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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Producing Next Generation Superalloys Through Advanced Characterization and Manufacturing Techniques

NASA is currently working towards developing the next generation high temperature alloys for various aerospace and energy applications. Through advanced microscopy and computational insights, a novel atomic scale strengthening mechanism was discovered in Ni-base superalloys. This new local phase transformation strengthening technique has been successfully implemented resulting in new disk alloys with substantial improvements in creep strength over current state-of-the-art. Furthermore, additive manufacturing has been leveraged to produce dispersion strengthened (DS), multi-principal element alloys (MPEA) without the use of traditional mechanical alloying or chemical reactions. This new processing technique has successfully resulted in 99.9% dense oxide dispersion strengthened NiCoCr alloy parts. High temperature mechanical testing of the DS alloys showed significant improvements in strength and ductility over the baseline NiCoCr. As a result, this recently discovered processing route opens a new alloy design and production path that is synergistic between additive manufacturing and dispersion strengthening, possibly enabling a new generation of high-performance alloys.

Smith, Timothy M.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-21952-DND

DISCOVER-AQ was a 4-year NASA project aimed to improve the interpretation of total column satellite observations to help diagnose near-surface conditions relating to air quality. During DISCOVER-AQ HSRL-2 was flown onboard the NASA Langley B200 King Air. A suite of in-situ instruments was flown onboard NASA Wallops P-3B aircraft which spiraled up and down over a number of ground stations. The two aircraft flew coordinated flight tracks, both flying over several designated ground stations with close time coincidence, allowing for colocation of measurements from the in situ instruments suite and the HSRL-2. HSRL-2 is the first multiwavelength airborne lidar system that provides profiles of 3β (backscatter)+2α(extinction),allowing the retrieval of microphysical parameters like number, surface-area, and volume concentrations, and effective radius.

Patricia Sawamura↗
NASA NTRS2020

Detection of Dynamical Instability in Titan's Thermospheric Jet

Similar to Earth, Saturn’s largest moon, Titan, possesses a system of high-altitude zonal winds (or jets) that encircle the globe. Using the Atacama Large Millimeter/submillimeter Array (ALMA) in August 2016, Lellouch et al. (2019) discovered an equatorial jet at much higher altitudes than previously known, with a surprisingly fast speed of up to∼340 m s−1, but the origin of such high velocities is not yet understood. We obtained spectrally and spatially resolved ALMA observations in May 2017 to map Titan’s 3D global wind field and compare our results with a reanalysis of the August 2016 data. Doppler wind velocity maps were derived in the altitude range∼300–1000 km (from the upper stratosphere to the thermosphere). At the highest, thermospheric altitudes, a 47% reduction in the equatorial zonal wind speed was measured over the 9-month period (corresponding toLs= 82◦–90◦on Titan). This is interpreted as due to a dramatic slowing and loss of confinement (broadening) of the recently-discovered thermospheric equatorial jet, as a result of dynamical instability. These unexpectedly-rapid changes in the upper-atmospheric dynamics are consistent with strong variability of the jet’s primary driving mechanism.

M A Cordiner↗
NASA NTRS2019

Atmospheric impacts on EDL maneuver targeting for the InSight mission and unguided Mars landers

Early in operational testing for the InSight mission to Mars, it was discovered that the final maneuver to target the entry-interface point (EIP) was unexpectedly sensitive, in both magnitude and direction, to planned atmosphere model updates that would be based on real-time measurements of the Martian atmosphere by Mars Reconnaissance Orbiter (MRO). Upon investigation, the team realized that the Phoenix mission also discovered this sensitivity during its operational testing. A further investigation identified that maneuver sensitivity to real-time atmosphere updates was a result of the fact that both the EFPA and ground target were being held fixed, constraining the maneuver in a way that forced the entry time to change in order to compensate for changes to the nominal trajectory from updating the atmosphere model. The final maneuver occurs 22 hours prior to entry, at which point it is very expensive to change entry time. The study also revealed that any unguided Mars entry, descent, and landing (EDL) mission would be impacted by this sensitivity if it used real-time atmosphere observations to model the nominal expected atmosphere used for maneuver targeting of the EIP. This paper discusses the results of that investigation and presents a number of mitigations as well as the consequences of ignoring the sensitivity.

