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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Biogeochemical cycling of manganese in Oneida Lake, New York: whole lake studies of manganese

Oneida Lake, New York is a eutrophic freshwater lake known for its abundant manganese nodules and a dynamic manganese cycle. Temporal and spatial distribution of soluble and particulate manganese in the water column of the lake were analyzed over a 3-year period and correlated with other variables such as oxygen, pH, and temperature. Only data from 1988 are shown. Manganese is removed from the water column in the spring via conversion to particulate form and deposited in the bottom sediments. This removal is due to biological factors, as the lake Eh/pH conditions alone can not account for the oxidation of the soluble manganese Mn(II). During the summer months the manganese from microbial reduction moves from the sediments to the water column. In periods of stratification the soluble Mn(II) builds up to concentrations of 20 micromoles or more in the bottom waters. When mixing occurs, the soluble Mn(II) is rapidly removed via oxidation. This cycle occurs more than once during the summer, with each manganese atom probably being used several times for the oxidation of organic carbon. At the end of the fall, whole lake concentrations of manganese stabilize, and remain at about 1 micromole until the following summer, when the cycle begins again. Inputs and outflows from the lake indicate that the active Mn cycle is primarily internal, with a small accumulation each year into ferromanganese nodules located in the oxic zones of the lake.

NASA Discipline Exobiology↗
NASA NTRS2014

NASA Glenn Research Center Support of the ASRG Project

A high efficiency radioisotope power system is being developed for long-duration NASA space science missions. The U.S. Department of Energy (DOE) managed a flight contract with Lockheed Martin Space Systems Company (LMSSC) to build Advanced Stirling Radioisotope Generators (ASRGs), with support from NASA Glenn Research Center (GRC). Sunpower Inc. held two parallel contracts to produce Advanced Stirling Convertors (ASCs), one with DOELockheed Martin to produce ASC-F flight units, and one with GRC for the production of ASC-E3 engineering unit pathfinders that are built to the flight design. In support of those contracts, GRC provided testing, materials expertise, government furnished equipment, inspections, and related data products to DOELockheed Martin and Sunpower. The technical support includes material evaluations, component tests, convertor characterization, and technology transfer. Material evaluations and component tests have been performed on various ASC components in order to assess potential life-limiting mechanisms and provide data for reliability models. Convertor level tests have been used to characterize performance under operating conditions that are representative of various mission conditions. Technology transfers enhanced contractor capabilities for specialized production processes and tests. Despite termination of flight ASRG contract, NASA continues to develop the high efficiency ASC conversion technology under the ASC-E3 contract. This paper describes key government furnished services performed for ASRG and future tests used to provide data for ongoing reliability assessments.

Technology Transfer↗
DOE OSTI2020

Natural Gas Vehicle Basics

Natural gas powers about 175,000 U.S. vehicles and more than 23 million vehicles worldwide [1]. Natural gas vehicles (NGVs) are a good choice for high-mileage (high fuel-use) fleets - such as buses, medium- and heavy-duty trucks, and refuse vehicles - that are centrally fueled or operate within a limited area or along a route with natural gas fueling stations. The advantages of natural gas as an alternative fuel include its domestic production, established distribution network, relatively low cost, and emissions benefits.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Data from: No‐till establishment improves the climate benefit of bioenergy crops on marginal grasslands

Expanding biofuel production is expected to accelerate the conversion of unmanaged marginal lands to meet biomass feedstock needs. Greenhouse gas production during conversion jeopardizes ensuing climate benefits, but most research to date has focused only on conversion to annual crops and only following tillage. Here we report the global warming impact of converting USDA Conservation Reserve Program (CRP) grasslands to three types of bioenergy crops using no-till (NT) versus conventional tillage (CT). In three CRP fields planted to continuous corn, switchgrass, or restored prairie we established replicated NT and CT plots. For the two years following an initial soybean year in all fields, we found that, on average, NT conversion reduced nitrous oxide (N2O) emissions by 50% and carbon dioxide (CO2) emissions by 20% compared to CT conversion. Differences were higher in year 1 than in year 2 in the continuous corn field, and in the two perennial systems the differences disappeared after year 1. In all fields net CO2 emissions (as measured by eddy covariance) were positive for the first two years following CT establishment, but following NT establishment net CO2 emissions were close to zero or negative, indicating net C sequestration. Overall, NT improved the global warming impact of biofuel crop establishment following CRP conversion by over 20-fold compared to CT (-6.01 Mg CO2e ha-1 yr-1 for NT vs. -0.25 Mg CO2e ha-1 yr-1 for CT, on average). We also found that IPCC estimates of N2O emissions (as measured by static chambers) greatly underestimated actual emissions for converted fields regardless of tillage. Policies should encourage adoption of NT for converting marginal grasslands to perennial bioenergy crops in order to reduce carbon debt and maximize climate benefits.

