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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluating the Performance of Random Forest and Iterative Random Forest Based Methods when Applied to Gene Expression Data

Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression Networks (PEN) capture relationships between genes and are beneficial for use in downstream biological analyses. There exists multiple network inference tools to produce these gene-to-gene networks from matrices of gene expression data. Random Forest-Leave One Out Prediction (RF-LOOP) is a method that has been shown to be efficient at producing these gene-to-gene networks, frequently known as GEne Network Inference with Ensemble of trees (GENIE3). Here we validate that iterative Random Forest-Leave One Out Prediction (iRF-LOOP) produces higher quality networks than GENIE3. We use both synthetic and empirical networks from the Dialogue for Reverse Engineering Assessment and Methods (DREAM) Challenges by Sage Bionetworks, as well as two additional empirical networks created from Arabidopsis thaliana and Populus trichocarpa expression data.

iRF-Loop, expression network, Populus Trichocarpa↗
DOE OSTI2023

Simulation of a rapid compression machine for evaluation of ignition chemistry and soot formation using gasoline/ethanol blends

Due to the projected decline of demand for gasoline in light duty engines and the advent of ethanol as a green fuel, the use of gasoline/ethanol blend fuels in heavy duty applications are being investigated as they are projected to have lower cost and lower lifecycle green house gas (GHG) emissions. In heavy duty engines, the primary mode of combustion is mixing controlled combustion where wide range of mixture conditions (equivalence ratio) exist. Soot emissions of these fuels in richer conditions are not well understood. The goal of this research is to evaluate some commercially available soot modeling codes for the particulate matter emissions from gasoline/ethanol fuel blends, especially at fuel rich conditions. A Rapid Compression Machine (RCM) is modeled in a three-dimensional numerical simulation using CONVERGE computational software using a reduced chemical kinetic mechanism with SAGE chemistry solver and a RANS k-ϵturbulence model with a sector model including the creviced piston. The creviced piston is used in the experimental setup to reduce boundary layer effects and to maintain a homogeneous core in the reaction cylinder. Computational fluid dynamics simulations are conducted for different gasoline-ethanol fuel blends from E10 (10% ethanol v/v) to E100. The fuel blend is modeled as a surrogate mixture of toluene, iso-octane, n-heptane for gasoline content, and ethanol. The computational results were validated against experimental results using pressure measurements and laser extinction diagnostics. Different soot models are investigated to evaluate their capability of predicting the sooting tendencies of fuel blends, especially in richer conditions experienced during mixing-controlled combustion. The experimental combustion characteristics such as the ignition delay of different blends of fuel are reasonably well predicted. The Particulate Size Mimic (PSM) model accurately predicts the soot generation characteristics of the different fuels, but the Hiroyasu-NSC model falls short in this regard. For accurate prediction of soot with the PSM model, the thermodynamic conditions during combustion must be accurately modeled. While the current computational modeling tools can produce accurate results for the prediction of particulate matter emissions, there is much work to be done in improving our understanding of the underlying fundamental processes.

Energy & Fuels↗
DOE OSTI2022

A Study of Propane Combustion in a Spark-Ignited Cooperative Fuel Research (CFR) Engine

Liquefied petroleum gas (LPG), whose primary composition is propane, is a promising candidate for heavy-duty vehicle applications as a diesel fuel alternative due to its CO 2 reduction potential and high knock resistance. To realize diesel-like efficiencies, spark-ignited LPG engines are proposed to operate near knock-limit over a wide range of operating conditions, which necessitates an investigation of fuel-engine interactions that leads to end-gas autoignition with propane combustion. This work presents both experimental and numerical studies of stoichiometric propane combustion in a sparkignited (SI) cooperative fuel research (CFR) engine. Engine experiments are initially conducted at different compression ratio (CR) values, and the effects of CR on engine combustion are characterized. A three-pressure analysis (TPA) model based on the two-zone combustion concept is developed in GT-Power and validated using test results to estimate in-cylinder wall temperatures, residual gas fraction, etc. This model is further utilized to examine end-gas chemistry by enabling the SI turbulent flame combustion and unburned gas chemical kinetics modules. Finally, a three-dimensional (3D) computational fluid dynamic (CFD) model of the CFR engine is developed in CONVERGE, where the G-equation and SAGE detailed chemical kinetics models are implemented for combustion modeling. Here, a 153 species reduced chemical kinetics mechanism derived from the detailed NUIGMech1.1 mechanism based on the ignition delay and laminar flame speed (LFS) studies is used to generate an LFS lookup table and to describe end-gas autoignition chemistry. Multi-cycle Reynolds-averaged Navier-Stokes (RANS) simulations are then performed for the tested CRs, and the numerical model is shown to be capable of predicting the propane combustion characteristics, particularly the end-gas autoignition behavior.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Viability Assessment of Wind and Solar Renewable Energy Generation in Support of Nationwide Vehicle Electrification

