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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dark Energy Survey Year 3 Results: Deep Field optical + near-infrared images and catalogue

ABSTRACT We describe the Dark Energy Survey (DES) Deep Fields, a set of images and associated multiwavelength catalogue (ugrizJHKs) built from Dark Energy Camera (DECam) and Visible and Infrared Survey Telescope for Astronomy (VISTA) data. The DES Deep Fields comprise 11 fields (10 DES supernova fields plus COSMOS), with a total area of ∼30 sq. deg. in ugriz bands and reaching a maximum i-band depth of 26.75 (AB, 10σ, 2 arcsec). We present a catalogue for the DES 3-yr cosmology analysis of those four fields with full 8-band coverage, totalling 5.88 sq. deg. after masking. Numbering 2.8 million objects (1.6 million post-masking), our catalogue is drawn from images coadded to consistent depths of r = 25.7, i = 25, and z = 24.3 mag. We use a new model-fitting code, built upon established methods, to deblend sources and ensure consistent colours across the u-band to Ks-band wavelength range. We further detail the tight control we maintain over the point-spread function modelling required for the model fitting, astrometry and consistency of photometry between the four fields. The catalogue allows us to perform a careful star–galaxy separation and produces excellent photometric redshift performance (NMAD = 0.023 at i < 23). The Deep-Fields catalogue will be made available as part of the cosmology data products release, following the completion of the DES 3-yr weak lensing and galaxy clustering cosmology work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The Davis–Chandrasekhar–Fermi method revisited

ABSTRACT Despite the rich observational results on interstellar magnetic fields in star-forming regions, it is still unclear how dynamically significant the magnetic fields are at varying physical scales, because direct measurement of the field strength is observationally difficult. The Davis–Chandrasekhar–Fermi (DCF) method has been the most commonly used method to estimate the magnetic field strength from polarization data. It is based on the assumption that gas turbulent motion is the driving source of field distortion via linear Alfvén waves. In this work, using MHD simulations of star-forming clouds, we test the validity of the assumption underlying the DCF method by examining its accuracy in the real 3D space. Our results suggest that the DCF relation between turbulent kinetic energy and magnetic energy fluctuation should be treated as a statistical result instead of a local property. We then develop and investigate several modifications to the original DCF method using synthetic observations, and propose new recipes to improve the accuracy of DCF-derived magnetic field strength. We further note that the biggest uncertainty in the DCF analysis may come from the linewidth measurement instead of the polarization observation, especially since the line-of-sight gas velocity can be used to estimate the gas volume density, another critical parameter in the DCF method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Data and code for: Combining eddy covariance towers, field measurements, and the MEMS 2 ecosystem model improves confidence in the climate impacts of bioenergy with carbon capture and storage

BECCS demands extensive land use change that may create positive or negative radiative forcing impacts upstream of the BECCS facility through changes to in situ greenhouse gas fluxes and land surface albedo. When quantifying these upstream climate impacts, even at a single site, different methods can give different estimates. Here we show how three common methods for estimating the net ecosystem carbon balance of bioenergy crops established on former grassland or former cropland can differ in their central estimates and uncertainty.

BECCS↗
DOE OSTI2023

Model America

Data set including 17 fields of information for 141,506,665 U.S. buildings. Advantages of this dataset include: Resolution - actionable data and models for individual U.S. buildings; Flexibility - ability to modify data, models, and analysis for any simulation-informed use case; Scalability - dynamic archetypes can be used as representative models for any geography of interest; Accuracy - error rates for total energy use at city-scale of 1-5%

New, JoshuaR↗
DOE OSTI2023

FTR for: Reducing plug-load electricity footprint of residential buildings through low-cost, non-intrusive sub-metering and personalized feedback technology

The project started in October 2016 and ended in December 2022. The project's principal goals and achievements were: (i) Measure real and reactive electric power consumption in ~400 apartments in multifamily settings of varying size and vintage and publish the data; data was published according to New York State's recommended 15x15 rule continuously from Jan 2019 through December 2022 (10 second time resolution); with the combination of large number of apartments, real and reactive power, as well as high time resolution (10-seconds), the dataset is first of its kind worldwide; because the dataset New York City apartment consumption pre, during, and post pandemic, it further offers unique insights into changes in residential electricity consumption during lockdowns and after modified work from home schedules. (ii) Measure effectiveness of different feedback types to prompt residents to lower their electricity consumption; achieved 11% (kWh-weighted) reduction versus baseline consumption; confirmed previous studies that social comparisons elicit above average responses; showed, for the first time, that the so called boomerang effect in power consumption feedback projects can be explained by a previously hypothesized norm-conforming "magnet effect" (rather than a non-conforming defiance effect), thus substantially advancing the research in the field. (iii) Disaggregate apartment-level consumption to appliance level; because the hardware for electricity consumption unexpectedly allowed only for 10-second time resolution (rather than the 1-second resolution we had planned on), the disaggregation algorithms we developed on sample data could not be applied to the actual field data we collected. The project has yielded high visibility, with a total of 17 publications, from peer reviewed journals, published data sets (free access), blog posts, NY Times, National Public Radio, and CNN.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Procedure for locating oil and gas wells in the Appalachian Basin

