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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Data and scripts associated with a manuscript investigating impacts of solid phase extraction on freshwater organic matter optical signatures and mass spectrometry pairing

This data package is associated with the publication “Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high-resolution mass spectrometry data in a freshwater system” submitted to “Limnology and Oceanography: Methods.” This data is an extension of the River Corridor and Watershed Biogeochemistry SFA’s Spatial Study 2021 (https://doi.org/10.15485/1898914). Other associated data and field metadata can be found at the link provided. The goal of this manuscript is to assess the impact of solid phase extraction (SPE) on the ability to pair ultra-high resolution mass spectrometry data collected from SPE extracts with optical properties collected on ambient stream samples. Forty-seven samples collected from within the Yakima River Basin, Washington were analyzed dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), absorbance, and fluorescence. Samples were subsequently concentrated with SPE and reanalyzed for each measurement. The extraction efficiency for the DOC and common optical indices were calculated. In addition, SPE samples were subject to ultra-high resolution mass spectrometry and compared with the ambient and SPE generated optical data. Finally, in addition to this cross-platform inter-comparison, we further performed and intra-comparison among the high-resolution mass spectrometry data to determine the impact of sample preparation on the interpretability of results. Here, the SPE samples were prepared at 40 milligrams per liter (mg/L) based on the known DOC extraction efficiency of the samples (ranging from ~30 to ~75%) compared to the common practice of assuming the DOC extraction efficiency of freshwater samples at 60%. This data package folder consists of one main data folder with one subfolder (Data_Input). The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) final data summary output from processing script; and (5) the processing script. The R-markdown processing script (SPE_Manuscript_Rmarkdown_Data_Package.rmd) contains all code needed to reproduce manuscript statistics and figures (with the exception of that stated below). The Data_Input folder has two subfolders: (1) FTICR and (2) Optics. Additionally, the Data_Input folder contains dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (SPS_NPOC_Summary.csv) and relevant supporting Solid Phase Extraction Volume information (SPS_SPE_Volumes.csv). Methods information for the optical and FTICR data is embedded in the header rows of SPS_EEMs_Methods.csv and SPS_FTICR_Methods.csv, respectively. In addition, the data dictionary (SPS_SPE_dd.csv), file level metadata (SPS_SPE_flmd.csv), and methods codes (SPS_SPE_Methods_codes.csv) are provided. The FTICR subfolder contains all raw FTICR data as well as instructions for processing. In addition, post processed FTICR molecular information (Processed_FTICRMS_Mol.csv) and sample data (Processed_FTICRMS_Data.csv) is provided that can be directly read into R with the associated R-markdown file. The Optics subfolder contains all Absorbance and Fluorescence Spectra. Fluorescence spectra have been blank corrected, inner filter corrected, and undergone scatter removal. In addition, this folder contains Matlab code used to make a portion of Figure 1 within the manuscript, derive various spectral parameters used within the manuscript, and used for parallel factor analysis (PARAFAC) modeling. Spectral indices (SPS_SpectralIndices.csv) and PARAFAC outputs (SPS_PARAFAC_Model_Loadings.csv and SPS_PARAFAC_Sample_Scores.csv) are directly read into the associated R-markdown file. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Airborne LiDAR to Improve Canopy Fuels Mapping for Wildfire Modeling

