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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Monitoring vegetation using Nimbus-7 scanning mutichannel microwave radiometer's data

Field studies and radiative transfer model calculations have shown that brightness temperature at high microwave frequencies is strongly affected by vegetation. The daytime observations for six consecutive years (1979 to 1984) over the Sahara, Senegalese Sahel, Burkina Fasso (Upper Volta), and U.S. Southern Great Plains at 37 GHz frequency of the Sanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite are analyzed, and a high correlation with the normalized difference vegetation index derived from the Advanced Very High Resolution Radiometer on board the NOAA-7 satellite is found. The SMMR data appear to provide a valuable new long-term global data set for monitoring vegetation. In particular, the differing responses of vegetation (for example, annual grasses versus woody plants) to drought and the stability of the desert/steppe boundary of northern Africa might be studied using the time series data.

Choudhury, B. J.↗
NASA NTRS2008

Effective Interpolation of Incomplete Satellite-Derived Leaf-Area Index Time Series for the Continental United States

Many earth science modeling applications employ continuous input data fields derived from satellite data. Environmental factors, sensor limitations and algorithmic constraints lead to data products of inherently variable quality. This necessitates interpolation of one form or another in order to produce high quality input fields free of missing data. The present research tests several interpolation techniques as applied to satellite-derived leaf area index, an important quantity in many global climate and ecological models. The study evaluates and applies a variety of interpolation techniques for the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf-Area Index Product over the time period 2001-2006 for a region containing the conterminous United States. Results indicate that the accuracy of an individual interpolation technique depends upon the underlying land cover. Spatial interpolation provides better results in forested areas, while temporal interpolation performs more effectively over non-forest cover types. Combination of spatial and temporal approaches offers superior interpolative capabilities to any single method, and in fact, generation of continuous data fields requires a hybrid approach such as this.

Jasinski, Michael F.↗
NASA NTRS1982

Analysis of the profile characteristics of corn and soybeans using field reflectance data

The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to LANDSAT-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.

Crist, E. P.↗
NASA NTRS1986

Observations of field-aligned currents, waves, and electric fields at substorm onset

Substorm onsets, identified Pi 2 pulsations observed on the Air Force Geophysics Laboratory Magnetometer Network, are studied using magnetometer and electric field data from ISEE 1 as well as magnetometer data from the geosynchronous satellites GOES 2 and 3. The mid-latitude magnetometer data provides the means of both timing and locating the substorm onset so that the spacecraft locations with respect to the substorm current systems are known. During two intervals, each containing several onsets or intensifications, ISEE 1 observed field-aligned current signatures beginning simultaneously with the mid-latitude Pi 2 pulsation. Close to the earth broadband bursts of wave noise were observed in the electric field data whenever field-aligned currents were detected. One onset occurred when ISEE 1 and GOES 2 were on the same field line but in opposite hemispheres. During this onset ISEE 1 and GOES 2 saw magnetic signatures which appear to be due to conjugate field-aligned currents flowing out of the western end of the westward auroral electrojets. The ISEE 1 signature is of a line current moving westward past the spacecraft. During the other interval, ISEE 1 was in the near-tail region near the midnight meridian. Plasma data confirms that the plasma sheet thinned and subsequently expanded at onset. Electric field data shows that the plasma moved in the opposite direction to the plasma sheet boundary as the boundary expanded which implies that there must have been an abundant source of hot plasma present. The plasma motion was towards the center of the plasma sheet and earthwards and consisted of a series of pulses rather than a steady flow.

Smits, D. P.↗
DOE OSTI2021

Evaluation of Mode Meters Robust to Forced Oscillations using Field-Measured Data

Mode meters are tools used by power system operators to continuously monitor a system's small-signal stability. They do so by estimating the system's electromechanical modes of oscillation. When a system undergoes a forced oscillation, mode meters may become biased because the two types of oscillation cannot be distinguished. Modified mode meter algorithms robust to this bias have been proposed in prior research, but these studies were based primarily on simulated data. In this paper, modified least squares and Yule-Walker mode meter algorithms are evaluated using field-measured data from phasor measurement units (PMUs). Results show that the sensitivities of the least squares algorithm make it impractical for use given the complexities of real-world forced oscillations. However, the modified Yule-Walker algorithm is shown to perform well and has significant potential for practical deployment in mode meter tools.