In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals, multiple computational frameworks are used to locate suitable land for renewable infrastructure development, and to quantify spatiotemporal variations in the potential energy generation and financial viability of development sites across the Unites States. First, the Oak Ridge Siting Analysis for power Generation Expansion tool (OR-SAGE) is used to assess the suitability of land for potential wind and solar energy development across the contiguous U.S. From there, resource data from the National Solar Radiation Database (NSRDB) and the Wind Integration National Dataset (WIND) are used in concert with the National Renewable Energy Laboratory (NREL) Renewable Energy Potential (ReV) model to calculate the variation in potential generation capacity for each resource. Additionally, the capital and operational expenditures are calculated for an example configuration of each renewable technology. These measures are then used to calculate the levelized cost of energy (LCOE) of potential sites. All of these results are then processed and analyzed to determine where in the U.S. solar and wind energy are most viable. This viability is based on available generation potential, consistency and stability of energy generation over time, and economic viability with respect to LCOE.

Miller, Brandon [ORNL] (ORCID:0009000300169201)↗
DOE OSTI2023

Optimizing cloud motion estimation on the edge with phase correlation and optical flow

Abstract. Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transform. In this study, we investigate the performance and the stability of the blockwise PC method by changing the block size, the frame interval, and combinations of red, green, and blue (RGB) channels from the total sky imager (TSI) at the United States Atmospheric Radiation Measurement user facility's Southern Great Plains site. We find that shorter frame intervals, followed by larger block sizes, are responsible for stable estimates of the CMV, as suggested by the higher autocorrelations. The choice of RGB channels has a limited effect on the quality of CMVs, and the red and the grayscale images are marginally more reliable than the other combinations during rapidly evolving low-level clouds. The stability of CMVs was tested at different image resolutions with an implementation of the optimized algorithm on the Sage cyberinfrastructure test bed. We find that doubling the frame rate outperforms quadrupling the image resolution in achieving CMV stability. The correlations of CMVs with the wind data are significant in the range of 0.38–0.59 with a 95 % confidence interval, despite the uncertainties and limitations of both datasets. A comparison of the PC method with constructed data and the optical flow method suggests that the post-processing of the vector field has a significant effect on the quality of the CMV. The raindrop-contaminated images can be identified by the rotation of the TSI mirror in the motion field. The results of this study are critical to optimizing algorithms for edge-computing sensor systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

The anatomy of an anomaly

An anomalous tonal pattern, apparently associated with the Beaver Creek oil field in central Wyoming, was identified using an MSS Band 5 to 4 ratio image made from digital LANDSAT data. This pattern was attributed to an increase in iron with rocks and/or soils which might have resulted from escaping hydrocarbons. The nature of this anomaly was investigated by producing several different combinations of band ratios and by conducting appropriate field studies. The results indicated (1) the existence of a well-defined oval feature related to exposure of iron-cemented red sandstones in a badlands topography, (2) a broader iron-influenced anomaly surrounding this feature, and (3) a spectral response of the rocks, soils, and alluvium making up this iron-colored surface that is readily distinguishable from that of iron-rich reddish Chugwater siltstones exposed in nearby anticlines. The general pattern of the broad anomaly extending beyond the Beaver Creek field is controlled by several factors including variations in vegetation (mainly sage and tall grasses), soil composition and moisture, and topography in addition to variations in iron content of the rock materials. From the available evidence, there is no provable correlation between the oval or the broad anomalies and the distribution of petroleum-producing structures or possible surface alteration effects related to uranium deposits known to occur within this region.