Locating undocumented (or poorly documented) oil and gas wells for environmental assessment is often difficult. Remnant features that confirm the presence of a well (intact casing/wellhead, well bore, etc.) are typically less than a meter in size and often are obscured from direct observation on the ground or from the air (by dense vegetation, for example). To efficiently find such features, it is useful to first systematically compile publicly available digital data at progressively smaller scales prior to embarking on field campaigns. Further, the information presented here describes the procedure developed and used by the U.S. Department of Energy's National Energy Technology Laboratory to locate potential oil and gas well sites for follow-up field verification and characterization. Digital data are first compiled from national and state resources such as well location/production databases, historical topographic maps, historical aerial photographs, and LiDAR data. Although each data set is likely to be incomplete or inaccurate to some extent, combining the data resources using geographic information system technology can generate potential well site targets with a higher degree of confidence, which improves the efficiency of fieldwork activities. This workflow was developed in the Appalachian Basin region, and although certain aspects may be unique, the general process would be applicable to locating undocumented wells in other regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Perch 3D

Processed SEGY files from the Perch 3D seismic area in the Michigan Basin. Data was used to make estimates of the stress field in the study area. Data was processed from Texseis, Inc.

3D↗
DOE OSTI2022

Transient Data Library of Solar Grid Integrated Distributed System

This submission contains an open-source library of transient events in distributed system with high solar PV. The library includes the collected data, related documents and scripts for loading the data. The data library is built for transient event detection and machine learning based analysis algorithm development. The data was collected via both field test and software simulation. The units for the data are included in the data file headers for each data series. A text editor or spreadsheet software, such as Excel, and Matlab is required to view the data.

algorithms↗
DOE OSTI2020

Urban-scale Energy Modeling: Scaling Beyond Tax Assessor Data

In an attempt to attain building-specific characteristics for urban-scale building energy models, county-specific tax assessors’ data is often an initial data source. This data source can contain valuable information such as year built, area, height, HVAC type, and roof/wall descriptions.We will show examples of 2,000 fields from Hamilton County in Tennessee with examples of many fields which are not relevant to urban-scale building energy modeling, are incorrect compared to other data sources, and highlight some lessons learned working with such a data source.There are currently 3,142 counties in the United States, each with their own data format, field definitions, and data access policy. As urban-scale involves city-scale analysis potentially covering multiple counties and matures toward state- or nation-scale analysis, county-by-county approaches are not scalable. While there are efforts to unify these datasets, there is an increasing proliferation of data and algorithms that can cover wider areas and provide more accurate inputs for urban-scale models. This paper summarizes computer vision of imagery, cartographic layers, building type assessment, and model generation used to achieve scalable detection and analysis of buildings.

New, Joshua↗
DOE OSTI2022

A data science approach for analysis and reconstruction of spinodal-like composition fields in irradiated FeCrAl alloys

A statistical method for the analysis of continuously distributed data representative of composition fluctuations in irradiated FeCrAl alloys acquired using Energy Dispersive X-ray Spectroscopy (EDS) method is presented. Using probability distribution functions, direct and cross-covariances between the elemental compositions, the effects of alloy composition and irradiation dose were investigated on the spatial distribution and length scale of composition fluctuations at the nanoscale. We have observed that, for neutron-irradiated FeCrAl alloys, the distribution of Fe and Cr followed a left-skewed and right-skewed distribution, respectively for all (average) alloy compositions and irradiation doses. The analysis also revealed enhanced spatial gradients in the elemental compositions at higher irradiation dose. Direct and cross-covariance estimates of the experimental data were also utilized for reconstruction of composition data through fitting it to a parametric form of the covariance functions. Linear Model of Coregionalization was used to determine the parameters of the covariance functions. Subsequently, a spectral method was utilized for simulating a realization of the alloy compositions. Close correspondence was observed between the experimental and the reconstructed data which was analyzed using probability distribution functions and covariance functions. Composition space of the experimental and reconstructed data and dislocation velocities as a function of applied stress and line directions over the entire composition maps were also examined.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A labeled dataset for building HVAC systems operating in faulted and fault-free states

Abstract Open data is fueling innovation across many fields. In the domain of building science, datasets that can be used to inform the development of operational applications - for example new control algorithms and performance analysis methods - are extremely difficult to come by. This article summarizes the development and content of the largest known public dataset of building system operations in faulted and fault free states. It covers the most common HVAC systems and configurations in commercial buildings, across a range of climates, fault types, and fault severities. The time series points that are contained in the dataset include measurements that are commonly encountered in existing buildings as well as some that are less typical. Simulation tools, experimental test facilities, and in-situ field operation were used to generate the data. To inform more data-hungry algorithms, most of the simulated data cover a year of operation for each fault-severity combination. The data set is a significant expansion of that first published by the lead authors in 2020.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

OSCAR-Mike: Why not ATAK?