Increasing conflict between wildfire and the built environment has increased the need for more up-to-date and finer resolution canopy fuels data to improve wildfire modeling and associated risk forecasts. The US Forest Service and US Department of the Interior’s LANDFIRE product, which provides 30-m resolution canopy fuels data for the entire US, is one of the most widely used sources of fuels data. However, the last complete mapping effort for LANDFIRE is based on 2016 conditions, and subsequent updates reflect disturbances 1-2 years behind the release year. Airborne systems equipped with Light Detection and Ranging (LiDAR) sensors can be deployed to actively sense canopy structure and estimate canopy fuels data (cover, height, base height, bulk density) at finer resolutions. Canopy base height (CBH) and canopy bulk density (CBD) are difficult to measure both in the field and in LiDAR point clouds. Still, they are important for accurately modeling crown fires, which are often intense and difficult to contain. Additionally, point cloud datasets are large, and calculations require efficient utilization of computational resources. To address these challenges, we are working on an approach that uses openly available National Ecological Observatory Network (NEON) airborne LiDAR data, with calculations processed in the R programming language and parallelized through the lidR package. CBH and CBD are often derived from tree height, diameter at breast height, and species-specific allometries using the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS). We aim to test if airborne LiDAR can estimate CBH and CBD without the use of empirical equations. Reliable estimates of canopy fuels data directly from airborne LiDAR could streamline quick, fine-resolution updates for use in wildfire behavior models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Assessment of the urban heat island effect through the use of satellite data

A recent NASA satellite is obtaining high spatial resolution thermal infrared data at times of day appropriate for the study of the urban heat island effect. Quantitative estimates of the extent and intensity of urban surface heating are obtained by analysis of digital data acquired over the New York City-New England area. In many large cities satellite sensed temperatures are 10-15 C warmer than in surrounding rural areas. A thorough interpretation of the elevated urban surface temperature will require studies of (1) the relationship between remotely sensed surface temperatures and air temperatures, and (2) compensation for observed very localized heating due to industry and/or power plants.

Price, J. C.↗
DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data: Preprint

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data input to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Identification of Climatological Representative Days in the Mid-Atlantic for High-Fidelity Offshore Wind Energy Modeling

The goal of reaching 30 GW of offshore wind energy by 2030 becomes more realistic with the continued approval of offshore wind energy areas by the Biden Administration. In the Mid-Atlantic, where wind energy projects are in the most advanced stages of development, there is increased research focus on the eventual interaction of these wind farms. These interactions, in the form of wakes and cluster wakes, or wakes from multiple wind farms, could have detrimental effects on power production and forecastability for downwind wind farms (Pryor et al. 2022, Golbazi et al. 2022, Rosencrans et al. 2023). To help alleviate these issues, numerical simulations in the form of numerical weather prediction (NWP) and large eddy simulations (LES) can provide insight into when cluster wake situations may occur, but running such simulations can be expensive and difficult to run for multiple years. In this study, we leverage and build upon existing techniques in the literature (Fischereit et al. 2022) to identify climatologically representative days for wind energy areas in the Mid-Atlantic where conditions would promote cluster wake situations. We select meteorological variables (wind speed, wind direction, atmospheric stability, boundary-layer height, TKE) critical to understanding wind energy production and wake propagation. We then consider two different NWP datasets of varying spatial and temporal resolution: ERA5 provides data at hourly intervals from 1940 to present at 0.25 deg (31 km) spatial resolution (Hersbach et al. 2020), and the NOW-23 dataset provides data at 5-minute resolution for 21 years at 2-km spatial resolution (Bodini et al. 2020). Our first step is to compare these two datasets for an overlapping 21-year time period. Initial results show that the required number of days to represent the long-term climate increases with each additional variable considered. In their study of the German Bight, Fischereit et al. (2022) found that they could represent the long-term wind and wave climate in a "near-perfect" way with -180 days, by reaching a Perkins Skill Score (PSS) of 0.9; our investigation of the mid-Atlantic wind resource region with ERA5 and NOW-23 data suggests that we will need -100 days to reach a PSS of 0.9. As we expand our parameter space to include multiple variables, the number of required days will likely grow. These results will ultimately be used to select case studies to best represent cluster wake conditions that apply to this region for the lifetime of likely wind farms in this mid-Atlantic region.

clusterwakes↗
NASA NTRS1985

Performance evaluation of a simulated data-flow computer with low-resolution actors

Basic problems related to the exploitation of parallelism in a program include sequencing of the instructions and communication of the data. It is pointed out that the data-flow approach offers an elegant solution to the sequencing problem, since all data dependencies are automatically handled and only instructions with ready input sets are activated. It is shown that a change in the level of subcomputations (actors) affects communications costs. The concept of variable resolution is discussed, and the testbed environment is examined. Attention is given to the architecture of the processing elements, the communication network, and the simulators. A description of the analytical model is also provided. Simulation and results are discussed, taking into account test programs and allocation, the variation of the number of processing elements, the variation of the resolution in directed acyclic graphs, performance in processing loops, and array handling.

