidate piston alloys are predicted to enable improved oxidation resistance under more severe engine operating conditions relative to the current piston materials. However, further evaluation is required to determine if the elevated temperature fatigue strength and durability of these alloys are suitable for more severe engine conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance

Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events.

Geology↗
DOE OSTI2022

An Evaluation of Tropical Cyclone Rainfall Structures in the HighResMIP Simulations against Satellite Observations

This study evaluates tropical cyclone (TC) rainfall structures in the CMIP6 HighResMIP global climate model (GCM) simulations against satellite rainfall retrievals. Here, we specifically focus on TCs within the deep tropics (25°S–25°N). Analysis of TC rain rate composites indicates that in comparison to the satellite observations at the same intensity, many HighResMIP simulations tend to overproduce rain rates around TCs, in terms of both maximum rain rate magnitude and area-averaged rain rates. In addition, as model horizontal resolution increases, the magnitude of the peak rain rate appears to increase. However, the area-averaged rain rates decrease with increasing horizontal resolution, partly due to the TC eyewall being located closer to the TC center, thus occupying a smaller area and contributing less to the area-averaged rain rates. The effect of ocean coupling is to lower the TC rain rates, bringing them closer to the satellite observations, due to reduced horizontal moisture flux convergence and surface latent heat flux beneath TCs. Examination of horizontal rain rate distributions indicates that vertical wind shear–induced rainfall asymmetries in HighResMIP-simulated TCs are qualitatively consistent with the observations. In addition, a positive relationship is observed between the area-averaged inner-core rainfall and TC intensification likelihoods across the HighResMIP simulations, as GCM simulations producing stronger TCs more frequently have the greater rainfall close to the center, in agreement with previous theoretical and GCM simulation results.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Mass and Volume Optimization of Space Flight Medical Kits

Resource allocation is a critical aspect of space mission planning. All resources, including medical resources, are subject to a number of mission constraints such a maximum mass and volume. However, unlike many resources, there is often limited understanding in how to optimize medical resources for a mission. The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulates outcomes and describes the impact of medical events in terms of lost crew time, medical resource usage, and the potential for medically required evacuation. Previously published work describes an approach that uses the IMM to generate optimized medical kits that maximize benefit to the crew subject to mass and volume constraints. We improve upon the results obtained previously and extend our approach to minimize mass and volume while meeting some benefit threshold. METHODS We frame the medical kit optimization problem as a modified knapsack problem and implement an algorithm utilizing dynamic programming. Using this algorithm, optimized medical kits were generated for 3 mission scenarios with the goal of minimizing the medical kit mass and volume for a specified likelihood of evacuation or Crew Health Index (CHI) threshold. The algorithm was expanded to generate medical kits that maximize likelihood of evacuation or CHI subject to mass and volume constraints. RESULTS AND CONCLUSIONS In maximizing benefit to crew health subject to certain constraints, our algorithm generates medical kits that more closely resemble the unlimited-resource scenario than previous approaches which leverage medical risk information generated by the IMM. Our work here demonstrates that this algorithm provides an efficient and effective means to objectively allocate medical resources for spaceflight missions and provides an effective means of addressing tradeoffs in medical resource allocations and crew mission success parameters.

Monte Carlo Method↗
NASA NTRS2012

Climate Change: A New Metric to Measure Changes in the Frequency of Extreme Temperatures using Record Data

Consensus on global warming is the result of multiple and varying lines of evidence, and one key ramification is the increase in frequency of extreme climate events including record high temperatures. Here we develop a metric- called "record equivalent draws" (RED)-based on record high (low) temperature observations, and show that changes in RED approximate changes in the likelihood of extreme high (low) temperatures. Since we also show that this metric is independent of the specifics of the underlying temperature distributions, RED estimates can be aggregated across different climates to provide a genuinely global assessment of climate change. Using data on monthly average temperatures across the global landmass we find that the frequency of extreme high temperatures increased 10-fold between the first three decades of the last century (1900-1929) and the most recent decade (1999-2008). A more disaggregated analysis shows that the increase in frequency of extreme high temperatures is greater in the tropics than in higher latitudes, a pattern that is not indicated by changes in mean temperature. Our RED estimates also suggest concurrent increases in the frequency of both extreme high and extreme low temperatures during 2002-2008, a period when we observe a plateauing of global mean temperature. Using daily extreme temperature observations, we find that the frequency of extreme high temperatures is greater in the daily minimum temperature time-series compared to the daily maximum temperature time-series. There is no such observable difference in the frequency of extreme low temperatures between the daily minimum and daily maximum.