The Office of Nuclear Smuggling Detection and Deterrence (NSDD) is evaluating methods to increase the probability that international partners will detect radioactive materials. One proposed method to accomplish this goal is to improve communications within teams operating in challenging environments. The goal of these improvements would be to enable remote monitoring of detection equipment, share data among end users in the field and subject matter experts, and integrate data from radiation detectors with other types of sensors and camera systems. Accomplishing this goal has the potential to improve the capabilities of currently deployed NSDD equipment. During FY 2021, Oak Ridge National Laboratory demonstrated some core and expanded capabilities of the Android Team Awareness Kit (ATAK), a situational awareness application developed by the US Department of Defense, to enable precision targeting, navigation, and data sharing. During FY 2022, Oak Ridge National Laboratory developed software requirements for an NSDD team awareness kit–based system. The requirements were developed by liaising with NSDD management and subject matter experts to determine NSDD’s needs and by reviewing available software and hardware solutions with US Department of Defense team awareness kit program managers and developers and radiation detection equipment vendors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A materials data framework and dataset for elastomeric foam impact mitigating materials

The availability of materials data for impact-mitigating materials has lagged behind applications-based data. For example, data describing on-field helmeted impacts are available, whereas material behaviors for the constituent impact-mitigating materials used in helmet designs lack open datasets. Here, we describe a new FAIR (findable, accessible, interoperable, reusable) data framework with structural and mechanical response data for one example elastic impact protection foam. The continuum-scale behavior of foams emerges from the interplay of polymer properties, internal gas, and geometric structure. This behavior is rate and temperature sensitive, therefore, describing structure-property characteristics requires data collected across several types of instruments. Data included are from structure imaging via micro-computed tomography, finite deformation mechanical measurements from universal test systems with full-field displacement and strain, and visco-thermo-elastic properties from dynamic mechanical analysis. These data facilitate modeling and design efforts in foam mechanics, e.g., homogenization, direct numerical simulation, or phenomenological fitting. The data framework is implemented using data services and software from the Materials Data Facility of the Center for Hierarchical Materials Design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

NucD-23 Nuclear Diagnostics Development: The future of neutron imaging and gamma reaction history

The Neutron Imaging team has deployed novel, active detection systems along two lines of sight at NIF. Studies aimed to characterize NIS sensitivity to implosion shape will be carried out to further extend reconstruction capabilities. Additionally, an improved camera timing system that will reduce uncertainties stemming from bang time jitter will also be fielded. The NIF GRH data recording system is more then 10 years old needs to be updated. Bandwidth and noise are a key limiting factor for improving data quality. New high bandwidth and low noise components will be tested at OMEGA in advance before fielding the components at NIF.

42 ENGINEERING↗
DOE OSTI2021

Influence of tower shadow on downwind flexible rotors: Field tests and simulations

Abstract As wind turbine rotors become larger, the blades become more flexible, requiring extra stiffness and cost to avoid the risk of tower strike. Wind turbines in a downwind configuration have a reduced risk of tower strike because the rotor thrust acts away from the tower. However, downwind blades pass through the wake of the tower, and the resulting load variation may contribute to blade fatigue. To date, there have been no field tests to quantify this tower shadow effect on unsteady blade moments. The present study reports on the first field testing of a flexible, downwind, coned rotor and compares the experimental data against simulations run in OpenFAST. The tower shadow effect is simulated using the conventional Powles model and a new Eames model (developed herein), which includes the influence of upstream turbulence. Both models reasonably predict the blade root out‐of‐plane bending moment data and the tower shadow dip magnitude when compared to field test data in Region 3. Tower shadow was found to increase the short‐term Damage Equivalent Loads (DELs) by less than 10% compared to other effects (gravity, shear, and turbulence), and the predictions were consistent with experiments. These results indicate that the tower shadow effect can be reasonably modeled with the simpler Powles model and that the tower shadow effect can be small compared to the effect of turbulence. However, long‐term fatigue due to tower shadow should be included in detailed structural analysis and design of the rotor and the tower.

Simpson, Juliet G.↗