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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Atmospheric Teleconnection over Eurasia Induced by Aerosol Radiative Forcing During Boreal Spring

The direct effects of aerosols on global and regional climate during boreal spring are investigated based on simulations using the NASA Global Modeling and Assimilation Office (GMAO) finite-volume general circulation model (fvGCM) with Microphyics of clouds in Relaxed Arakawa Schubert Scheme (McRAS). The aerosol loading are prescribed from three-dimensional monthly distribution of tropospheric aerosols viz., sulfate, black carbon, organic carbon, soil dust, and sea salt from output of the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The aerosol extinction coefficient, single scattering albedo, and asymmetric factor are computed as wavelength-dependent radiative forcing in the radiative transfer scheme of the fvGCM, and as a function of the aerosol loading and ambient relative humidity. We find that anomalous atmospheric heat sources induced by absorbing aerosols (dust and black carbon) excites a planetary scale teleconnection pattern in sea level pressure, temperature and geopotential height spanning North Africa through Eurasia to the North Pacific. Surface cooling due to direct effects of aerosols is found in the vicinity and downstream of the aerosol source regions, i.e., South Asia, East Asia, and northern and western Africa. Additionally, atmospheric heating is found in regions with large loading of dust (over Northern Africa, and Middle East), and black carbon (over South-East Asia). Paradoxically, the most pronounced feature in aerosol-induced surface temperature is an east-west dipole anomaly with strong cooling over the Caspian Sea, and warming over central and northeastern Asia, where aerosol concentration are low. Analyses of circulation anomalies show that the dipole anomaly is a part of an atmospheric teleconnection driven by atmospheric heating anomalies induced by absorbing aerosols in the source regions, but the influence was conveyed globally through barotropic energy dispersion and sustained by feedback processes associated with the regional circulations.

Kim, Maeng-Ki↗
NASA NTRS2007

Integral Radiator and Storage Tank

A simplified, lightweight system for dissipating heat of a regenerative fuel- cell system would include a heat pipe with its evaporator end placed at the heat source and its condenser end integrated into the wall of the regenerative fuel cell system gas-storage tanks. The tank walls act as heat-radiating surfaces for cooling the regenerative fuel cell system. The system was conceived for use in outer space, where radiation is the only physical mechanism available for transferring heat to the environment. The system could also be adapted for use on propellant tanks or other large-surface-area structures to convert them to space heat-radiating structures. Typically for a regenerative fuel cell system, the radiator is separate from the gas-storage tanks. By using each tank s surface as a heat-radiating surface, the need for a separate, potentially massive radiator structure is eliminated. In addition to the mass savings, overall volume is reduced because a more compact packaging scheme is possible. The underlying tank wall structure provides ample support for heat pipes that help to distribute the heat over the entire tank surface. The heat pipes are attached to the outer surface of each gas-storage tank by use of a high-thermal conductance, carbon-fiber composite-material wrap. Through proper choice of the composite layup, it is possible to exploit the high longitudinal conductivity of the carbon fibers (greater than the thermal conductivity of copper) to minimize the unevenness of the temperature distribution over the tank surface, thereby helping to maximize the overall heat-transfer efficiency. In a prototype of the system, the heat pipe and the composite wrap contribute an average mass of 340 g/sq m of radiator area. Lightweight space radiator panels have a mass of about 3,000 g/sq m of radiator area, so this technique saves almost 90 percent of the mass of separate radiator panels. In tests, the modified surface of the tank was found to have an emissivity of 0.85. The composite wrap remained tightly bound to the surface of the tank throughout the testing in thermal vacuum conditions.