Follum, James D.↗
NASA NTRS1999

GOCART Model Simulated Tropospheric Aerosols and Comparison with Satellite, Sun Photometer, and Field Measurement Data

We present the results of tropospheric sulfate, dust, carbonaceous, and sea salt aerosols simulated in the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. Because it is a global model and uses assimilated meteorological data produced by the Goddard Data Assimilation Office, the GOCART model is an ideal tool for global aerosol analysis combining the satellite and in-situ field measurement data. The aerosol optical depth for total aerosols are compared with that retrieved from TOMS and AVHRR remote sensing instruments and from ground-based sun photometer measurements. Individual aerosol concentrations are compared with field measurements at different geographical locations. The distributions of different aerosol types to total aerosol optical depth will be discussed.

Chin, Mian↗
NASA NTRS1981

Measurements of energy exchange between acoustic fields and non-uniform steady flow fields

Data were obtained for a resonance tube having a vent at the center in the lateral boundary, an average flow being introduced at the ends. Experiments were done for both circular and slot vents, over ranges of both frequency and Mach number. It was demonstrated that a subsonic exhaust vent in the lateral boundary of a cold flow resonance tube provides a gain of acoustic energy for the fundamental mode within the resonance tube. The gain of acoustic energy increases approximately linearly with the Mach number, as predicted by the one-dimensional analysis. The one-dimensional result gives the values for the slope representing the variation of the attenuation coefficient of the exhaust vent with respect to the average Mach number of the flow within roughly 30% of those measured. It has been verified that the subsonic vent produces a gain proportional to the average Mach number, proportional to the frequency, and independent of the shape. The results may be applicable to the study of vibration phenomena in solid propellant rocket engines.

Magiawala, K. R.↗
NASA NTRS1999

Interpretation of Lidar and Satellite Data Sets Using a Global Photochemical Model

A primary goal of the NASA Tropospheric Chemistry Program (TCP) is to "contribute substantially to scientific understanding of human impacts on the global troposphere". In order to analyze global or regional trends and factors of the troposphere chemistry, for example, its oxidation capacity or composition, a continuous global/regional data coverage as well as model simulations are needed. The Global Tropospheric Experiment (GTE), a major component of the TCP, provides data vital to these questions via aircraft measurement of key trace chemical species in various remote regions of the world. Another component in NASA's effort are satellite projects for exploration of tropospheric chemistry and dynamics. A unique data product is the Tropospheric Ozone Residual (TOR) utilizing global tropospheric ozone data. Another key research tool are simulation studies of atmospheric chemistry and dynamics for the theoretical understanding of the atmosphere, the extrapolation of observed trends, and for sensitivity studies assessing a changing anthropogenic impact to air chemistry and climate. In the context with model simulations, field data derived from satellites or (airborne) field missions are needed for two purposes: 1. To initialize and validate model simulations, and 2., to interpret field data by comparison to model simulation results in order to analyze global or regional trends and deviations from standard tropospheric chemistry and transport conditions as defined by the simulations. Currently, there is neither a sufficient global data coverage available nor are existing well established global circulation models. The NASA LARC CTM model is currently not yet in a state to accomplish a sufficient tropospheric chemistry simulation, so that the current research under this cooperative agreement focuses on utilizing field data products for direct interpretation. They will be also available for model testing and a later interpretation with a finally utilized model.

Zenker, Thomas↗
NASA NTRS1977

The effect of forward speed on J85 engine noise from suppressor nozzles as measured in the NASA-Ames 40- by 80-foot wind tunnel

An investigation to determine the effect of forward speed on the exhaust noise from a conical ejector nozzle and three suppressor nozzles mounted behind a J85 engine was performed in a 40- by 80-foot wind tunnel. The nozzles were tested at three engine power settings and at wind tunnel forward speeds up to 91 m/sec (300 ft/sec). In addition, outdoor static tests were conducted to determine (1) the differences between near field and far field measurements, (2) the effect of an airframe on the far field directivity of each nozzle, and (3) the relative suppression of each nozzle with respect to the baseline conical ejector nozzle. It was found that corrections to near field data are necessary to extrapolate to far field data and that the presence of the airframe changed the far field directivity as measured statically. The results show that the effect of forward speed was to reduce the noise from each nozzle more in the area of peak noise, but the change in forward quadrant noise was small or negligible. A comparison of wind tunnel data with available flight test data shows good agreement.