Kipp, Devin↗
NASA NTRS2020

The First Habitable-zone Earth-sized Planet from TESS. III. Climate States and Characterization Prospects for TOI-700 d

We present self-consistent three-dimensional climate simulations of possible habitable states for the newly discovered habitable-zone Earth-sized planet TOI-700 d. We explore a variety of atmospheric compositions, pressures, and rotation states for both ocean-covered and completely desiccated planets in order to assess the planet's potential for habitability. For all 20 of our simulated cases, we use our climate model outputs to synthesize transmission spectra, combined-light spectra, and integrated broadband phase curves. These climatologically informed observables will help the community assess the technological capabilities necessary for future characterization of this planet—as well as similar transiting planets discovered in the future—and will provide a guide for distinguishing possible climate states if one day we do obtain sensitive spectral observations of a habitable planet around an M star. We find that TOI-700 d is a strong candidate for a habitable world and can potentially maintain temperate surface conditions under a wide variety of atmospheric compositions. Unfortunately, the spectral feature depths from the resulting transmission spectra and the peak flux and variations from our synthesized phase curves for TOI-700 d do not exceed 10 ppm. This will likely prohibit the James Webb Space Telescope from characterizing its atmosphere; however, this motivates the community to invest in future instrumentation that perhaps can one day reveal the true nature of TOI-700 d and to continue to search for similar planets around less distant stars.

Gabrielle Suissa↗
NASA NTRS2020

SN2020bvc: A Broad-line Type Ic Supernova with a Double-peaked Optical Light Curve and a Luminous X-Ray and Radio Counterpart

We present optical, radio, and X-ray observations of SN 2020bvc (=ASASSN-20bs, ZTF 20aalxlis), a nearby (z = 0.0252; d = 114Mpc) broad-line (BL) Type Ic supernova (SN) and the first double-peaked Ic-BL discovered without a gamma-ray burst (GRB) trigger. Our observations show that SN 2020bvc shares several properties in common with the Ic-BL SN 2006aj, which was associated with the low-luminosity gamma-ray burst (LLGRB) 060218. First, the 10 GHz radio luminosity (L(radio) ≈ 10^(37) erg/s) is brighter than ordinary core-collapse SNe but fainter than LLGRB SNe such as SN 1998bw (associated with LLGRB 980425). We model our VLA observations (spanning 13–43 days) as synchrotron emission from a mildly relativistic (v ≳ 0.3c) forward shock. Second, with Swift and Chandra, we detect X-ray emission (L(X) ≈ 10^(41) erg/s) that is not naturally explained as inverse Compton emission or part of the same synchrotron spectrum as the radio emission. Third, high-cadence (6 × per night) data from the Zwicky Transient Facility (ZTF) show a double-peaked optical light curve, the first peak from shock cooling of extended low-mass material (mass Me < 10^(-2) Mꙩ at radius Re > 10^(12) cm) and the second peak from the radioactive decay of 56Ni. SN 2020bvc is the first double-peaked Ic-BL SN discovered without a GRB trigger, so it is noteworthy that it shows X-ray and radio emission similar to LLGRB SNe. For four of the five other nearby (z ≲ 0.05) Ic-BL SNe with ZTF high-cadence data, we rule out a first peak like that seen in SN 2006aj and SN 2020bvc, i.e., that lasts ≈1 day and reaches a peak luminosity M ≈ −18. Follow-up X-ray and radio observations of Ic-BL SNe with well-sampled early optical light curves will establish whether double-peaked optical light curves are indeed predictive of LLGRB-like X-ray and radio emission.

Anna Y. Q. Ho↗
NASA NTRS2021

An Information Theory Approach to Physical Domain Discovery

The project of physics discovery is often equivalent to finding the most concise description of a physical system. The description with optimum predictive capability for a dataset generated by a physical system is one that minimizes both predictive error on the dataset and the complexity of the description. The discovery of the governing physics of a system can therefore be viewed as a mathematical optimization problem. We outline here a method to optimize the description of arbitrarily complex physical systems by minimizing the entropy of the description of the system. The Recursive Domain Partitioning (RDP) procedure finds the optimum partitioning of each physical domain into subdomains, and the optimum predictive function within each subdomain. Penalty functions are introduced to limit the complexity of the predictive function within each domain. Examples are shown in 1D and 2D. In 1D, the technique effectively discovers the elastic and plastic regions within a stress-strain curve generated by simulations of amorphous carbon material, while in 2D the technique discovers the free-flow region and the inertially-obstructed flow region in the simulation of fluid flow across a plate.