Gaudiot, J. L.↗
NASA NTRS1983

High spectral resolution lidar to measure optical scattering properties of atmospheric aerosols. II - Calibration and data analysis

The high spectral resolution lidar (HSRL) measures optical properties of atmospheric aerosols by interferometically separating the elastic aerosol backscatter from the Doppler broadened molecular contribution. Calibration and data analysis procedures developed for the HSRL are described. Data obtained during flight evaluation testing of the HSRL system are presented with estimates of uncertainties due to instrument calibration. HSRL measurements of the aerosol scattering cross section are compared with in situ integrating nephelometer measurements.

Sroga, J. T.↗
NASA NTRS1988

MODIS-HIRIS ground data systems commonality report

The High Resolution Imaging Spectrometer (HIRIS) and Moderate Resolution Imaging Spectrometer (MODIS) Data Systems Working Group was formed in September 1988 with representatives of the MODIS Data System Study Group and the HIRIS Project Data System Design Group to collaborate in the development of requirements on the EosDIS necessary to meet the science objectives of the two facility instruments. A major objective was to identify and promote commonality between the HIRIS and MODIS data systems, especially from the science users' point of view. A goal was to provide a base set of joint requirements and specifications which could easily be expanded to a Phase-B representation of the needs of the science users of all EOS instruments. This document describes the points of commonality and difference between the Level-II Requirements, Operations Concepts, and Systems Specifications for the ground data systems for the MODIS and HIRIS instruments at their present state of development.

Han, D.↗
NASA NTRS1991

Mapping compositional and particle size variations across Silver Lake Playa: Relevance to analyses of Mars TIR data

The high spectral and spatial resolution thermal infrared (TIR) data to be acquired from the upcoming Mars Observer-Thermal Emission Spectra (TES) mission will map the composition and texture of the Martian sediments. To prepare for these data, portions of two remote sensing experiments were conducted to test procedures for extracting surface property information from TIR data. Reported here is the continuing analysis of Thermal Infrared Multispectral Scanner (TIMS) data, field emission spectra, laboratory Fourier Transform Infrared (FTIR) reflectance spectra, and field observations with respect to the physical characteristics (composition, emissivity, etc.) of Silver Lake playa in southern California.

Petroy, S. B.↗
DOE OSTI2018

DWT-Based Aggregated Load Modeling and Evaluation for Quasi-Static Time-Series Simulation on Distribution Feeders

This paper presents an extension of a previously reported discrete wavelet transform (DWT) based load modeling methodology which targets at modeling time-series load profiles to enable the more effective and realistic quasi-static time-series simulation of distribution feeders. The time-series load model is composed of two major parts: 1) The low-resolution field-measured load data which usually have a resolution of 30 or 15 min., 2) The high-resolution load variability model data extracted from the established variability database which can have resolution up to 1 sec. A load aggregation methodology is developed to aggregate the load profiles so that load profiles at different transformer ratings can be effectively modeled. Validation, evaluation, and analysis of the developed load modeling approach has been performed on the IEEE-123 feeder and an actual utility feeder from California. The analysis completed on the two feeders have demonstrated the effectiveness and revealed the value of the developed model for distribution feeder quasi-static time-series simulation at high temporal resolution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

DWT-Based Aggregated Load Modeling and Evaluation for Quasi-Static Time-Series Simulation on Distribution Feeders: Preprint