09 BIOMASS FUELS↗
NASA NTRS1976

Interactive analysis of thermal imagery

Necessary knowledge is presented on data acquisition and preparation for analysis of thermal imagery of power plant heated discharges remotely sensed from an aircraft, with special emphasis on analog to digital conversion of analog tapes acquired during scanning and to geometrical scaling. The central element in the interactive analysis of thermal imagery is an interactive graphics computer terminal which allows an interpreter to effectively interact with a large-scale computer, providing decisions or data as computations are carried out. A temperature calibration is performed, which the interpreter may test anywhere on the image. When satisfied that calibration is correct, the portion of the image to be analyzed is outlined. Printed and microfiche analyses of the plume are produced. The flow chart of programs for analysis of thermal imagery is presented and discussed in some detail.

Madding, R. P.↗
NASA NTRS2023

An Assessment of Stratospheric Water Vapor Trends and Variations Above the Boulder Region

This study analyzes time series of stratospheric water vapor (SWV) data at 30 hPa, based on frost-point hygrometer (FPH) measurements at Boulder, CO (40°N, 255°E), and on sets of HALOE scans above that region for 1993 through 2005; their differing trends agree with previously published findings. Yet, there is an apparent switch over in 2002 from positive to negative trends in the HALOE time series, and that change follows the episodic decrease of tropical, lower stratospheric SWV in early 2001. The HALOE data points only resolve medium to large scale spatial variations, as they are based on an average of four or more limb scans within a latitude/longitude sector near Boulder. The FPH time series do not indicate a similar change of trend in 2002, although its time series points have variations about the mean that are twice as large as those from HALOE. The FPH soundings are sensitive to variations from all spatial scales, however, including the effects of a local vertical mixing of the air due to gravity waves. The vertical gradient SWV mixing ratio with altitude is positive at 30 hPa. There is also a positive trend in methane and its conversion to water vapor during this time that may explain a slightly larger SWV trend from the local FPH data than from the HALOE data. The Nimbus 7 LIMS experiment provides daily SWV plots at medium to large scales during the dynamically active, winter and springtime periods, for assessing the effects of meridional transport of SWV from its source regions. There is transport of high SWV from polar regions and of lower SWV from the subtropics at those times. SWV variations and trends from both the FPH and HALOE time series are reasonable and in accord with the spatial scales that they observed.

Ellis Remsberg↗
NASA NTRS2019

A Compilation of Global Bio-Optical in Situ Data for Ocean-Colour Satellite Applications – Version Two

A global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONETOC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at https://doi.org/10.1594/PANGAEA.898188.

Andre Valente↗
DOE OSTI2023

Using Data-Driven Prediction of Downstream 1D River Flow to Overcome the Challenges of Hydrologic River Modeling

Methods for downstream river flow prediction can be categorized into physics-based and empirical approaches. Although based on well-studied physical relationships, physics-based models rely on numerous hydrologic variables characteristic of the specific river system that can be costly to acquire. Moreover, simulation is often computationally intensive. Conversely, empirical models require less information about the system being modeled and can capture a system’s interactions based on a smaller set of observed data. This article introduces two empirical methods to predict downstream hydraulic variables based on observed stream data: a linear programming (LP) model, and a convolutional neural network (CNN). We apply both empirical models within the Colorado River system to a site located on the Green River, downstream of the Yampa River confluence and Flaming Gorge Dam, and compare it to the physics-based model Streamflow Synthesis and Reservoir Regulation (SSARR) currently used by federal agencies. Results show that both proposed models significantly outperform the SSARR model. Moreover, the CNN model outperforms the LP model for hourly predictions whereas both perform similarly for daily predictions. Although less accurate than the CNN model at finer temporal resolution, the LP model is ideal for linear water scheduling tools.

13 HYDRO ENERGY↗
NASA NTRS2013

Inclusion of Linearized Moist Physics in Nasa's Goddard Earth Observing System Data Assimilation Tools

Inclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa-Schubert (RAS) convection scheme has been developed and tested in NASA's Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encountered. Efficient filtering of these profiles is achieved by diagnosis of steep gradients in a reduced version of the operator of the tangent linear model. With filtering turned on, the inclusion of linearized moist physics increases the correlation between the nonlinear perturbation trajectory and the linear approximation of the perturbation trajectory. A month-long observation impact experiment is performed and the effect of including moist physics on the impacts is discussed. Impacts from moist-sensitive instruments and channels are increased. The effect of including moist physics is examined for adjoint sensitivity studies. A case study examining an intensifying Northern Hemisphere Atlantic storm is presented. The results show a significant sensitivity with respect to moisture.