Munasinghe, L.↗
DOE OSTI2022

Novel Amorphous Carbons for the Adsorption of Phosphate: Part I. Elucidation of Chemical Structure of N-Metal-Doped Chars

Due to phosphate’s necessity in agriculture and its danger to the environment, the development of adsorbents for its removal has been the subject of intensive research activity. Although the introduction of nitrogen functionality to chars and modification of biochar with metals have proven to change the character of the char structure, making it more active toward nutrients, there is no study regarding the doping of biochar with metals and nitrogen simultaneously for the adsorption of phosphates. This paper is the first of two in which we report the production, characterization, and evaluation of N-metal-doped biochars from cellulose for phosphate removal from liquid effluents. In this part, we describe the production and characterization of N-Ca-, N-Fe-, and N-Mg-doped biochars. The elemental composition and surface area of each of the materials produced is reported. Elemental and surface characterization of the chars are reported with the largest N content appearing at a temperature of 800 °C (12.5 wt %) and a maximum surface area for biochar produced at 900 °C (1314 m2/g). All of the adsorbents were visualized by scanning electron microscope (SEM), confirming that although there are some crystals on the surface of the biochar produced, most of the N, Mg, and Ca are part of the polyaromatic ring structure. Transmission electron microscope (TEM) images clearly show the formation of nanoclusters with the metals in the case of N-Fe and N-Ca biochars. The N-Mg biochars show a uniform distribution of the Mg through the carbon surface. X-ray photoelectron spectroscopy (XPS) studies of the biochars produced with metals and varying nitrogen levels clearly show Mg and Ca peaks shifting their position in the presence of N, suggesting the formation of stable structures between metals and N in the carbon polyaromatic ring system. To elucidate the nature of these structures, we conducted DFT-based calculations on different configurations of the nitrogenated structures. The calculated binding energy shifts were found to closely match the XPS experimental binding energy, confirming the likelihood of these structures in biochar. Finally, based on our experimental and modeling results, we hypothesize that an important fraction of the Mg and Ca is introduced to these biochars at the edges. Another fraction of Mg and Ca is in the form of phthalocyanine-like internal structures. More experimental studies are needed to confirm the formation of these very interesting structures and their potential use as adsorbents or catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Laboratory Directed Research and Development Program FY 2020 Annual Summary of Completed Projects

ORNL has established a program with four complementary subprograms to meet its LDRD objectives and to fulfill the particular needs of the laboratory. A provision for multiple routes of access to ORNL LDRD funds maximizes the likelihood that novel ideas with scientific and technological merit will be recognized and supported. The ORNL LDRD Program comprises the following four subprograms: 1) The Director’s R&D Program supports projects that advance research frontiers, capabilities, and expertise at ORNL in key strategic areas. 2) The Seed Program supports innovative high-risk/high-reward research to the proof-of-principle stage. 3) The Strategic Hire Program supports the research of key new staff whose expertise and capabilities address a critical strategic need for the laboratory. 4) The Distinguished Staff Fellowships assist the laboratory in bringing in exceptional early-career scientists to refresh and expand its scientific and technical expertise. The total ORNL LDRD Program budget authorized by DOE for FY 2020 was $\$$55 million. FY 2020 allocations totaled $\$$52.5 million and supported 153 projects. An additional $\$$95,827 was allocated to administrative costs for conducting proposal reviews. Overall, 96.4% of the allocated funds were spent. The expenditure of $\$$50.6 million was about 3.2% of the laboratory’s total budget of $\$$1,572 million for operating and capital expenses, which is well below the maximum of 6% allowed by DOE Order 413.2C and is in accordance with Section 309 of Division D of the Consolidated Appropriations Act.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Linking habitat suitability with a longleaf pine-hardwood model: Building a species-predictive fire-land management framework

