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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Realization of a Faster, Cheaper, Better Star Tracker for the New Millennium

The first Danish satellite, إrsted, will be launched in August of 1997. The scientific objective of إrsted is to perform a precision mapping of the Earth's magnetic field. Attitude data for the payload and the satellite are provided by the Advanced Stellar Compass (ASC) star tracker. The ASC consists of a CCD star camera and a capable microprocessor which operates by comparing the star image frames taken by the camera to its internal star catalogs.

star↗
NASA NTRSDate not supplied

Enabling Nuclear and Solar Thermal Propulsion with the Computational Laboratory: Faster and Cheaper Materials Characterization

Nuclear and solar thermal propulsion offer enhanced efficiencies for in-space travel which may open up the outer Solar System to both crewed and automated craft. However, these advanced propulsion systems require cutting-edge materials which are often not easily tested in the laboratory. Ab initio thermodynamics and other computational methods offer a way to test materials at high pressures and temperatures more quickly, and with reduced cost. Here, several case studies are presented which highlight the utility of modern simulation techniques. First, an extensive thermodynamic study was performed at the ab initio level to elucidate the role of hot hydrogen flow on the erosion of four refractory carbides to examine their appropriateness for use as channel coatings. A detailed analysis of reaction products informs estimates of erosion which are validated in comparison with heritage NERVA data. Specific material suggestions are made for both nuclear and solar designs. Secondly, we examined the mechanical behavior and chemical stability of various components of an idealized nuclear cermet core design using techniques spanning from the atomic to microscale. Next, the mechanical and chemical behavior of tungsten (a potential matrix material) and the stability of uranium mononitride (a potential ceramic fuel element), are characterized in the presence of hydrogen and at elevated temperatures with ab initio thermodynamics. Finally, the mechanical response and failure of tungsten under tensile strain is simulated at the micron scale with a combined finite element and dislocation dynamics approach. The resultant stress-strain data agrees well with experiments and leads to a workflow which can incorporate ab initio thermodynamic data into micron-scale simulations and thus provide real-world relevant estimates of erosion and stress-strain behavior. The power of this framework and our plans to use it in the future will be discussed.

William C Tucker↗
NASA NTRS2021

Faster Exo-Earth Yield for HabEx and LUVOIR via Extreme Precision Radial Velocity Prior Knowledge

The HabEx and LUVOIR mission concepts reported science yields for mission scenarios in which the instruments must search for potentially habitable planets, determine their orbits, and, if worthwhile, invest the integration time for a spectral characterization. We evaluate the impact of prior knowledge of planet existence and orbital parameters on yield for four mission concept architectures: HabEx 4m telescope with hybrid starshade and coronagraph, HabEx4m telescope with starshade only, HabEx 4m telescope with coronagraph only, and LUVOIR B8m telescope with coronagraph only. We use perfect prior knowledge to establish an upperbound on yield and use partial prior knowledge from a potential future extreme precision radial velocity (EPRV) instrument with3cm∕ssensitivity. We detail a modeling framework that per-forms dynamically responsive observation scheduling with realistic mission constraints. We evaluate exo-Earth yields against three metrics of spectral characterization for the four mission architectures and three levels of prior knowledge (none, partial, and perfect). The EPRV pro-vided prior knowledge increases yields by∼30%and accelerates by a factor of 3 to 6 the time to achieve half of the yield of the mission. Prior knowledge makes all the mission architectures more nimble and powerful, and most especially starshade-based architectures. With prior knowledge, a small telescope with a starshade can achieve comparable yield to a larger telescope with a coronagraph.

Rhonda Morgan↗
NASA NTRS2022

Faster Tropical Upper Stratospheric Upwelling Drives Changes in Ozone Chemistry

Tropospheric trends in long-lived source gases N2O and the chlorofluorocarbons (CFCs) cause trends in O3 through changes in their reactive product gases. Transport affects the product gases because it controls the distribution of the long-lived source gases. We find that large changes in tropical upwelling 10-5 hPa since 2012 have strengthened the northern branch of the upper stratospheric (UpS) transport circulation, dramatically altering the abundances of N2O and its odd nitrogen product gases, NOx and HNO3. Increased upwelling is connected to stronger and more frequent Quasi-Biennial Oscillation easterly winds at 10 hPa and above. We use simulations with and without time varying MERRA2 meteorology to quantify the impact of dynamical changes on O3 loss via the NOx and ClOx cycles. We find that dynamical impacts on these cycles explain the mid-stratospheric tropical O3 increase and Arctic UpS O3 decrease since 2005.