Convection↗
DOE OSTI2024

Machine learning-aided inverse design for biogas upgrading through biological CO 2 conversion

The biogas upgrading process through bioconversion of CO 2 to CH 4 by hydrogenotrophic methanogens is an attractive strategy for energy decarbonation. Many studies have optimized operational parameters to improve key performance indicators such as CH 4 % and H 2 utilization efficiency. However, inconsistent laboratory conditions make it challenging to compare results. Existing models for analyzing operating conditions can only assess the impact of individual conditions and lack the ability to simultaneously optimize multiple conditions. To address this, two XGBoost models were built with R 2 of 0.779 and 0.903 with data collected from literatures and were embedded into multi-objective partitive swarm optimization algorithm to optimal operating conditions. Predictions were compared with experimental validations under optimized conditions, revealing an 8.50% and 2.95% relative error in CH 4 % and H 2 conversion rate, respectively. This approach streamlines biogas upgrading processes, offering a data-driven solution to enhance efficiency and consistency in the pursuit of sustainable methane production.

Biogas upgrading↗
DOE OSTI2021

Consensus International Solar Resource Standards and Best Practices Development

Standardization and best practices of data sets and models enable the industry to develop widely accepted protocols adapted to various stages of solar project development and operations. In collaboration with the International Energy Agency Photovoltaic Power Systems Programme Task 16, the National Renewable Energy Laboratory (NREL) developed and regularly updates the Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications. In collaboration with ASTM's radiometry subcommittee, NREL leads the development of various radiometric standards. These contribute to increased accuracy in the measurement of the solar resource available to conversion systems and boost the development and improvement of radiative models. These models can then provide the long-term geographic or climatic distribution of solar radiation for areas where measured solar data are not available. Further, these standards play a preeminent role in all aspects of solar energy projects, including standard conditions, methods and instrumentation, accelerated testing, and service lifetime of materials.

ASTM↗
NASA NTRS2019

Dynamic RPS Path to Flight

NASA Glenn Research Center has been pursuing the development of dynamic power conversion for several decades. Candidate NASA missions involve mutli-year travel to far away destinations, or to extreme environments where sunlight does not exist. Human-base mission studies also show that power needs would be beyond the capabilities of solar energy conversion, and instead would require nuclear reactor energy sources, for which the thermal energy must be converted to electricity. Dynamic power conversion technology has developed sufficiently to make a sound engineering argument that it is suitable for these NASA missions. Dynamic conversion power sources have yet to be flown in space, and thus suffer a disadvantage owing to their lack of heritage data on flight missions. One of the largest obstacles for adoption is the uncertainty in reliability of a device with moving parts. However, significant progress has been made toward demonstrating the technology capable in all relevant environments, with the necessary long life. Another hurdle for adoption is the lack of mission, which would drive specific requirements, and provide a solid timeline for technology development endpoint. Until a mission is identified, an alternative approach is necessary to advance a dynamic power conversion system towards flight.

Oriti, Sal↗
NASA NTRS2019

Dynamic RPS Path to Flight - Nuclear and Emerging Technologies for Space

NASA Glenn Research Center has been pursuing the development of dynamic power conversion for several decades. Candidate NASA missions involve mutli-year travel to far away destinations, or to extreme environments where sunlight does not exist. Human-base mission studies also show that power needs would be beyond the capabilities of solar energy conversion, and instead would require nuclear reactor energy sources, for which the thermal energy must be converted to electricity. Dynamic power conversion technology has developed sufficiently to make a sound engineering argument that it is suitable for these NASA missions. Dynamic conversion power sources have yet to be flown in space, and thus suffer a disadvantage owing to their lack of heritage data on flight missions. One of the largest obstacles for adoption is the uncertainty in reliability of a device with moving parts. However, significant progress has been made toward demonstrating the technology capable in all relevant environments, with the necessary long life. Another hurdle for adoption is the lack of mission, which would drive specific requirements, and provide a solid timeline for technology development endpoint. Until a mission is identified, an alternative approach is necessary to advance a dynamic power conversion system towards flight.