Short, N. M.↗
NASA NTRS1976

LACIE performance predictor final operational capability program description, volume 2

Given the swath table files, the segment set for one country and cloud cover data, the SAGE program determines how many times and under what conditions each segment is accessed by satellites. The program writes a record for each segment on a data file which contains the pertinent acquisition data. The weather data file can also be generated from a NASA supplied tape. The Segment Acquisition Selector Program (SACS) selects data from the segment reference file based upon data input manually and from a crop window file. It writes the extracted data to a data acquisition file and prints two summary reports. The POUT program reads from associated LACIE files and produces printed reports. The major types of reports that can be produced are: (1) Substrate Reference Data Reports, (2) Population Mean, Standard Deviation and Histogram Reports, (3) Histograms of Monte Carlo Statistics Reports, and (4) Frequency of Sample Segment Acquisitions Reports.

Source record↗
NASA NTRS1979

Theoretical simulation of solar spectra in the middle ultraviolet and visible for atmospheric trace constituent measurements

The data compiled during the study allowed a detailed examination of the attenuation of the solar radiance by the combined effect of the atmospheric trace gases and the SAGE filters. The case of the 0.44 microns channel is presented. The amounts of NO2, NO2, O3 and the airmass were chosen to closely simulate a low sun spectral scan from a 9 February 1977 balloon flight. The solar radiance outside the earth's atmosphere was determined from the AFGL Sacramento Peak Observatory spectral data tape degraded to 2.0A resolution and normalized to Thekaekara's absolute intensities. The spectral absorption coefficients used for NO2 and O3 were tabulated previously.

Goldman, A.↗
NASA NTRS1978

HCMM/SAGE test results

The salient features of the nickel cadmium batteries used in the Heat Capacity Mapping Mission spacecraft and the SAGE satellite are presented. Life tests, battery profiles, and recommendations for structural improvement are reported.

Ford, F.↗
NASA NTRS1978

Statistical sampling analysis for stratospheric measurements from satellite missions

Earth orbiting satellite experiments can be designed to measure stratospheric constituents such as ozone by utilizing remote sensing techniques. Statistical analysis techniques, mission simulation and model development have been utilized to develop a method for analyzing various mission/sensor combinations. Existing and planned NASA satellite missions such as Nimbus-4 and G, and Stratospheric Aerosol and Gas Experiment-Application Explorer Mission (SAGE-AEM) have been analyzed to determine the ability of the missions to adequately sample the global field.

Drewry, J. W.↗
NASA NTRS1980

Remote sensing of the middle atmospheric aerosol

It is shown that current or planned spacecraft measurements could contribute toward the input data required for studies of natural anthropogenic influences on the middle atmosphere and their effects on weather and climate. Emphasis is placed on the solar occultation sounding technique used in the SAGE I experiment on board the Atmospheric Explorer Mission B spacecraft. It is shown that the aerosol and ozone number densities cannot be recovered simultaneously without introducing some formula for the aerosol extinction, or assumptions on the form of the aerosol size distribution.

Fymat, A. L.↗
NASA NTRS1981

Satellite and correlative measurements of the stratospheric aerosol. I An optical model for data conversions

A description is presented of an empirically based model of stratospheric aerosol optical properties (size distributions and refractive indices) and their variations. The need for such a model arose in the data validation and archival programs for two satellite sensors, SAM II and SAGE. These programs require the ability to convert measurements of a given aerosol macroproperty (e.g., volume extinction coefficient, volume backscatter coefficient, particle number or mass per unit volume) to best estimates of other aerosol macroproperties, and to assess quantitatively the uncertainties in the conversion process. The described model provides the information on size distributions, refractive indices and their variations necessary for these tasks, and also defines a procedure for combining the model information with empirical data in a way that facilitates automatic data processing. Although the model was developed for use in the satellite validation and archival programs, it also has proven useful in other studies of stratospheric aerosol.

