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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2025

Projection-based multifidelity linear regression for data-scarce applications

Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to acquire. This work develops multifidelity methods for multiple-input multiple-output linear regression targeting data-limited applications with high-dimensional outputs. Multifidelity methods integrate many inexpensive low-fidelity model evaluations with limited, costly high-fidelity evaluations. We introduce two projection-based multifidelity linear regression approaches with linear and nonlinear features that leverage principal component basis vectors for dimensionality reduction and combine multifidelity data through: (i) a direct data augmentation using low-fidelity data, and (ii) a data augmentation incorporating explicit linear corrections between low-fidelity and high-fidelity data. The data augmentation approaches combine high-fidelity and low-fidelity data into a unified training set and train the linear regression model through weighted least squares with fidelity-specific weights. We introduce a proximity-based weighting scheme with automatic weight selection strategy through cross-validation. Here, the proposed multifidelity linear regression methods are demonstrated on approximating the surface pressure field of a hypersonic vehicle in flight and the temperature field on an aircraft disc braking system. In an ultra low-data regime of no more than twelve high-fidelity samples, multifidelity linear regression achieves approximately 2% – 12% improvement in median accuracy and a higher R 2 score relative to single-fidelity methods at comparable computational cost.

data augmentation↗
NASA NTRS2016

Precipitation and Carbon-Water Coupling Jointly Control the Interannual Variability of Global Land Gross Primary Production

Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO2 concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.

chlorophyll fluorescence↗
DOE OSTI2025

Impact of Grazing Duration and Environment on Soil Carbon in Reclaimed Uranium Mines Tailings: A Region Specific Study

ABSTRACT Grassland ecosystems, which cover over one‐third of the Earth's land area, store 10%–30% of global soil carbon (C). However, these ecosystems face substantial impacts from human activities, including mining. This study investigates the spatial distribution of soil C and related environmental factors in reclaimed grasslands on former uranium mine sites in Wyoming. We hypothesized that grazing duration and environmental factors would influence soil C levels. Interactions between topography, vegetation diversity, soil properties, and soil C in the context of grazing management in both natural and reclaimed grasslands from a wide range of periods from 1 year to 100 years were analyzed using geographically weighted regression models. Data collected from 2022 to 2023 showed that total carbon was consistently higher in natural grasslands (1.2%–4.9%) than in reclaimed grasslands (0.8%–1.3%). Additionally, soil C was significantly higher in natural grasslands grazed for 1 year compared to those grazed for 100 years. In contrast, reclaimed grasslands had lower soil C in areas grazed for 1 year compared to those grazed for 7 or 14 years. The absolute values of coefficients from environmental covariates indicated that areas grazed for a shorter duration (~1 year) were more influenced by biotic and abiotic factors than areas grazed for longer periods (> 7 years). Our findings show moderate grazing increases the resiliency of grassland ecosystems when grazed 7 years or longer and acknowledge the roles of topographic, soil, and vegetative factors in enhancing soil C concentration and developing sustainable land management practices in rangeland conditions.

Shilpakar, Chandan [Department of Plant Sciences U↗
DOE OSTI2016

In situ synchrotron powder diffraction study of the setting reaction kinetics of magnesium-potassium phosphate cements

This work reports a kinetic study of the formation of magnesium-potassium phosphate cements accomplished using in-situ synchrotron powder diffraction. The reaction: MgO + KH{sub 2}PO{sub 4} + 5H{sub 2}O → MgKPO{sub 4} · 6H{sub 2}O was followed in situ in the attempt of contributing to explain the overall mechanism and assess the influence of periclase (MgO) grain size and calcination temperature (1400-1600 °C) on the reaction kinetics. Numerical kinetic parameters for the setting reaction have been provided for the first time. The best fit to the kinetic data was obtained using a weighted nonlinear model fitting method with two kinetic equations, representing two consecutive, partially overlapping processes. MgO decomposition could be described by a first order (F1) model followed by a Jander diffusion (D3) controlled model. Crystallization of the product of reaction was modelled using an Avrami model (A{sub n}) followed by a first order (F1) chemical reaction. A reaction mechanism accounting for such results has been proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Geologic CO2 Input Into Groundwater and the Atmosphere, Soda Springs, ID, USA