This paper presents an extension of a previously reported discrete wavelet transform (DWT) based load modeling methodology which targets at modeling time-series load profiles to enable the more effective and realistic quasi-static time-series simulation of distribution feeders. The time-series load model is composed of two major parts: 1) The low-resolution field-measured load data which usually have a resolution of 30 or 15 min., 2) The high-resolution load variability model data extracted from the established variability database which can have resolution up to 1 sec. A load aggregation methodology is developed to aggregate the load profiles so that load profiles at different transformer ratings can be effectively modeled. Validation, evaluation, and analysis of the developed load modeling approach has been performed on the IEEE-123 feeder and an actual utility feeder from California. The analysis completed on the two feeders have demonstrated the effectiveness and revealed the value of the developed model for distribution feeder quasi-static time-series simulation at high temporal resolution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Intensified Tpx3Cam, a fast data-driven optical camera with nanosecond timing resolution for single photon detection in quantum applications

Here we describe a fast data-driven optical camera, Tpx3Cam, with nanosecond scale timing resolution and 80 Mpixel/sec throughput. After the addition of intensifier, the camera is single photon sensitive with quantum efficiency determined primarily by the intensifier photocathode. The single photon performance of the camera was characterized with results on the gain, timing resolution and afterpulsing reported here. The intensified camera was successfully used for measurements in a variety of applications including quantum applications. As an example of such application, which requires simultaneous detection of multiple photons, we describe registration of photon pairs from the spontaneous parametric down-conversion source in a spectrometer. We measured the photon wavelength and timing with respective precisions of 0.15 nm and 3 ns, and also demonstrated that the two photons are anti-correlated in energy.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

High resolution Viking Orbiter images: A useful data source for testing the viability of geomorphic processes attributed to Martian landforms

The diversity of landforms visible in the Viking images of Mars have led to a proliforation of geomorphic agents proposed to be active in shaping the Martian surface. While it is likely that numerous different processes have contributed to the geomorphology of Mars throughout Martian history, it is important that proposed Martian geomorphic agents be subjected to critical scrutiny by the scientific community. High resolution Viking Orbiter images represent a data set for investigating geomorphic processes on Mars. Geologic mapping of Mars can take place at a variety of scales, utilizing a variety of image resolutions, but an interpretation of the history of individual landforms is dependent upon the best available spatial resolution. These high resolution images provide the opportunity to examine proposed Martian geomorphic processes. It is clear that researchers may not interpret features in the same way but it is important that high resolution images of candidate features be made available to the scientific community so that a consensus can be reached. This procedure can provide a way to refine the understanding of geomorphic processes on Mars.

Zimbelman, James R.↗
DOE OSTI2026

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1983

Monitoring global vegetation using NOAA-7 AVHRR data

The NOAA-7 polar orbiting, sun-synchronous, operational satellite carries the 5 channel Advanced Very High Resolution Radiometer (AVHRR). Data are acquired globally at a resolution of 4 km on a daily basis. This data provides the means of frequently monitoring global vegetation on continental scales. Techniques for compositing and cloud screening a vegetation index for Africa are presented. The sample data set covers 9 days beginning August 16, 1983 and is compared with a semi-operational vegetation index product produced by NOAA.

Gatlin, J. A.↗
NASA NTRS1989

Comparison of data from the Scanning Multifrequency Microwave Radiometer (SMMR) with data from the Advanced Very High Resolution Radiometer (AVHRR) for terrestrial environmental monitoring - An overview

Comparison between the microwave polarized difference temperature (MPDT) derived from 37 GHz band data and the normalized difference vegetation index (NDVI) derived from near-infrared and red bands, from several empirical investigations are summarized. These indicate the complementary character of the two measures in environmental monitoring. Overall the NDVI is more sensitive to green leaf activity, whereas the MPDT appears also to be related to other elements of the above-ground biomass. Monitoring of hydrological phenomena is carried out much more effectively by the MPDT. Further work is needed to explain spectral and temporal variation in MPDT both through modelling and field experiments.

Townshend, J. R. G.↗