Active management of fire-dependent ecosystems for specific species leads to complex tradeoffs, which affect conservation outcomes to other species. Therefore a multi-species evaluation of management actions is required. Habitat Suitability Models (HSMs) can help in predicting the likelihood of species occurrence using corresponding environmental variables and empirical relationships that link occurrence with specific environmental conditions. Incorporating multiple species into HSMs and relating them to habitat dynamics is crucial for ecosystems that require active management with prescribed fire. To address this issue, we developed multi-species HSM driven within an existing population model of the longleaf pine-hardwood ecosystem to assess the suitability of an ecosystem given different fire management strategies and environmental conditions. The population model used in this study provides spatial and temporal changes of longleaf pine-hardwood habitat structure in response to fire. These habitat values are used by the HSM to calculate habitat suitability for three threatened and endangered faunal species of this ecosystem, which all thrive with frequent fire, but have unique habitat requirements. Transient habitat conditions are traced to predict longleaf pine ecosystem trajectories under various management strategies, thereby evaluating current land management actions, such as thinning or prescribed fire frequencies. We tested a suite of environmental conditions to emphasize the sensitivity of the species to different fire management actions. The results of our modeling suggest that maximum suitable habitat for all three species can be achieved with fire frequency occurring at approximately once every three years. The modeling results support current management actions and provide a new habitat assessment tool that incorporates ecological factors for multiple species, thus providing for habitat optimization.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy Data Fusion to Map Global Surface Ozone Concentration and Associated Uncertainty

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R 2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m −3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Ozone↗
DOE OSTI2020

Characterization of Partial Charge Collection Induced by Neutron Damage in High-Purity Germanium Detectors

This paper investigates the correlation of damage induced by neutron interactions and degradation in the spectra of HPGe detectors. As neutrons kinetically interact with germanium crystals, they create interstitial and vacancy defects within the lattice. These defects then interfere with the charge migration of electron-hole pairs and reduce resolution in the observed energy spectrum. The partial charge collection produces observable spectral changes by increasing the peak width and reducing resolution (full width half maximum). A detailed characterization using various check sources was performed before and after iterations of neutron exposure in order to observe the effects of the neutron damage. An additional set of measurements was performed along with characterizations to show the detector’s response at discrete locations on the HPGe crystal. This was done to observe how the spectrum changes when the gamma rays are isolated to regions of various thicknesses of germanium. In order to impart damage, the detector was placed inside a californium shuffler with the face of the detector against the guide tube for the 252 Cf source. For irradiation of the HPGe, the source was then positioned in front of the face of the detector using the stepper motor of the shuffler. The neutron exposure time intervals were recorded and increased based on the initial damage observed. An MCNP simulation was performed to estimate the amount of interactions that occurred in the germanium crystal to ensure enough damage had occurred. Studying the effects that neutron damage imparts on a bullet-type HPGe detector can help provide necessary data to estimate total neutron exposure limits, reduce the likelihood of decisions made on suspect data, and aid in diagnostics of a damaged detector.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

The Impact of Delayed Communication on NASA’s Human-Systems Operations: Preliminary Results of a Systematic Review

Throughout the history of human spaceflight, NASA has relied on a team of ground-based experts on Earth to manage its missions, vehicles, and crews to ensure crew safety and mission success. However, as missions progress beyond low-Earth orbit (LEO), this paradigm of dependence on ground must evolve. Beyond LEO, in missions to the moon and Mars, crews will confront new challenges: limited evacuation options, reduced resupply capabilities, and significant communication delays that impede real-time support from experts on the ground. This reduction in ground support amplifies the likelihood that crews will be unable to adequately respond to unanticipated, safety-critical events. Understanding the scope of these risks and identifying effective countermeasures hinges on understanding the impact of communication delays on complex operations, especially in urgent, unforeseen events. Real-time communication currently provides the crew with continuous access to a large, extensively resourced ground team skilled in anomaly resolution. However, as communication delays grow, the need to transfer some responsibilities from ground experts to onboard crew becomes evident. NASA has been exploring this shift in operational responsibilities and its effectiveness in managing complex operations for decades. Nevertheless, a comprehensive understanding of the specific challenges posed by communication delays and the necessary countermeasures to mitigate them remains a gap. In this paper, we present an update on our systematic review of the literature on communication delays, the first in-depth review since 2013 (Rader et al.). We introduce a coding taxonomy to capture key constructs from papers of interest and discuss preliminary findings. These preliminary results suggest two significant research gaps: limited studies have been conducted 1) with lunar-like latencies and 2) on problem-solving strategies for the maximum latencies expected in Mars missions. We outline plans and propose recommendations to address these gaps through ongoing and future research.

human-systems integration↗
NASA NTRSDate not supplied

The Impact of Delayed Communications on NASA's Human-Systems Operations: Preliminary Results of a Systematic Review