A set of CO2 flux, geochemical, and hydrologic measurement techniques was used to characterize the source of and quantify gaseous and dissolved CO2 discharges from the area of Soda Springs, southeastern Idaho. An eddy covariance system was deployed for approximately one month near a bubbling spring and measured net CO2 fluxes from - 74 to 1147 g m- 2 d- 1. An inversion of measured eddy covariance CO2 fluxes and corresponding modeled source weight functions mapped the surface CO2 flux distribution within and quantified CO2 emission rate (24.9 t d- 1) from a 0.05 km2 area surrounding the spring. Soil CO2 fluxes (< 1 to 52,178 g m- 2 d- 1) were measured within a 0.05 km2 area of diffuse degassing using the accumulation chamber method. The estimated CO2 emission rate from this area was 49 t d- 1. A carbon mass balance approach was used to estimate dissolved CO2 discharges from contributing sources at nine springs and the Soda Springs geyser. Total dissolved inorganic carbon (as CO2) discharge for all sampled groundwater features was 57.1 t d- 1. Of this quantity, approximately 3% was derived from biogenic carbon dissolved in infiltrating groundwater, 35% was derived from carbonate mineral dissolution within the aquifer(s), and 62% was derived from deep source(s). Isotopic compositions of helium (1.74–2.37 Ra) and deeply derived carbon (d13C approximately 3‰) suggested contribution of volatiles from mantle and carbonate sources. Assuming that the deeply derived CO2 discharge estimated for sampled groundwater features (approximately 35 t d- 1) is representative of springs throughout the study area, the total rate of deeply derived CO2 input into the groundwater system within this area could be ~ 350 t d- 1, similar to CO2 emission rates from a number of quiescent volcanoes.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

The impact of Uber and Lyft on vehicle ownership, fuel economy, and transit across U.S. cities

We estimate the effects of transportation network companies (TNCs) Uber and Lyft on vehicle ownership, fleet average fuel economy, and transit use in U.S. urban areas using a set of difference-in-difference propensity score-weighted regression models that exploit staggered market entry across the U.S. from 2011 to 2017. We find evidence that TNC entry into urban areas causes an average 0.7% increase in vehicle registrations with significant heterogeneity in these effects across urban areas: TNC entry produces larger vehicle ownership increases in urban areas with higher initial ownership (car-dependent cities) and in urban areas with lower population growth (where TNC-induced vehicle adoption outpaces population growth). We also find no statistically significant average effect of TNC entry on fuel economy or transit use but find evidence of heterogeneity in these effects across urban areas, including larger transit ridership reductions after TNC entry in areas with higher income and more childless households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Polyethylene Upcycling to Liquid Alkanes in Molten Salts under Neat and External Hydrogen Source-Free Conditions

Development of facile approaches to convert plastic waste into liquid fuels under neat conditions is highly desired but challenging, particularly without noble metal catalysts and an external hydrogen source. Herein, highly efficient and selective polyethylene-to-gasoline oil (branched C 6 –C 12 alkanes) conversion was achieved under mild conditions (<170 °C) using commercially available AlCl 3 -containing molten salts as reaction media and to provide catalytic sites (no extra solvents, additives, or hydrogen feeding). The high catalytic efficiency and selectivity was ensured by the abundant active Al sites with strong Lewis acidity (comparable to the Al type in acidic zeolite) and highly ionic nature of the molten salts to stabilize the carbenium intermediates. Dynamic genesis of the Al sites was elucidated via time-resolved Al K-edge soft X-ray and 27 Al NMR, confirming the tricoordinated Al 3+ as active sites and its coordination with the as-generated alkene/aromatic intermediates. Further, the carbenium formation and polyethylene chain variation was illustrated by inelastic neutron scattering (INS) and an isotope-labeling experiment. Theoretical simulations further demonstrated the successive hydride abstraction, β-scission, isomerization, and internal hydrogen transfer reaction pathway with AlCl 3 as active sites. This facile catalytic system can further achieve the conversion of robust, densely assembled, and high molecular weight plastic model compounds to liquid alkane products in the diesel range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Work from Home Patterns across COVID-19 Waves: Implications for Future Transportation