Middle atmosphere chemistry and composition↗
NASA NTRSDate not supplied

Faster Tropical Upper Stratospheric Upwelling is Driving Changes in Ozone Chemistry

Trends in N2O and the chlorofluorocarbons (CFCs) cause trends in O3 through changes in their reactive product gases, NOx and ClOx, but transport plays an important role because it controls the distribution of the long‐lived source gases that produce ozone‐destroying radicals. In this study we show that increased tropical upwelling 10‐5 hPa from 2013‐2021 has changed upper stratospheric (UpS) composition and shifted the balance of O3 loss processes. We use N2O, HNO3, NOx, temperature and O3 data from the Aura Microwave Limb Sounder (MLS) and the SCI‐Sat Atmospheric Chemistry Experiment Fourier Transport Spectrometer (ACE‐FTS) over a 16‐year period to show how changes in reactive nitrogen species affected gas phase ozone chemistry above 30 hPa between June 2013‐May 2021 compared to the previous 8 years, June 2005‐May 2013. We use 2 simulations of the Global Modeling Initiative (GMI) chemistry transport model (CTM), with and without time varying MERRA2 meteorology, to understand how dynamical changes during this 16‐yr period affected O3 through changes in loss via the NOx and ClOx cycles. We also identify the role that the quasi‐biennial oscillation (QBO) in tropical zonal winds plays in the UpS composition changes. We find large increases in tropical upwelling and poleward transport in the northern branch of the UpS transport circulation since 2013 that dramatically increased the abundance of the N2O and its odd nitrogen product gases, NOx and HNO3. O3 loss by NOx in the Arctic UpS increased due to dynamically driven composition change, explaining the observed weak O3 recovery in that region since 2005. The increased upwelling also drove decreases in tropical NOx, leading to increased tropical O3 from 12‐6 hPa.

middle atmosphere chemistry and composition↗
NASA NTRSDate not supplied

A New Era of H-O-C-S Magma Solubility Modeling: Better, Faster, Stronger

H 2 O, CO 2 , and S are the most abundant volatiles in magmatic systems and are critical to understanding magma storage, phase equilibria, and volcanic eruptions. Models that consider all three of these components, however, may not allow for critical examination and adjustment of assumptions underlying the model, or provide benchmark testing or extensible interfaces. Thus, understanding why models produce different results can be challenging. We have gathered authors of established (D-Compress) and recent (VolFe, EVo, Sulfur_X, MAGEC) H-O-C-S volatile solubility models to work together to understand how and why our models diverge. We present a series of benchmark basalt degassing scenarios revealing that often understated model assumptions such as fO 2 buffer equations, fO 2 -Fe 3+ /ΣFe relationships, and even major element normalization routines have outsized effects on model results. All models consider S 2- and S 6+ melt species but with different approaches to sulfate/sulfide capacities, partition coefficients, and species fugacities, leading to divergence in the evolution of modeled gas compositions, melt S and Fe speciation, and fO 2 , with the extent of divergence depending on melt composition. Such scenarios enable meaningful intercomparison of existing models and lay the groundwork for a user-friendly yet powerful solubility modeling framework. Given our wealth of existing solubility literature, we suggest that the field of magmatic volatiles should focus now on the creation of modern tools and the modular implementation of existing model equations or methods, and that the evaluation of code usability, transparency, and benchmarking should be codified pillars of the peer-review process. As an example of such an endeavor, we present early work coupling these sulfur solubility models with VESIcal, an extensible and rigorously tested python library containing seven existing H 2 O-CO 2 solubility models. VESIcal includes the ability to extract, edit, and even interchange assumptions underlying any model. For example, users may combine or swap separately published H 2 O, CO 2 , and S models, as well as underlying model choices, such as Equations of State and redox models.

volatiles in magmas↗
DOE OSTI2017

Sprites and State Channels: Payment Networks that Go Faster than Lightning

Bitcoin, Ethereum and other blockchain-based cryptocurrencies, as deployed today, cannot scale for wide-spread use. A leading approach for cryptocurrency scaling is a smart contract mechanism called a payment channel which enables two mutually distrustful parties to transact efficiently (and only requires a single transaction in the blockchain to set-up). Payment channels can be linked together to form a payment network, such that payments between any two parties can (usually) be routed through the network along a path that connects them. Crucially, both parties can transact without trusting hops along the route. In this paper, we propose a novel variant of payment channels, called Sprites, that reduces the worst-case “collateral cost” that each hop along the route may incur. The benefits of Sprites are two-fold. 1) In Lightning Network, a payment across a path of ℓ channels requires locking up collateral for Θ(ℓΔ) time, where Δ is the time to commit an on-chain transaction. Sprites reduces this cost to Θ(ℓ+Δ). 2) Unlike prior work, Sprites supports partial withdrawals and deposits, during which the channel can continue to operate without interruption. In evaluating Sprites we make several additional contributions. First, our simulation-based security model is the first formalism to model timing guarantees in payment channels. Our construction is also modular, making use of a generic abstraction from folklore, called the “state channel,” which we are the first to formalize. We also provide a simulation framework for payment network protocols, which we use to confirm that the Sprites construction mitigates against throughput-reducing attacks.

97 MATHEMATICS AND COMPUTING↗