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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Computer Program For Variable-Conductance Heat Pipes

VCHPDA provides accurate mathematical models of transient as well as steady-state performance of variable-conductance heat pipes over wide range of operating conditions. Applies to heat pipes with either cold, wicked or hot, nonwicked gas reservoirs and uses ideal-gas law and "flat-front" (negligible vapor diffusion) gas theory. Calculates length of gas-blocked region and temperature of vapor in active portion of heat pipe by solving set of nonlinear equations for conservation of energy and mass. Written in FORTRAN 77.

Antoniuk, D.↗
DOE OSTI2025

Evaluating Cloud Properties at Scott Base: Comparing Ceilometer Observations With ERA5, JRA55, and MERRA2 Reanalyses Using an Instrument Simulator

This study compares CL51 ceilometer observations made at Scott Base, Antarctica, with statistics from the ERA5, JRA55, and MERRA2 reanalyses. To enhance the comparison we use a lidar instrument simulator to derive cloud statistics from the reanalyses which account for instrumental factors. The cloud occurrence in the three reanalyses is slightly overestimated above 3 km, but displays a larger underestimation below 3 km relative to observations. Unlike previous studies, we see no relationship between relative humidity and cloud occurrence biases, suggesting that the cloud biases do not result from the representation of moisture. We also show that the seasonal variation of cloud occurrence and cloud fraction, defined as the vertically integrated cloud occurrence, are small in both the observations and the reanalyses. We also examine the quality of the cloud representation for a set of weather states derived from ERA5 surface winds. The variability associated with grouping cloud occurrence based on weather state is much larger than the seasonal variation, highlighting weather state is a strong control of cloud occurrence. All the reanalyses continue to display underestimates below 3 km and overestimates above 3 km for each weather state. But the variability in ERA5 statistics matches the changes in the observations better than the other reanalyses. We also use a machine learning scheme to estimate the quantity of supercooled liquid water cloud from the ceilometer observations. Ceilometer low-level supercooled liquid water cloud occurrences are considerably larger than values derived from the reanalyses, further highlighting the poor representation of low-level clouds in the reanalyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Trajectory controllability of semilinear systems with multiple variable delays in control

In this paper, finite-dimensional dynamical control system described by semilinear differential state equation with multiple variable delays in control are considered. The concept of controllability we extend on trajectory controllability for systems with multiple point delays in control. Moreover, remarks and comments on the relationships between different concepts of controllability are presented. Finally, simple numerical example, which illustrates theoretical considerations is also given. The possible extensions are also proposed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2001

Long-Term Space Astrophysics Program

This is the final report for our Long-Term Space Astrophysics Program (NRA 94-OSS-12) grant NAG 5-3225. The proposal is entitled 'Spectral and Temporal Properties of Black Hole Candidates', and began funding in May 1995, and ran through 31 Aug 2000. The project summary from the original proposal was as follows: 'We will study the spectral and temporal properties of black hole candidates (BHC) by using data from archival sources (e.g., EXOSAT, Ginga, ROSAT) and proposed follow-up observations with modern instruments (e.g., ASCA, XTE). Our spectral studies will focus on identifying the basic characteristics and luminosities of the emission components in the various 'states' of BHC. We hope to understand and quantify the global energetics of these states. Our temporal studies will focus on expanding and classifying our knowledge of BHC variability properties in each state. We will explore the nature of quasi-periodic oscillations in BHC. We will combine our spectral and temporal studies by analyzing time lags and variability coherence between energy channels. In addition, we will investigate ways of correlating observed variability behavior with specific emission components.' We have accomplished many of these goals laid out within the original proposal. As originally proposed, we have utilized both archival and proprietary satellite data. In terms of archival data, we have utilized data from the Advanced Satellite for Cosmology and Astrophysics (ASCA), ROSAT, and the Rossi X-ray Timing Explorer (RXTE). We also obtained proprietary data from ASCA, RXTE, and the Extreme Ultraviolet Explorer (EUVE). In terms of sources, we have examined a wide variety of both galactic black hole candidates and extra-galactic black holes. For the galactic black holes we have observed and analyzed both the low/hard state and the high/soft state. We have performed both spectral and timing analyses on all of these objects. In addition, we have also examined a number of neutron stars or potential neutron stars. All of our research on the above mentioned objects has resulted in one or more publications in peer-reviewed journals. Attached is a list of refereed publications of research results which have been funded by this grant over approximately the past five and a half years. In addition, we have included a list of conference proceedings and other similar reports that have been associated with this grant.