Burke, Kenneth A.↗
NASA NTRS2014

An Efficient, Multi-Layered Crown Delineation Algorithm for Mapping Individual Tree Structure Across Multiple Ecosystems

Deriving individual tree information from discrete return, small footprint LiDAR data may improve forest above ground biomass estimates, and provide tree-level information that is important in many ecological studies. Several crown delineation algorithms have been developed to extract individual tree information from LiDAR point clouds or rasterized canopy height models (CHM), but many of these algorithms have difficulty discriminating between overlapping crowns, and also may fail to detect understory trees. Our approach uses a watershed based delineation of a CHM, which is subsequently refined using the LiDAR point cloud. Individual tree detection was validated with stem mapped field data from the Smithsonian Environmental Research Center (SERC), Maryland, and on a plot and stand level through comparisons of stem density and basal area to delineated metrics at both SERC and a study area in the Sierra Nevada, California. For individual tree detection, the algorithm correctly identified 70% of dominant trees, 58% of co-dominant trees, 35% of intermediate trees and 21% of suppressed trees at SERC. The algorithm had difficulty distinguishing between crowns of small, dense understory trees of approximately the same height. Delineated crown volume alone explained 53% and 84% of the variability in basal area at the SERC and Sierra Nevada sites, respectively. The algorithm produced crown area distributions comparable to diameter at breast height (DBH) size class distributions observed in the field in both study sites. The algorithm detected understory crowns better in the conifer-dominated Sierra Nevada site than in the closed-canopy deciduous site in Maryland. The ability for the algorithm to reproduce both accurate tree size distributions and individual crown geometries in two dissimilar and complex forests suggests great promise for applicability to a wide range of forest systems.

LiDAR↗
NASA NTRSDate not supplied

Preliminary Results from Propellant Mass Gauging with Electrical Capacitance Tomography

Propellants mass gauging technologies designed to work in an accelerated environment, where the propellant remains settled at one end of the propellant tank, do not work well in a microgravity environment because the propellant is not necessarily settled. While some microgravity mass gauging technologies exist at various TRLs, most of them have major disadvantages. Improvements in microgravity propellant mass gauging will result in improvements to many areas of propellant management, which influences performance and mission assurance. Electrical Capacitance Tomography (ECT) is a sensing technology that is able to reconstruct the liquid distribution inside of a tank, which can then be integrated to obtain mass. ECT mass gauging recently achieved high accuracy in laboratory testing, <0.1% liquid volume measurement error, even during sloshing. While ECT mass gauging will theoretically work during all phases of flight, it had not yet been tested in microgravity. The NASA KSC Launch Services Program, with support from the Flight Opportunities Program, successfully flew an ECT liquid mass gauging system experiment on a Zero-G parabolic flight aircraft. Basics of ECT measurement theory, details of the experiment setup and flights, and preliminary results will be discussed. The preliminary results suggest that, even in the current prototype generation, ECT sensor systems will be useful as a propellant mass gauging technology in both an accelerated and microgravity environment.

mass gauging↗
DOE OSTI2022

Industrialized and Robotic Construction Advances in Terrestrial Construction and Opportunities in Space Construction

Advanced Building Construction (ABC) methods such as industrialized prefabrication and robotically controlled additive deposition are becoming promising technologies to support rapid construction of buildings at volume and scale. However, apart from the structural shell of the building, optimal integration of other systems – mechanical, electrical, plumbing, thermal, power generation, storage and distribution, is key to enabling functional buildings. Leveraging ABC methods to integrate such systems in the buildings requires the building design to be optimized for constructability constraints imposed by the industrialized and robotically controlled production setups entailing such ABC methods. The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been focusing on research and development of such ABC technologies and processes that can lead to production of buildings which are resilient to extreme climatic conditions at reduced cost and time. There is a potential synergy between such advancements in terrestrial construction, which can be leveraged for the benefit of space (orbital and extra-terrestrial) construction. Similarly, advances in space construction can lend itself to accelerated adoption of robotic construction methods in terrestrial construction. This presentation will give an overview of selective research efforts of the ICI team at NREL, along with a vision for potential collaborations with agencies like NASA.