Daniel Shea↗
NASA NTRSDate not supplied

NASA’s Near-Earth Object Observations Program: Abbreviated History and Update

In the wake of Comet Shoemaker-Levy 9’s (D/1993 F2) collision with Jupiter, NASA’s Near-Earth Object (NEO) Observations Program was established more than two decades ago. The NEO Observations Program is responsible for finding, tracking, and characterizing NEOs. Since the Program’s inception in 1998, NASA-funded efforts have discovered more than 98% of the more than 30,000 NEOs currently known. This unique NASA Program supports several NEO surveys that contribute to a sustained and productive campaign to find and track NEOs; collecting data of sufficient precision to allow accurate predictions of the future trajectories of discovered objects. It is a key element of the Planetary Defense Coordination Office (PDCO). The Program also sponsors applied planetary science research conducted at NASA field centers, astronomical observatories, and other locations around the United States. The PDCO relies on data from projects supported by the NEO Observations Program which, in turn, also coordinates NEO observation efforts conducted at ground-based observatories sponsored by the National Science Foundation (NSF) and the space domain awareness facilities of the United States Space Force (USSF). PDCO’s current priority is the NEO Surveyor Mission (NEOSM) , launched away from the vicinity of Earth to SEL1 and working in coordination with large ground-based surveys could complete the NEO survey within a decade following launch. NEOSM’s has three primary mission objectives: - assess the current risk to the Earth of asteroid impact(s); - examine the origin and ultimate fate of the asteroid population (within our solar system); - to find suitable, low-Δv targets for future robotic and piloted missions of exploration Operating at SEL1, NEOSM will also find NEOs with long synodic periods (i.e., several decades or longer) and unfavorable orbital viewing geometries. NEOSM will obviate the inherent Earth-based geometric observing handicap.

NEO↗
NASA NTRS2022

Systematic Kmtnet Planetary Anomaly Search V. Complete Sample of 2018 Prime-Field

We complete the analysis of all 2018 prime-field microlensing planets identified by the Korea Microlensing Telescope Network (KMTNet) Anomaly Finder. Among the ten previously unpublished events with clear planetary solutions, eight are either unambiguously planetary or are very likely to be planetary in nature: OGLE-2018-BLG-1126, KMT-2018-BLG-2004, OGLE-2018-BLG-1647, OGLE-2018-BLG-1367, OGLE-2018-BLG-1544, OGLE-2018-BLG-0932, OGLE-2018-BLG-1212, and KMT-2018-BLG-2718. Combined with the four previously published new Anomaly Finder events and 12 previously published (or in preparation) planets that were discovered by eye, this makes a total of 24 2018 prime-field planets discovered or recovered by Anomaly Finder. Together with a paper in preparation on 2018 subprime planets, this work lays the basis for the first statistical analysis of the planet mass-ratio function based on planets identified in KMTNet data. By systematically applying the heuristic analysis to each event, we identified the small modification in their formalism that is needed to unify the so-called close-wide and inner-outer degeneracies.

gravitational lensing: micro↗
NASA NTRSDate not supplied

Real-Time Pilot Inputs for Aircraft Dynamic Modeling

Real-time dynamic modeling and pilot displays are used to enable pilots to intuitively discover effective multi-axis inputs for aircraft dynamic modeling during flight tests. An F-16 nonlinear simulation flown by a pilot using a joystick and a laptop computer with real-time displays of relevant information is used to demonstrate the approach. Results show that pilots can use the real-time display to discover and implement effective and efficient multi-axis inputs for accurate dynamic modeling in flight. The real-time dynamic modeling results driving the pilot display can be used to certify that the acquired flight data are adequate for accurate dynamic modeling, thus avoiding postflight data analysis and modeling by an analyst to make that determination. Implications for pilot training and efficient flight testing are discussed.

Pilot Inputs↗
NASA NTRS2025

Sulfur outgassing and in-gassing in lunar orange glass beads and implications for 33S “Anomaly” in the Moon

Our recent investigations have discovered inward diffusion (in-gassing) of moderately volatile elements (MVEs; e.g., Na, K and Cu) from volcanic gas into volcanic beads/droplets. In this work, we examine the distribution of sulfur in lunar orange glass beads. Our analyses reveal that sulfur exhibits a non-uniform distribution across the beads, forming “U” or “W” shaped profiles typical of in-gassing. A model developed to assess sulfur contributions from different sources (original magmatic sulfur versus atmospheric in-gassed sulfur) in the orange beads indicates that atmospheric sulfur in-gassed during eruption contributes approximately 9–24 % to the total sulfur content of an orange bead, averaging around 16 %. This in-gassed sulfur is derived from the eruption plume, where atmospheric sulfur could undergo photochemical reactions induced by UV light, leading to mass independent fractionation and a distinct sulfur isotope signature. Interestingly, a recent study discovered a small mass independent isotope fractionation of sulfur in lunar orange glass beads in drive tube 74002/1 and a lack of such mass independent isotope fractionation in black glass beads in the same lunar sample. This finding contrasts with sulfur in lunar basalts, which typically exhibit mass dependent fractionation. With our work, the observed mass independent fractionation signal in sulfur isotopes of orange beads can be attributed to the in-gassing of photolytic sulfur in the optically thin part of the eruption plume where UV light can penetrate. Using the sulfur isotope data of lunar orange beads, we estimate that the Δ33S value of atmospheric sulfur is approximately −0.18 ‰. Our study provides new insights into the complex dynamics of volatile elements in lunar volcanic processes, highlighting the role of in-gassing in shaping sulfur isotope signatures in volcanic glass beads.