Throughout the history of human spaceflight, NASA has relied on a team of ground-based experts on Earth to manage its missions, vehicles, and crews to ensure crew safety and mission success. However, as missions progress beyond low-Earth orbit (LEO), this paradigm of dependence on ground must evolve. Beyond LEO, in missions to the moon and Mars, crews will confront new challenges: limited evacuation options, reduced resupply capabilities, and significant communication delays that impede real-time support from experts on the ground. This reduction in ground support amplifies the likelihood that crews will be unable to adequately respond to unanticipated, safety-critical events. Understanding the scope of these risks and identifying effective countermeasures hinges on understanding the impact of communication delays on complex operations, especially in urgent, unforeseen events. Real-time communication currently provides the crew with continuous access to a large, extensively resourced ground team skilled in anomaly resolution. However, as communication delays grow, the need to transfer some responsibilities from ground experts to onboard crew becomes evident. NASA has been exploring this shift in operational responsibilities and its effectiveness in managing complex operations for decades. Nevertheless, a comprehensive understanding of the specific challenges posed by communication delays and the necessary countermeasures to mitigate them remains a gap. In this paper, we present an update on our systematic review of the literature on communication delays, the first in-depth review since 2013 (Rader et al.). We introduce a coding taxonomy to capture key constructs from papers of interest and discuss preliminary findings. These preliminary results suggest two significant research gaps: limited studies have been conducted 1) with lunar-like latencies and 2) on problem-solving strategies for the maximum latencies expected in Mars missions. We outline plans and propose recommendations to address these gaps through ongoing and future research.

earth-independence↗
NASA NTRS2020

MSL Telecom Automated Anomaly Detection

The Mars Science Laboratory (MSL) Telecom Operations Team at the Jet Propulsion Laboratory (JPL) has implemented a machine learning system in order to automate the anomaly detection process as a part of daily operations. Machine learning enables reliable detection of anomalies in Telecom-related telemetry and automated reporting of Telecom subsystem status, resulting in an 90% reduction in team workload and improved anomaly detection reliability. At present, machine learning methods are used to detect: 1. Anomalous long-term trends in telemetry data 2. Anomalous time-domain evolution of telemetry values Both types of anomalies pose their own unique challenges that are addressed in different ways. In the first case, long term trending of daily minima, maximum, and mean telemetry values in temperatures, currents, voltages, and radio frequency (RF) power levels is used in addition to hard threshold safety checks to look for changes in long-term equipment health and performance. Long-term trending methods allow for ordinary seasonal variations in these quantities caused by temperature changes over the course of the Martian year while allowing operators to determine whether current performance remains in line with historical values from previous years. Changes in long-term trends can provide important insights into the health and status of the rover's on-board systems as well as valuable early warning if subtle degradation begins to take hold. But while trending of daily statistics is valuable, it does not detect anomalies in the short-term time evolution of data over the course of minutes or hours during a day, and this task is handled with short-term shape analysis. Principal components analysis (PCA) has been found to provide robust detection of short-term anomalies, and several examples of the use of PCA to detect actual anomalous events will be provided here. In using PCA, we use both the percentage of explained variance and also a log likelihood test on the PCA expansion coefficients to flag telemetry data for human review. Previous work in the field of spacecraft anomaly detection includes [1] for MSL and [2] for some other JPL missions.

Mukai, Ryan↗
DOE OSTI2020

Planck 2018 results - VIII. Gravitational lensing

We present measurements of the cosmic microwave background (CMB) lensing potential using the final Planck 2018 temperature and polarization data. Using polarization maps filtered to account for the noise anisotropy, we increase the significance of the detection of lensing in the polarization maps from 5σ to 9σ. Combined with temperature, lensing is detected at 40σ. We present an extensive set of tests of the robustness of the lensing-potential power spectrum, and construct a minimum-variance estimator likelihood over lensing multipoles 8 ≤ L ≤ 400 (extending the range to lower L compared to 2015), which we use to constrain cosmological parameters. We find good consistency between lensing constraints and the results from the Planck CMB power spectra within the ΛCDM model. Combined with baryon density and other weak priors, the lensing analysis alone constrains σ 8 Ωm 0.25 = 0.589 ± 0.020 (1σ errors). Also combining with baryon acoustic oscillation data, we find tight individual parameter constraints, σ8 = 0.811 ± 0.019, H0 = 67.9-1.3+1.2 km s -1 Mpc -1 , and Ω m = 0.303 -0.018 +0.016 . Combining with Planck CMB power spectrum data, we measure σ 8 to better than 1% precision, finding σ 8 = 0.811 ± 0.006. CMB lensing reconstruction data are complementary to galaxy lensing data at lower redshift, having a different degeneracy direction in σ 8 - Ω m space; we find consistency with the lensing results from the Dark Energy Survey, and give combined lensing-only parameter constraints that are tighter than joint results using galaxy clustering. Using the Planck cosmic infrared background (CIB) maps as an additional tracer of high-redshift matter, we make a combined Planck-only estimate of the lensing potential over 60% of the sky with considerably more small-scale signal. We additionally demonstrate delensing of the Planck power spectra using the joint and individual lensing potential estimates, detecting a maximum removal of 40% of the lensing-induced power in all spectra. The improvement in the sharpening of the acoustic peaks by including both CIB and the quadratic lensing reconstruction is detected at high significance.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1996