Atencio, A., Jr.↗
DOE OSTI2022

Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning

Cover cropping between cash crop growing seasons is a multifunctional conservation practice. Timely and accurate monitoring of cover crop traits, notably aboveground biomass and nutrient content, is beneficial to agricultural stakeholders to improve management and understand outcomes. Currently, there is a scarcity of spatially and temporally resolved information for assessing cover crop growth. Remote sensing has a high potential to fill this need, but conventional empirical regression operated with coarse-resolution multispectral data has large uncertainties. Therefore, this study utilized airborne hyperspectral imaging techniques and developed new process-guided machine learning approaches (PGML) for cover crop monitoring. Specifically, we deployed an airborne hyperspectral system covering visible to shortwave-infrared wavelengths (400–2400 nm) to acquire high spatial (0.5 m) and spectral (3–5 nm) resolution reflectance over 23 cover crop fields across Central Illinois in March and April of 2021. Airborne hyperspectral surface reflectance with high spectral and spatial resolution can be well matched with field data to quantify cover crop traits. Furthermore, the PGML models were pre-trained by synthetic data from soil-vegetation radiative transfer modeling (one million records), and then fine-tuned with field data of cover crop biomass and nutrient content. Results show that airborne hyperspectral data with PGML can achieve high accuracy to predict cover crop aboveground biomass (R 2 = 0.72, relative RMSE = 15.16%) and nitrogen content (R 2 = 0.69, relative RMSE = 16.59%) through leave-one-field-out cross-validation. Unlike the pure data-driven approach (e.g., partial least-squares regression), PGML incorporated radiative transfer knowledge and obtained higher predictive performance with fewer field data. Meanwhile, with field data for model fine-tuning, PGML predicted biomass more accurately than the inversion of radiative transfer models. Here we also found that the red edge has a high contribution in quantifying aboveground biomass and nitrogen content, followed by green and shortwave spectra. This study demonstrated the first attempt of utilizing hyperspectral remote sensing to accurately quantify cover crop traits. We highlight the strength of PGML in exploiting sensing data to quantify ecosystem variables to advance agroecosystem monitoring for sustainable agricultural management.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Commercial Building Energy Code Field Study: Data Collection Methodology and Protocol

In support of the U.S. Department of Energy’s Commercial Buildings Energy Code Field Study, this data collection methodology and protocol provides guidance on all aspects of undertaking a compliance study, from development of a sampling plan to recruitment to code requirements and compliance checks for each energy code measure specified to be collected. The protocol also includes a data collection form that captures all key information needed for analysis of commercial energy code compliance. This methodology was developed by the Institute for Market Transformation in coordination with Pacific Northwest National Laboratory (PNNL) and the U.S. Department of Energy Building Energy Codes Program with the objective of assisting states, jurisdictions, utilities and others as they seek to measure and demonstrate compliance rates with energy codes in commercial buildings, as well as to target areas for improvement through increased energy code compliance and broader energy-efficiency programs. It is also intended to facilitate a consistent and replicable approach to research studies of this type and establish a transparent data set representing baseline construction practices across the U.S.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Commercial Building Energy Code Field Study: Data Collection Methodology and Protocol

In support of the U.S. Department of Energy’s Commercial Buildings Energy Code Field Study, this data collection methodology and protocol provides guidance on all aspects of undertaking a compliance study, from development of a sampling plan to recruitment to code requirements and compliance checks for each energy code measure specified to be collected. The protocol also includes a data collection form that captures all key information needed for analysis of commercial energy code compliance. This methodology was developed by the Institute for Market Transformation in coordination with Pacific Northwest National Laboratory (PNNL) and the U.S. Department of Energy Building Energy Codes Program with the objective of assisting states, jurisdictions, utilities and others as they seek to measure and demonstrate compliance rates with energy codes in commercial buildings, as well as to target areas for improvement through increased energy code compliance and broader energy-efficiency programs. It is also intended to facilitate a consistent and replicable approach to research studies of this type and establish a transparent data set representing baseline construction practices across the U.S.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1996

Electromagnetic Scattered Field Evaluation and Data Compression Using Imaging Techniques

This is the final report on Project #727625 between The Ohio State University and NASA, Lewis Research Center, Cleveland, Ohio. Under this project, a data compression technique for scattered field data of electrically large targets is developed. The technique was applied to the scattered fields of two targets of interest. The backscattered fields of the scale models of these targets were measured in a ra compact range. For one of the targets, the backscattered fields were also calculated using XPATCH computer code. Using the technique all scattered field data sets were compressed successfully. A compression ratio of the order 40 was achieved. In this report, the technique is described briefly and some sample results are included.