Russell, P. B.↗
NASA NTRS1981

Stratospheric aerosols

The current state of information on stratospheric aerosols is reviewed. Aerosol properties such as size, size distribution, composition, refractive index, number density, extinction, optical depth, and single scattering albedo are considered and generalized as much as possible to be representative of the global aerosol in times of volcanic and nonvolcanic (background) periods. Data are presented that show the global distribution of stratospheric aerosols as measured by the stratospheric aerosol and gas experiment (SAGE) satellite system for background and volcanic (post-Mount St. Helens) conditions. In addition, lidar and dustsonde data are presented that show the changes in stratospheric aerosol over an 8-year period.

Mccormick, M. P.↗
NASA NTRS1981

Remote sensing applications to resource problems in South Dakota

The procedures used as well as the results obtained and conclusions derived are described for the following applications of remote sensing in South Dakota: (1) sage grouse management; (2) censusing Canada geese; (3) monitoring grasshopper infestation in rangeland; (4) detecting Dutch elm disease in an urban environment; (5) determining water usage from the Belle Fourche River; (6) resource management of the Lower James River; and (7) the National Model Implantation Program: Lake Herman watershed.

Myers, V. I.↗
NASA NTRS1982

Global distribution of stratospheric aerosols by satellite measurements

A description is given of the first-ever global stratospheric aerosol climatology which is being developed by the earth-orbiting SAM II and SAGE satellite-based sensors. These sensors use the technique of solar occulation; that is, for every spacecraft sunrise and sunset, the modulation of solar intensity caused by the intervening earth-limb is measured. These data are mathematically inverted to yield vertical profiles of aerosol extinction coefficients with 1 km resolution. The data show seasonal variations which are similar in each hemisphere, with strong correlation between aerosol extinction and the corresponding temperature field. Typical values of extinction in the stratosphere are found to be about 0.0001 to 0.0002 per km at 1 micrometer; stratospheric optical depths at this wavelength are about 0.002. The peak extinction in the stratospheric aerosol layer follows the tropopause with altitude, with peak extinction ratios about 10 km above the local tropopause.

Mccormick, M. P.↗
NASA NTRS1983

Clastic sedimentary rocks of the Michipicoten Volcanic-sedimentary belt, Wawa, Ontario

The Wawa area, part of the Michipicoten greenstone belt, contains rock assemblages representative of volcanic sedimentary accumulations elsewhere on the shield. Three mafic to felsic metavolcanic sequences and cogenetic granitic rocks range in age from 2749 + or - 2Ma to 2696 + or - 2Ma. Metasedimentary rocks occur between the metavolcanic sequences. The total thickness of the supracrustal rocks may be 10,000 m. Most rocks have been metamorphosed under greenschist conditions. The belt has been studied earlier and is currently being remapped by Sage. The sedimentrologic work has been briefly summarized; two mainfacies associations of clastic sedimentary rocks are present - a Resedimented (Turbidite) Facies Association and a Nonmarine (Alluvial Fan Fluvial) Facies Association.

Ojakangas, R. W.↗
NASA NTRS1984

Development of a global model for atmospheric backscatter at CO2 wavelengths

The effect of gravitational sedimentation on the atmospheric aerosol size distribution has been simulated using a one layer numerical model. A nonlinear curve fitting program is being developed to study aerosol size parameters. The Sage/Sam 2 data establishing the geographical and temporal variations of aerosol concentration in the troposphere are being studied. The basic version of the Sam 2 program and the alternative version of the Sage 2 program are operational. Above 6 km, latitudinal differences are more important in determining aerosol concentration than surface conditions.

Source record↗
NASA NTRS1984

Satellite stratospheric aerosol measurement validation

The validity of the stratospheric aerosol measurements made by the satellite sensors SAM II and SAGE was tested by comparing their results with each other and with results obtained by other techniques (lider, dustsonde, filter, and impactor). The latter type of comparison required the development of special techniques that convert the quantity measured by the correlative sensor (e.g. particle backscatter, number, or mass) to that measured by the satellite sensor (extinction) and quantitatively estimate the uncertainty in the conversion process. The results of both types of comparisons show agreement within the measurement and conversion uncertainties. Moreover, the satellite uncertainty is small compared to aerosol natural variability (caused by seasonal changes, volcanoes, sudden warmings, and vortex structure). It was concluded that the satellite measurements are valid.

Russell, P. B.↗