3D printing↗
DOE OSTI2024

Additive Molar Volumes in Amorphous Ca/Sr Carbonate Solid Solutions

The development of predictive models of minor element incorporation in crystalline carbonate end products requires an understanding of the fundamental controls on metastable intermediate phase composition. In this study, we used small-angle X-ray scattering (SAXS), X-ray pair distribution function (PDF), thermogravimetric analysis (TGA), inductively coupled plasma mass spectrometry (ICP-MS), and transmission electron microscopy (TEM) to determine the composition-dependent density of an amorphous calcium–strontium carbonate (ACSC) solid solution. The amorphous calcium carbonate (ACC) and strontium carbonate (ASC) measured densities were ρ ACC = 2.19 ± 0.04 g/cm 3 and ρ ASC = 2.97 ± 0.05 g/cm 3 . Throughout our work, the experiments showed a dependence of the water content of the amorphous solid solution on the Sr mole fraction. An equation that relates the molar volume to the average cation radius, the carbonate ion radius, and the water volume was parameterized for hydrated crystalline carbonates and predicted well the molar volume of the ACSC solid solution. This finding indicates that, as for hydrated crystalline carbonates, the molar volumes of amorphous carbonates are additive and that water is a structural component of ACSC. Ab initio molecular dynamics (AIMD) simulations of the ACSC solid solutions showed strong linear correlations between calculated molar volumes and Sr and H 2 O contents, thus supporting the experimental results. In conclusion, our findings highlight the need to consider the full CaCO 3 –MeCO 3 –H 2 O ternary when quantifying metal cation incorporation in ACC.

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

Microstructure Evolution of a Multimodal Gamma-Prime Ni-Based Superalloy Characterized by In Situ Diffraction

The relationship between the evolution of microstructure, deformation micromechanisms and mechanical properties is difficult to establish in multimodal size distribution $_γ$$'$ superalloys, as the microstructure evolves with both temperature and time, and multiple strengthening mechanisms across each size distribution contribute to mechanical performance. In situ X-ray scattering can offer unparalleled insight regarding microstructure evolution at the temperatures and stresses of importance to gas-turbine applications; however, in situ X-ray diffraction has not been applied to the study of multimodal $_γ$$'$ distribution superalloys. Herein, lattice parameter evolution of secondary and tertiary $_γ$$'$ precipitates in a representative superalloy, Nimonic 115, is determined between 750 °C and 950 °C and correlated to room-temperature SEM and microhardness values. A large positive lattice parameter misfit of secondary $_γ$$'$ induces precipitate splitting, and the tertiary $_γ$$'$ goes into dissolution at ~ 800 °C, but with little apparent change in hardness values. The volume fraction of $_γ$$'$ decreases above 900 °C and precipitate-matrix coherency is lost, and there is a corresponding decrease in microhardness values. Importantly, the diffraction analysis demonstrates the capability to determine critical microstructural parameters of both precipitate size distributions in situ, representing an additional tool for determining microstructure-mechanical property relationships of multimodal superalloys.

36 MATERIALS SCIENCE↗
NASA NTRS2002

The D3 Middleware Architecture

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid-dynamics) model executions. DARWIN captures, stores and indexes data; manages derived knowledge (such as visualizations across multiple datasets); and provides an environment for designers to collaborate in the analysis of test results. DARWIN is an interesting application because it supports high-volumes of data. integrates multiple modalities of data display (e.g., images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and views of data. Here we provide an overview of the architecture of D3, the third generation of DARWIN. Earlier versions of DARWIN were characterized by browser-based interfaces and a hodge-podge of server technologies: CGI scripts, applets, PERL, and so forth. But browsers proved difficult to control, and a proliferation of computational mechanisms proved inefficient and difficult to maintain. D3 substitutes a pure-Java approach for that medley: A Java client communicates (though RMI over HTTPS) with a Java-based application server. Code on the server accesses information from JDBC databases, distributed LDAP security services, and a collaborative information system. D3 is a three tier-architecture, but unlike 'E-commerce' applications, the data usage pattern suggests different strategies than traditional Enterprise Java Beans - we need to move volumes of related data together, considerable processing happens on the client, and the 'business logic' on the server-side is primarily data integration and collaboration. With D3, we are extending DARWIN to handle other data domains and to be a distributed system, where a single login allows a user transparent access to test results from multiple servers and authority domains.