Xue Su↗
DOE OSTI2020

Complementary workflows for identifying one-hop network behavior and multi-hop network dependencies

A network analysis tool evaluates network flow information in complementary workflows to identify one-hop behavior of network assets and also identify multi-hop dependencies between network assets. In one workflow (e.g., using association rule learning), the network analysis tool can identify significant one-hop communication patterns to and/or from network assets, taken individually. Based on the identified one-hop behavior, the network analysis tool can discover patterns of similar communication among different network assets, which can inform decisions about deploying patch sets, mitigating damage, configuring a system, or detecting anomalous behavior. In a different workflow (e.g., using deep learning or cross-correlation analysis), the network analysis tool can identify significant multi-hop communication patterns that involve network assets in combination. Based on the identified multi-hop dependencies, the network analysis tool can discover functional relationships between network assets, which can inform decisions about configuring a system, managing critical network assets, or protecting critical network assets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Data-Driven Template Discovery Using Graph Convolutional Neural Networks

Modeling adversarial activities is a critical component of developing high-con?dence indicators of efforts to acquire, fabricate, proliferate, and/or deploy weapons of mass terror (WMTs). Current approaches to generating representative patterns of interest (a.k.a templates) from the real-world domains involve a Subject Matter Expert (SME)-guided manual process. The goal of Data-Driven Template Discovery (DDTD) is to use a (potentially small) set of SME generated templates to discover other previously unknown and interesting templates in an attributed graph. A template is an activity pattern describing a set of interactions among a group of nodes in the graph. The motivation behind DDTD is to expand the original set of templates, without having SMEs craft all the templates by hand. DDTD also provides seed templates to SMEs, to help them construct larger, high-?delity, and scenario-oriented templates. In these cases, obtaining a larger set of templates that are related (contain similar signals) to the original set is of great value. In this work, we propose to use Graph Convolutional Neural Networks (GCNs) to discover new templates that are heavily related to the original set. GCNs are a family of Neural Network (NN) architectures especially designed to work directly on graphs. In contrast to the traditional NNs, that require considerable amounts of labeled data, GCNs do not require a big labeled training set because they can directly leverage the graph structure instead. This property makes GCNs the perfect tool for creating activity templates.

Joaristi, Mikel↗
DOE OSTI2021

Identifying Pathways for Enhanced Collaboration Between the Mining and Geothermal Industries

The locatable mineral industry is shifting toward improving environmental performance and becoming more sustainable, with numerous mining companies shifting to renewable energy technologies to power mine operations and at least one company pledging net-zero emissions by 2050. One potential electricity source to help achieve improved environmental performance and decarbonization within the mining industry is geothermal energy. As part of a study into potential collaboration between the geothermal and locatable mineral industries (focused on the portion of the Basin and Range Province within Nevada), the National Renewable Energy Laboratory (NREL) with support from the U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO), investigated data, economic, and regulatory factors that may contribute to or inhibit synergies between the two industries. The objectives of the study included analyzing: The type and quality of data collected by the locatable mineral industry to determine feasibility for geothermal resource exploration; The regulatory pathways and potential barriers that could prevent development of geothermal resources discovered via a mining claim (and vice versa); The historical development of geothermal resources discovered via mineral exploration data; The value propositions for both the locatable mineral and the geothermal industries to collaborate.