Gupta, I. J.↗
DOE OSTI2024

Model-ready benchmarks for NPP, ANPP, litter fluxes, and recruitment into the 1 cm dbh size class

The intended use of this dataset is to serve as an observational benchmark to evaluate model predictions of NPP, ANPP, litter fluxes, and recruitment at Barro Colorado Island, Panama. This dataset contains four CSV files and one text file. “Benchmarks-NPP-ANPP-R-L.csv” provides estimates of annual ecosystem-level reproductive litter flux (R), leaf litter flux (L), aboveground net primary productivity (ANPP), and net primary productivity (NPP) for 61 field plots throughout tropical, temperate, and boreal forest biomes. An additional 499 plots (n = 550) include estimates of just R, L, and R/L. Each row reports a distinct set of estimates for one sampling interval at one plot. “Metadata-Benchmarks-NPP-ANPP-R-L.csv” contains field descriptions for all data fields in “Benchmarks-NPP-ANPP-R-L.csv”. “References-Benchmarks-NPP-ANPP-R-L.txt” contains full references to the original studies used to produce the observations at each plot included in the data. “Benchmarks-Recruitment.csv” provides estimates of species-level recruitment rates into the 1 cm dbh size class at four CTFS-ForestGeo sites using methods that account for unobserved mortality of new recruits between census intervals (Kohyama et al., 2018). “Metadata-Benchmarks-Recruitment.csv” contains field descriptions for all data fields in “Benchmarks-Recruitment.csv”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying

This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms, last access: 11 November 2025), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical simulation (DNS) and some LES datasets of canonical turbulent flows, JHTDB-wind stores the 4D space–time history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 10×6 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. These data comprise 1 h (hour) of flow field data (velocity, pressure, potential temperature deviation, subgrid-scale (SGS) eddy viscosity, and turbine forces, approximately 15 TB (terabytes) and wind turbine data – including both turbine-level operational quantities and blade-level aerodynamic quantities (approximately 1.3 TB) – stored in Zarr and Parquet formats, respectively. Data retrieval is facilitated by the giverny Python package, allowing remote users to query the database in Python or MATLAB (C and Fortran support are available for flow field data). This paper details the simulation setup and demonstrates data access through examples that analyze wind farm flow structures and turbine performance. The framework is extensible to future datasets, including the JHTDB-wind diurnal cycle simulation analyzed in Xiao et al. (2025).

17 WIND ENERGY↗
DOE OSTI2024

Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018

Airborne measurements are pivotal for providing detailed, spatiotemporally resolved information about atmospheric parameters and aerosol and cloud properties, thereby enhancing our understanding of dynamic atmospheric processes. For 30 years, the US Department of Energy (DOE) Office of Science supported an instrumented Gulfstream 1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) Data Center and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated dataset was recently developed covering the final 6 years of G-1 operations (2013 to 2018, https://doi.org/10.5439/1999133; Mei and Gaustad, 2024). The integrated dataset includes data collected from 236 flights (766.4 h), which covered the Arctic, the US Southern Great Plains (SGP), the US West Coast, the eastern North Atlantic (ENA), the Amazon Basin in Brazil, and the Sierras de Córdoba range in Argentina. These comprehensive data streams provide much-needed insight into spatiotemporal variability in the thermodynamic quantities and aerosol and cloud properties for addressing essential science questions in Earth system process studies. This paper describes the DOE ARM merged G-1 datasets, including information on the acquisition, data collection challenges and future potentials, and quality control processes. It further illustrates the usage of this merged dataset to evaluate the Energy Exascale Earth System Model (E3SM) with the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Incorporating long-range dependence and fractal features in turbulence spectra

We introduce an advanced turbulence spectrum model developed from mathematical foundations from a covariance function class and empirically validated using extensive field data. This model captures the complex dynamics of long-range dependence, and fractal characteristics prevalent in riverine and atmospheric boundary layer (ABL) flows that are ignored by classical spectrum models, such as IEC (International Electrotechnical Commission) von Kármán and Kaimal model. The model delineates scaling behaviors across distinct frequency bands and offers substantial flexibility through five well-defined parameters each characterizing a distinct physical aspect of the velocity time series. A detailed procedure for obtaining each parameter from time series data is outlined. The comprehensive validations with field data from tidal currents and ABL flows substantiate the model’s fidelity in accurately replicating observed phenomena. This validation establishes the reliability of the proposed model and, when incorporated into stochastic full-field simulators such as TurbSim, demonstrates its potential to advance the predictive modeling and analysis of turbulent flows in environmental science and engineering contexts.

Cheng, Shyuan [Univ. of Illinois at Urbana-Champai↗