Early Energetic Particle Irradiation of the HED Parent Body Regolith

Previous studies have shown that many individual grains within the dark phase of the Kapoeta howardite were irradiated with energetic particles while residing on the surface of the early HED regolith. Particle tracks in these grains vary in density by more than an order of magnitude and undoubtedly were formed by energetic heavy (Fe) ions associated with early solar flares. Early Irradiation of HED Regolith: Concentrations of excess Ne alone are not sufficient to decide between competing galactic and solar irradiation models. However, from recent studies of depth samples of oriented lunar rocks, we have shown that the cosmogenic 21-Ne/22-Ne ratio produced in feldspar differs substantially between Galactic Cosmic Radiation (GCR) and solar protons, and that this difference is exactly that predicted from cross-section data. Using Ne literature data and new isotopic data we obtained on acid-etched, separated feldspar from both the light and dark phases of Kapoeta, we derive 21-Ne/22-Ne = 0.80 for the recent GCR irradiation and 21-Ne/22-Ne = 0.68 for the early regolith irradiation. This derived ratio indicates that the early Ne production in the regolith occurred by both galactic and solar protons. If we adopt a likely one-component regolith model in which all grains were exposed to galactic protons but individual grains had variable exposure to solar protons, we estimate that this early GCR irradiation lasted for about 3-6 m.y. More complex two-component regolith models involving separate solar and galactic irradiation would permit this GCR age to be longer. Higher-energy solar protons would permit the GCR to be longer. Higher-energy solar protons would permit the GCR age to be shorter. Further, cosmogenic 126(Xe) in Kapoeta dark is no more than a factor of about 2 higher than that observed in Kapoeta light. Because 126(Xe) can only be formed by galactic protons and not solar protons, these data support a short GCR irradiation for the HED regolith. This would also be the maximum time peRiod for the solar irradiation. Various asteroidal regolith models, based on Monte Carlo modeling of impact rates as a function of size and on irradiation features of meteorites, predict surface exposure times of about 0.1 to 10 m.y., and depend on such factors as gravity, rock mechanical properties, and micrometeoroid flux. Because the depth at which solar Fe tracks are produced (is much less than 1 micrometer) is much less than the depth at which Solar Cosmic Rays (SCR) Ne is produced (about 1 cm), for a reasonably well-stirred HED regolith the "surface exposure time" for SCR 21-Ne production should be significantly longer than that for solar tracks and some other surface irradiation features. Enhanced Solar Proton Irradiation: For bulk samples of Kapoeta dark feldspar and a one-component regolith model, the derived ratio of 21-Ne/22-Ne = 0.68 implies that the early production ratio of SCR 21-Ne to GCR 21-Ne was about 0.5-1.5. This ratio is independent of any assumptions about the fraction of dark grains that are irradiated or of the variability in the degree of solar irradiation among grains. The 21-Ne SCR/GCR ratio indirectly derived from bulk Kapoeta pyroxene is somewhat larger, as is the ratio derived for simple two-component regolith models. Individual feldspar grains that were extensively solar irradiated would require even larger 21-Ne SCR/GCR production ratios. In contrast, the theoretical SCR/GCR production ratio for lunar feldspar with 0 g/CM2 shield ing is is less than or equal to 2, and the lowest ratio observed in near-surface samples of lunar anorthosites is less than or equal to 1. Considering the greater solar distance of Vesta (compared to the Moon), the likelihood that SCR 21-Ne was acquired under some shielding where production rates are lower, and the likelihood that the exposure time to galactic protons exceeded the exposure time to solar protons because of their very different penetration depths, the 21-Ne SCR/GCR production ratio on the HED parent body was probably < 0.1. The relatively large difference between the derived 21-Ne SCR/GCR ratio in Kapoeta dark feldspar and the estimated production ratio strongly indicates that the early solar irradiation involved a flux -20-50x the recent solar flux. This enhanced proton flux was probably associated with an overall greater solar activity in the first approximately 10(exp 7) to 10(exp 8) years of solar history.

Bogard, D. D.↗
NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗
NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