Nowark, Michael A.↗
DOE OSTI2023

A New Sodium Thioborate Fast Ion Conductor: Na 3 B 5 S 9

Abstract We report a new sodium fast‐ion conductor, Na 3 B 5 S 9 , that exhibits a high Na ion total conductivity of 0.80 mS cm −1 (sintered pellet; cold‐pressed pellet=0.21 mS cm −1 ). The structure consists of corner‐sharing B 10 S 20 supertetrahedral clusters, which create a framework that supports 3D Na ion diffusion channels. The Na ions are well‐distributed in the channels and form a disordered sublattice spanning five Na crystallographic sites. The combination of structural elucidation via single crystal X‐ray diffraction and powder synchrotron X‐ray diffraction at variable temperatures, solid‐state nuclear magnetic resonance spectra and ab initio molecular dynamics simulations reveal high Na‐ion mobility (predicted conductivity: 0.96 mS cm −1 ) and the nature of the 3D diffusion pathways. Notably, the Na ion sublattice orders at low temperatures, resulting in isolated Na polyhedra and thus much lower ionic conductivity. This highlights the importance of a disordered Na ion sublattice—and existence of well‐connected Na ion migration pathways formed via face‐sharing polyhedra—in dictating Na ion diffusion.

Zhou, Laidong↗
DOE OSTI2023

A New Sodium Thioborate Fast Ion Conductor: Na 3 B 5 S 9

Abstract We report a new sodium fast‐ion conductor, Na 3 B 5 S 9 , that exhibits a high Na ion total conductivity of 0.80 mS cm −1 (sintered pellet; cold‐pressed pellet=0.21 mS cm −1 ). The structure consists of corner‐sharing B 10 S 20 supertetrahedral clusters, which create a framework that supports 3D Na ion diffusion channels. The Na ions are well‐distributed in the channels and form a disordered sublattice spanning five Na crystallographic sites. The combination of structural elucidation via single crystal X‐ray diffraction and powder synchrotron X‐ray diffraction at variable temperatures, solid‐state nuclear magnetic resonance spectra and ab initio molecular dynamics simulations reveal high Na‐ion mobility (predicted conductivity: 0.96 mS cm −1 ) and the nature of the 3D diffusion pathways. Notably, the Na ion sublattice orders at low temperatures, resulting in isolated Na polyhedra and thus much lower ionic conductivity. This highlights the importance of a disordered Na ion sublattice—and existence of well‐connected Na ion migration pathways formed via face‐sharing polyhedra—in dictating Na ion diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Enhancing the photoresponse and photocatalytic properties of TiO 2 by controllably tuning defects across {101} facets

Introducing defects into semiconductors with well-controlled exposed facets offers an effective route for the development of photocatalytic materials with greatly improved properties. Here, we report a facile ethylene glycol reduction procedure to make anatase titanium dioxide (TiO 2 ) with different concentrations of exposed {001} and {101} facets, leading to different surficial defects. TiO 2 with increased concentrations of {101} facets shows a 5-fold improvement in photocurrent generation as well as improved photocatalytic activity towards water splitting under visible light irradiation. Thus, the improved activity is ascribed to the oxygen vacancies as well as the variable surface chemical states, which collectively induce a slower recombination rate of photo-induced electron-hole pairs. This work also highlights a feasible strategy to obtain the defective TiO 2 and explore the synergistic effect of surface defects and different concentrations of exposed {001} and {101} facets for photocurrent and photocatalytic properties under visible light irradiation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Hydropower potential derived from streamflow extremes for Alaska, USA

Alaska is an expansive region known for its abundant natural resources, including thousands of miles of streams and rivers. These rivers represent potential opportunities for future hydropower development that could provide reliable energy supply for local communities. There is limited long-term high temporal resolution streamflow data available for the region, making data-driven estimates of potential hydropower and its variability across the state challenging. This study provides a novel data-driven approach for hydropower capacity estimation across Alaska. We use supervised machine learning to develop a relationship between the daily and peak flow duration curves in order to augment the size of our dataset from 44 sites to 67 sites. We perform a stochastic hydropower estimation across the 67 sites and identify approximately 1000 MW of total potential hydropower capacity distributed across these sites. Our study provides the first step towards more comprehensive hydropower estimation for this critical region, highlighting the need for future work integrating high-resolution spatial data, community needs, and economic constraints in estimates of potential hydropower development in Alaska.

Hydropower↗
DOE OSTI2021

Using In Situ High-Energy X-ray Diffraction to Quantify Electrode Behavior of Li-Ion Batteries from Extreme Fast Charging

Extreme fast charging (XFC, =15 min charging time) of Li-ion batteries (LIBs) has been proposed as an immediate target to increase the commercial appeal of electric vehicles. However, XFC of LIBs is associated with the degradation of battery performance and safety concerns. Quantitative and simultaneous characterization of various components during cell degradation represents a major experimental challenge. In this work, we outline a methodology for the use of spatially resolved, high-energy X-ray diffraction as a quantitative, in situ method of mapping the degradation of LIBs. We use this approach to study the battery cell capacity loss, both locally (mm scale) and globally over the entire cell (cm scale). Specifically, our workflow allows us to quantify the total amount of plated Li on the anode, as well as its spatial correlation to the structural properties of the anode and cathode. The method complements existing optical methods to resolve the spatial heterogeneity of local degradation mechanisms such as Li plating and provides simultaneous insights into concomitant anode state-of-charge variability. We apply it to commercially relevant single-layer pouch cells with the graphite anode and the LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathode. Our results show that Li plating occurs heterogeneously on the graphite anode and that it is spatially correlated to the extent of anode lithiation. In this work, we anticipate that the described workflow will allow for understanding multiscale degradation in energy-storage devices beyond LIBs, where quantitative analysis at a local and global length scale can be performed without the necessity to tear down the device, due to the applicability of high-energy X-rays to probe in situ degradation.