Walton, Joan↗
DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗
NASA NTRS2003

Data Access Tools And Services At The Goddard Distributed Active Archive Center (GDAAC)

As one of the largest providers of Earth Science data from the Earth Observing System, GDAAC provides the latest data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Solar Radiation and Climate Experiment (SORCE) data products via GDAAC's data pool (50TB of disk cache). In order to make this huge volume of data more accessible to the public and science communities, the GDAAC offers multiple data access tools and services: Open Source Project for Network Data Access Protocol (OPeNDAP), Grid Analysis and Display System (GrADS/DODS) (GDS), Live Access Server (LAS), OpenGlS Web Map Server (WMS) and Near Archive Data Mining (NADM). The objective is to assist users in retrieving electronically a smaller, usable portion of data for further analysis. The OPeNDAP server, formerly known as the Distributed Oceanographic Data System (DODS), allows the user to retrieve data without worrying about the data format. OPeNDAP is capable of server-side subsetting of HDF, HDF-EOS, netCDF, JGOFS, ASCII, DSP, FITS and binary data formats. The GrADS/DODS server is capable of serving the same data formats as OPeNDAP. GDS has an additional feature of server-side analysis. Users can analyze the data on the server there by decreasing the computational load on their client's system. The LAS is a flexible server that allows user to graphically visualize data on the fly, to request different file formats and to compare variables from distributed locations. Users of LAS have options to use other available graphics viewers such as IDL, Matlab or GrADS. WMS is based on the OPeNDAP for serving geospatial information. WMS supports OpenGlS protocol to provide data in GIs-friendly formats for analysis and visualization. NADM is another access to the GDAAC's data pool. NADM gives users the capability to use a browser to upload their C, FORTRAN or IDL algorithms, test the algorithms, and mine data in the data pool. With NADM, the GDAAC provides an environment physically close to the data source. NADM will benefit users with mining or offer data reduction algorithms by reducing large volumes of data before transmission over the network to the user.

Pham, Long↗
DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Statistical tools for a better optical model

Background: Modern statistical tools provide the ability to compare the information content of observables and provide a path to explore which experiments would be most useful to give insight into and constrain theoretical models. Purpose: Here we study three such tools in the context of nuclear reactions with the goal of constraining the optical potential. Method: The three statistical tools examined are (i) the principal component analysis, (ii) the sensitivity analysis based on derivatives, and (iii) the Bayesian evidence. We first apply these tools to a toy-model case, comparing the form of the imaginary part of the optical potential. Then we consider two different reaction observables, elastic angular distributions and polarization data for reactions on 48 Ca and 208 Pb at two different beam energies. Results: For the toy-model case, we find significant discrimination power in the sensitivities and the Bayesian evidence, showing clearly that the volume imaginary term is more useful to describe scattering at higher energies. When comparing between elastic cross sections and polarization data using realistic optical models, sensitivity studies indicate that both observables are roughly equally sensitive but the variability of the optical model parameters is strongly angle dependent. The Bayesian evidence shows some variability between the two observables, but the Bayes factor obtained is not sufficient to discriminate between angular distributions and polarization. Conclusions: From the cases considered, we conclude that, in general, elastic scattering angular distributions have similar impact in constraining the optical potential parameters compared with the polarization data. The angular ranges for the optimum experimental constraints can vary significantly with the observable considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids

Increase in the proliferation of distributed energy resources require real-time situational awareness for efficient grid operations. State estimation plays an important role for the real-time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hier-archical spectral clustering-based network partitioning algorithm followed by a decentralized compressive sensing (DCS)-based state estimation. The applicability of the proposed network partitioning algorithm is tested on an IEEE 123-bus network, an IEEE 8,500-node system, and a 6,000+ node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum number of edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6,000+ node distribution network after dividing the network into 18 optimal partitions. Simulation results show that the DCS-based state estimation recovers the system states with high accuracy and low complexity.