Oriti, Salvatore↗
DOE OSTI2022

Developing new pathways for energy and environmental decision-making in India: a review

Abstract India faces a dual challenge of economic development and responding to climate change. Although India’s per capita emissions are well below global average, the country is one of the world’s largest greenhouse gas emitters. Indian policymakers and stakeholders require high-quality data and research to assess low-emissions, sustainable development strategies. Peer-reviewed literature is a key source of this information and also a key venue for conversation amongst research leaders. This paper examines the recent peer-reviewed literature on India’s 2030 and 2050 pathways. We conducted a systematic literature review to identify key quantitative national modeling studies. From the 34 studies identified, we synthesized scenario data to draw common conclusions and identify critical research gaps. The main focus was on examining the coverage and the state of information available on low-carbon pathways. Overall, we find a few scenarios that are potentially consistent with a 2070 net-zero goal, but more limited assessment of pathways to reach net-zero emissions before this date. Mitigation pathways with greater ambition are required across all energy sectors to ensure a smooth transition to net-zero emissions by or before 2070. The scenarios confirm that reducing emissions to below 2 GtCO 2 yr −1 by mid-century would necessitate significant transformations of the Indian energy sector, such as, a decrease in unabated coal power capacity, transportation modal shift, and industrial process switching. The assessment also finds substantial differences in final energy estimates reported across studies, particularly in transportation. The lack of consistency in, and transparency about underlying drivers, assumptions, and even outputs across studies points to the critical need for the sorts of coordinated, multi-model studies that have proven exceptionally valuable for decision makers in other major emitting countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Software and Hardware Development for the Mu2e Trigger and Data Acquisition System

The Mu2e experiment at Fermilab will be 10,000 times more sensitive than previous experiments looking for muon-to-electron conversion. This precise and complex experimental apparatus will produce 200 million billion muons per year. The accelerator complex repurposes elements of the infrastructure that produced high energy proton and anti-protons beams for the Tevatron experiments to produce the high-intensity muon beams necessary for Mu2e and the Muon (g-2) experiments.

43 PARTICLE ACCELERATORS↗
NASA NTRS1985

External calibration of SIR-B imagery with area-extended and point targets

Data-takes on two ascending orbits of the Shuttle Imaging Radar-B (SIR-B) over an agricultural test site in west-central Illinois were used to establish end-to-end transfer functions for conversion of the digital numbers on the 8-bit image to values of the radar backscattering coefficient sigma sup 0 (sq m/sq. m) in dB. The transfer function for each data-take was defined by the SIR-B response to an array of six calibrated point targets of known radar cross-section (transponders) and to a large number of area-extended targets also with known radar cross-section as measured by externally calibrated, truck-mounted scatterometers. The radar cross-section of each transponder at the SIR-B center frequency was measured on an antenna range as a function of local angle of incidence. Two truck-mounted scatterometers observed 20 to 80 agricultural fields daily at 1.6 GHz with HH polarization and at azimuth viewing angles and incidence angles equivalent to those of the SIR-B. The form of the transfer function is completely defined by the SIR-B receiver and the incoherent averaging procedure incorporated into production of the standard SIR-B image product.

Dobson, M. C.↗
DOE OSTI2025

An experimental and numerical investigation of HD diesel engine DOC efficiency in oxidizing NO to NO 2

Reducing pollutant emissions from heavy-duty (HD) diesel engines is critical due to their significant environmental impact, particularly concerning NOx emissions. Understanding and optimizing modern diesel oxidation catalyst (DOC) and selective catalytic reduction (SCR) performance is essential for improving exhaust aftertreatment (EAT) system efficiency to meet stringent emissions regulations. The oxidation of nitric oxide (NO) to nitrogen dioxide (NO 2 ) in DOC plays a key role in improving SCR efficiency in reducing NO x . This study investigates the DOC performance in oxidizing NO to NO2 and its impact on the SCR efficiency of a 2021 MY Navistar E39 HD diesel engine. The influence of engine speed, load, exhaust gas temperature, and composition on DOC efficiency is experimentally investigated. The relationships between DOC inlet temperature, oxygen availability and NO 2 /NO x ratio at the DOC inlet are examined to better understand their effects on the overall DOC efficiency. The results indicate that DOC NO oxidation efficiency is highly dependent on exhaust temperature, with optimal oxidation occurring within a specific temperature range (275-350°C). Below this threshold, the chemical reactions are kinetically limited, while at higher temperatures, thermodynamic constraints reduce the efficiency of DOC in oxidizing NO to NO 2 . The experimental data further reveal that the NO 2 /NO x ratio peaks at medium loads before declining at higher loads due to reduced residence time and mass transfer effects. Additionally, the SCR NO x conversion efficiency is significantly influenced by the NO 2 /NO x ratio, achieving peak performance when the NO 2 /NO x ratio approaches 0.5. A DOC chemistry model was developed and validated against the experimental data to predict DOC oxidation behavior under various operating conditions. The findings of this study provide insights into the interdependencies between DOC and SCR performance, contributing to the optimization of SCR systems for optimized NOx reduction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