The unprecedented rise in work from home (WFH) during COVID-19 poses challenges for the transportation engineers and planners with the travel demand forecasting. If WFH persists post-pandemic, it could influence traffic patterns, reducing peak-hour congestion. However, the evolution of WFH decisions across pandemic phases and varying socio-economic contexts remains unclear. This study examines factors influencing WFH choices using data from the US Census Bureau’s Household Pulse Survey. Findings reveal a decline in WFH participation from 60% during the first wave to 38% by the third wave of the COVID-19 pandemic. A Geographically Weighted Regression model highlights the influence of socio-economic, household, and COVID-19-related variables, with notable spatial variability. Results show that younger individuals, females, and households with children are consistently more likely to WFH, while non-white and higher income individuals have an increasing likelihood for WFH as the pandemic progresses. These insights inform future transportation planning, emphasizing equity and decentralization strategies for post-pandemic commuting.

Patwary, Latif [ORNL] (ORCID:0000000189174928)↗
DOE OSTI2013

EXTINCTION AND DUST GEOMETRY IN M83 H II REGIONS: AN HUBBLE SPACE TELESCOPE/WFC3 STUDY

We present Hubble Space Telescope/WFC3 narrow-band imaging of the starburst galaxy M83 targeting the hydrogen recombination lines (Hβ, Hα, and Paβ), which we use to investigate the dust extinction in the H II regions. We derive extinction maps with 6 pc spatial resolution from two combinations of hydrogen lines (Hα/Hβ and Hα/Paβ), and show that the longer wavelengths probe larger optical depths, with A{sub V} values larger by ≳1 mag than those derived from the shorter wavelengths. This difference leads to a factor ≳2 discrepancy in the extinction-corrected Hα luminosity, a significant effect when studying extragalactic H II regions. By comparing these observations to a series of simple models, we conclude that a large diversity of absorber/emitter geometric configurations can account for the data, implying a more complex physical structure than the classical foreground ''dust screen'' assumption. However, most data points are bracketed by the foreground screen and a model where dust and emitters are uniformly mixed. When averaged over large (≳100-200 pc) scales, the extinction becomes consistent with a ''dust screen'', suggesting that other geometries tend to be restricted to more local scales. Moreover, the extinction in any region can be described by a combination of the foreground screen and the uniform mixture model with weights of 1/3 and 2/3 in the center (≲2 kpc), respectively, and 2/3 and 1/3 for the rest of the disk. This simple prescription significantly improves the accuracy of the dust extinction corrections and can be especially useful for pixel-based analyses of galaxies similar to M83.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Vehicle Lightweighting: 40% and 45% Weight Savings Analysis: Technical Cost Modeling for Vehicle Lightweighting

The U.S. Department of Energy’s Vehicle Technologies Office, Materials area commissioned a study to model and assess manufacturing economics of alternative design and production strategies for a series of lightweight vehicle concepts. The strategic targets were a 40% and a 45% mass reduction relative to a standard North American midsize passenger sedan at an effective cost of $3.42 per pound (lb) saved. The baseline vehicle was an average of several available vehicles in this class. Mass and cost breakdowns from several sources were used, including original equipment manufacturers’ (OEMs’) input through U.S. Department of Energy’s Vehicle Technologies Office programs and public presentations, A2Mac1 LLC’s teardown information, Lotus Engineering Limited and FEV, Inc. breakdowns in their respective lightweighting studies, and IBIS Associates, Inc.’s decades of experience in automotive lightweighting and materials substitution analyses. Information on lightweighting strategies in this analysis came from these same sources and the ongoing U.S. Department of Energy-funded Vehma International of America, Inc. /Ford Motor Company Multi-Material Lightweight Prototype Vehicle Demonstration Project, the Aluminum Association Transportation Group, and many United States Council for Automotive Research’s/United States Automotive Materials Partnership LLC lightweight materials programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Product Innovation to Increase Low-to-Moderate-Income Customers' Adoption of Community Solar PV