25 ENERGY STORAGE↗
DOE OSTI2020

Relating CMIP5 Model Biases to Seasonal Forecast Skill in the Tropical Pacific

Abstract We examine links between tropical Pacific mean state biases and El Niño/Southern Oscillation forecast skill, using model‐analog hindcasts of sea surface temperature (SST; 1961–2015) and precipitation (1979–2015) at leads of 0–12 months, generated by 28 different models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Model‐analog forecast skill has been demonstrated to match or even exceed traditional assimilation‐initialized forecast skill in a given model. Models with the most realistic mean states and interannual variability for SST, precipitation, and 10‐m zonal winds in the equatorial Pacific also generate the most skillful precipitation forecasts in the central equatorial Pacific and the best SST forecasts at 6‐month or longer leads. These results show direct links between model climatological biases and seasonal forecast errors, demonstrating that model‐analog hindcast skill—that is, how well a model can capture the observed evolution of tropical Pacific anomalies—is an informative El Niño/Southern Oscillation metric for climate simulations.

Ding, Hui↗
DOE OSTI2023

Modeling Land-Atmosphere Coupling at Cloud-Resolving Scale Within the Multiple Atmosphere Multiple Land (MAML) Framework in SP-E3SM

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a Multiple Atmosphere Multiple Land (MAML) framework in the superparamaterized version of E3SM (SP32 E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud-resolving scale and their interactions with atmosphere. Comparing to the standard SP-E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., Multiple Atmosphere Single Land (MASL)), the impact of MAML on the strength of land-atmosphere coupling is limited, partly because the current implementation mainly facilitates one-way coupling between the cloud-resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP-E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (PE) is primarily driven by the change in large-scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P-E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P-E by decreasing the NGMS. Finally, future development in the MAML framework is discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems

Abstract Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Asynchronous quadratic control for constrained hidden markov jump linear systems with incomplete MTPM and MOCPM

Abstract This paper investigates the quadratic optimal control problem for constrained Markov jump linear systems with incomplete mode transition probability matrix (MTPM). Considering original system mode is not accessible, observed mode is utilized for asynchronous controller design where mode observation conditional probability matrix (MOCPM), which characterizes the emission between original modes and observed modes is assumed to be partially known. An LMI optimization problem is formulated for such constrained hidden Markov jump linear systems with incomplete MTPM and MOCPM. Based on this, a feasible state-feedback controller can be designed with the application of free-connection weighting matrix method. The desired controller, dependent on observed mode, is an asynchronous one which can minimize the upper bound of quadratic cost and satisfy restrictions on system states and control variables. Furthermore, clustering observation where observed modes recast into several clusters, is explored for simplifying the computational complexity. Numerical examples are provided to illustrate the validity.

Zhu, Jin↗
DOE OSTI2024

Transition between Heavy-Fermion-Strange-Metal and Quantum Spin Liquid in a $4⁢d$-Electron Trimer Lattice

We present experimental evidence that a heavy Fermi surface consisting of itinerant, charge-neutral spinons underpins both heavy-fermion-strange-metal (without f electrons) and quantum-spin-liquid states in the 4d-electron trimer lattice, Ba 4 Nb 1-x Ru 3+x O 12 (|x| < 0.20). These two exotic states both exhibit an extraordinarily large entropy, a linear heat capacity extending into the milli-Kelvin regime, a linear thermal conductivity at low temperatures, and separation of charges and spins. Furthermore, the insulating spin liquid is a much better thermal conductor than the heavy-fermion-strange-metal that separately is observed to strongly violate the Wiedemann- Franz law. Here, we propose that at the heart of this 4d system is a universal, heavy spinon Fermi surface that provides a unified framework for explaining the exotic phenomena observed throughout the entire series. The control of such exotic ground states provided by variable Nb concentration offers a new paradigm for studies of correlated quantum matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Extending the Frontier of Quantum Computers with Qutrits

Here, we advocate for a fundamentally different way to perform quantum computation by using three-level qutrits instead of qubits. In particular, we substantially reduce the resource requirements of quantum computations by exploiting a third state for temporary variables (ancilla) in quantum circuits. Past work with qutrits has demonstrated only constant factor improvements, owing to the log 2 (3) binary-to-ternary compression factor. We present a novel technique using qutrits to achieve a logarithmic runtime decomposition of the Generalized Toffoli gate using no ancilla - an exponential improvement over the best qubit-only equivalent. Our approach features a 70× improvement in total two-qudit gate count over the qubit-only decomposition. This results in improvements for important algorithms for arithmetic and QRAM. Simulation results under realistic noise models indicate over 90% mean reliability (fidelity) for our circuit, versus under 30% for the qubit-only baseline. These results suggest that qutrits offer a promising path toward extending the frontier of quantum computers.

97 MATHEMATICS AND COMPUTING↗