40 EE - Geothermal Technologies Office (EE-4G)↗
DOE OSTI2022

Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference

Current ground-based cosmological surveys, such as the Dark Energy Survey (DES), are predicted to discover thousands of galaxy-scale strong lenses, while future surveys, such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will increase that number by 1-2 orders of magnitude. The large number of strong lenses discoverable in future surveys will make strong lensing a highly competitive and complementary cosmic probe. To leverage the increased statistical power of the lenses that will be discovered through upcoming surveys, automated lens analysis techniques are necessary. We present two Simulation-Based Inference (SBI) approaches for lens parameter estimation of galaxy-galaxy lenses. We demonstrate the successful application of Neural Posterior Estimation (NPE) to automate the inference of a 12-parameter lens mass model for DES-like ground-based imaging data. We compare our NPE constraints to a Bayesian Neural Network (BNN) and find that it outperforms the BNN, producing posterior distributions that are for the most part both more accurate and more precise; in particular, several source-light model parameters are systematically biased in the BNN implementation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics

The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. CERN's Large Hadron Collider (LHC) represents a huge step forward in this quest. The discovery of the Higgs boson, the observation of exceedingly rare decays of $B$ mesons, and stringent constraints on many viable theories of physics beyond the Standard Model (SM) demonstrate the great scientific value of the LHC physics program. The next phase of this global scientific project will be the High-Luminosity LHC (HL-LHC) which will collect data starting circa 2029 and continue through the 2030s. The primary science goal is to search for physics beyond the SM and, should it be discovered, to study its implications. In the HL-LHC era, the ATLAS and CMS experiments will record around 100 times as many collisions as were used to discover the Higgs boson (and at twice the energy). Both NSF and DOE are making large detector upgrade investments so the HL-LHC can operate in this high-rate environment. Similar investment in software R&D for acquiring, managing, processing and analyzing HL-LHC data is critical to maximize the return-on-investment in the upgraded accelerator and detectors. This report presents a strategic plan for a possible second 5-year funded phase (2023 through 2028) for the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) which will close remaining software and computing gaps to deliver HL-LHC science.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

A Landau-Devonshire Approach of Elastic Strain Effects on Ferroelectric Al1-xScxN

Landau-Devonshire thermodynamic modeling enables the phenomenological description of ferroelectrics. 1 The approach has been validated across a wide range of ferroelectric materials from the first ferroelectric discovered, Rochelle Salt, to recent HfO2-based materials. 2-4 Extension to what is now referred to as the Landau-Ginsburg-Devonshire model enables rigorous investigation of polarization boundaries and reorientation, phase transformations, and domain formation/evolution. We present a thermodynamic analysis of the recently discovered nitride ferroelectric materials 5-7 using the classic Landau-Devonshire approach. The electrostrictive and dielectric stiffness coefficients of Al1-xScxN with wurtzite structure (6mm) are determined using a free energy density function assuming a hexagonal parent phase (6/mmm), with the first order phase transition based on the dielectric stiffness relationships (Fig. 1). The results of this analysis show that the strain sensitivity of the energy barrier is one order of magnitude larger than that of the spontaneous polarization in these wurtzite ferroelectrics, yet both are less sensitive to strain compared to classic perovskite ferroelectrics (Fig. 2). These analysis results reported here explain experimentally reported sensitivity of coercive field to elastic strain/stress in Al1-xScxN films, and would enable further thermodynamic analysis via phase field simulation and related methods.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗
DOE OSTI2020

Emerging Contaminants: Identification, Life Cycle, and Key Challenges - 20415

The term 'emerging contaminants' and its multiple variants has come to refer to previously overlooked compounds discovered in the environment which represent a potential threat to human and ecological receptors. These compounds may be discovered in the environment as new analytical techniques are developed and/or as new monitoring programs for drinking water and groundwater are implemented, while the threat to receptors may be realized through advances in understanding of toxicology and pathways to receptors. Emerging contaminants present unique and considerable challenges as demands to address them can outpace the understanding of their toxicity, their need for regulation, their occurrence, and techniques for treating the environmental media they affect. With these challenges in mind, this paper serves as a primer for understanding emerging contaminants. The paper will lay a foundation for understanding emerging contaminants through three key topics: 1. Who identifies emerging contaminants? An overview of the various stakeholder groups around the world working on identifying potential emerging contaminants and developing systems for screening potential candidates, prioritizing, and ultimately generating regulations will be provided. 2. How Chemicals Rise into Awareness as Emerging Contaminants. The process by which contaminants emerge through a cycle of awareness, characterization, management and regulation will be discussed. Current emerging contaminants will be discussed in the context of the life cycle: emerging contaminants where impacts to drinking water supplies are driving public awareness (e.g. per and polyfuoroalkyl substances (PFASs) and 1,4-dioxane), emerging contaminants impacted by changing regulatory standards or development and debate on toxicity (e.g., hexavalent chromium, 1,2,3-trichloropropane, trichloroethylene in vapor intrusion), and those with evolving understanding of impacts and usage (e.g., microplastics). 3. Key Challenges. Unique challenges associated with emerging contaminants, including visibility and public sensitivity, uncertainty and vulnerability, will be discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