This study aims to comprehensively analyze community solar project preferences for consumers and suppliers by conducting three distinct analyses. First we analyze the predictors of community solar contract adoption to understand how individual priorities affect the probability of adoption. Using an original data set of survey responses from potential community solar customers, we analyzed the predictors of contract adoption by employing a weighted logit model. We find that individuals who were previously familiar with community solar projects were significantly more likely to adopt than those who were not familiar. Secondly, a survey of community solar developers and financiers identified industry perceived barriers to community solar access and inclusion. Thirdly, we gathered payment performance information from community solar initiatives to measure how financial risks are perceived and how they interact with customer demographics. Our study is beneficial to the public by providing insights into the drivers and barriers of community solar adoption and sheds light on the importance of understanding individual priorities in designing effective community solar policies. The community solar industry has changed significantly since the beginning of this project. The industry continues to grow at a rapid rate, with an additional 7 gigawatts expected to come online between 2022 and 2027. With federal pressure to meet climate goals, as the harms of climate change continue to impact everybody, legislators are looking to community solar as a method to achieving their states energy policy goals. These new policies that push for low-to-moderate inclusion, coupled with the increase in community solar capacity illustrate a new era for the community solar industry. A number of policies have arisen in the last few months that push for more inclusive practices including the groundbreaking Solar for All program run by the EPA. The research created a “best practice” contract that can then be used, in conjunction with the manuscript and validated study, to pitch the industry on a more inclusive community solar product.

14 SOLAR ENERGY↗
DOE OSTI2020

Dynamic Topology Reconfiguration of Boltzmann Machines on Quantum Annealers

Boltzmann machines have useful roles in deep learning applications, such as generative data modeling, initializing weights for other types of networks, or extracting efficient representations from high-dimensional data. Most Boltzmann machines use restricted topologies that exclude looping connectivity, as such connectivity creates complex distributions that are difficult to sample. We have used an open-system quantum annealer to sample from complex distributions and implement Boltzmann machines with looping connectivity. Further, we have created policies mapping Boltzmann machine variables to the quantum bits of an annealer. These policies, based on correlation and entropy metrics, dynamically reconfigure the topology of Boltzmann machines during training and improve performance.

Liu, Jeremy (ORCID:0000000172299417)↗
NASA NTRS1979

Orbit/attitude estimation with LANDSAT Landmark data

The use of LANDSAT landmark data for orbit/attitude and camera bias estimation was studied. The preliminary results of these investigations are presented. The Goddard Trajectory Determination System (GTDS) error analysis capability was used to perform error analysis studies. A number of questions were addressed including parameter observability and sensitivity, effects on the solve-for parameter errors of data span, density, and distribution an a priori covariance weighting. The use of the GTDS differential correction capability with acutal landmark data was examined. The rms line and element observation residuals were studied as a function of the solve-for parameter set, a priori covariance weighting, force model, attitude model and data characteristics. Sample results are presented. Finally, verfication and preliminary system evaluation of the LANDSAT NAVPAK system for sequential (extended Kalman Filter) estimation of orbit, and camera bias parameters is given.

Hall, D. L.↗
NASA NTRS1944

The NACA Impact Basin and Water Landing Tests of a Float Model at Various Velocities and Weights

The first data obtained in the United States under the controlled testing conditions necessary for establishing relationships among the numerous parameters involved when a float having both horizontal and vertical velocity contacts a water surface are presented. The data were obtained at the NACA impact basin. The report is confined to a presentation of the relationship between resultant velocity and impact normal acceleration for various float weights when all other parameters are constant. Analysis of the experimental results indicated that the maximum impact normal acceleration was proportional to the square of the resultant velocity, that increases in float weight resulted in decreases in the maximum impact normal acceleration, and that an increase in the flight-path angle caused increased impact normal acceleration.

Batterson, Sidney A↗