alternating direction method of multipliers↗
NASA NTRS1995

Uncertainties for two-dimensional models of solar rotation from helioseismic eigenfrequency splitting

Observed solar p-mode frequency splittings can be used to estimate angular velocity as a function of position in the solar interior. Formal uncertainties of such estimates depend on the method of estimation (e.g., least-squares), the distribution of errors in the observations, and the parameterization imposed on the angular velocity. We obtain lower bounds on the uncertainties that do not depend on the method of estimation; the bounds depend on an assumed parameterization, but the fact that they are lower bounds for the 'true' uncertainty does not. Ninety-five percent confidence intervals for estimates of the angular velocity from 1986 Big Bear Solar Observatory (BBSO) data, based on a 3659 element tensor-product cubic-spline parameterization, are everywhere wider than 120 nHz, and exceed 60,000 nHz near the core. When compared with estimates of the solar rotation, these bounds reveal that useful inferences based on pointwise estimates of the angular velocity using 1986 BBSO splitting data are not feasible over most of the Sun's volume. The discouraging size of the uncertainties is due principally to the fact that helioseismic measurements are insensitive to changes in the angular velocity at individual points, so estimates of point values based on splittings are extremely uncertain. Functionals that measure distributed 'smooth' properties are, in general, better constrained than estimates of the rotation at a point. For example, the uncertainties in estimated differences of average rotation between adjacent blocks of about 0.001 solar volumes across the base of the convective zone are much smaller, and one of several estimated differences we compute appears significant at the 95% level.

Genovese, Christopher R.↗
NASA NTRS2004

Job Scheduling in a Heterogeneous Grid Environment

Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and three job migration algorithms. The architecture is scalable and does not assume control of local site resources. The job migration policies use the availability and performance of computer systems, the network bandwidth available between systems, and the volume of input and output data associated with each job. An extensive performance comparison is presented using real workloads from leading computational centers. The results, based on several key metrics, demonstrate that the performance of our distributed migration algorithms is significantly greater than that of a local scheduling framework and comparable to a non-scalable global scheduling approach.

Shan, Hong-Zhang↗
DOE OSTI2021

Pressure Effects on the Relaxation of an Excited Ethane Molecule in High-Pressure Bath Gases

Here, we use molecular dynamics to calculate the rotational and vibrational energy relaxation of C 2 H 6 in Ar, Kr, and Xe bath gases over a pressure range of 10 to 400 atm and at temperatures of 300 K and 800 K. The C 2 H 6 is instantaneously excited by 80 kcal/mol randomly distributed into both vibrational and rotational modes. The computed relaxation rates show little sensitivity to the identity of the noble gas in the bath. Vibrational relaxation rates show a non-linear pressure dependence at 300 K. At 800 K the reduced range of bath gas densities covered by the range of pressures do not yet show any non-linearity in the pressure dependence. Rotational relaxation is characterized with two relaxation rates. The slower rate is comparable to the vibrational relaxation rate. The faster rate has a linear pressure dependence at 300 K but an irregular, nonlinear pressure dependence at 800 K. To understand this, a model was developed based on approximating the periodic box used in the molecular dynamics simulations by an equal-volume collection of cubes where each cube is sized to allow only single occupancy by the noble gas or the molecule. Combinatorial statistics then leads to a pressure and temperature dependent analytic distribution of the bath gas species the molecule encounters in a collision. This distribution, the dissociation energy of molecule/bath gas complexes and bath gas clusters, and the computed energy release per collision combine to show that only at 300 K is the energy release sufficient to dissociate likely complexes and clusters. This suggests that persistent and pressure-dependent clusters and complexes at 800 K may be responsible for the non-linear pressure dependence of rotational relaxation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