Effects of different field expansions on omnidirectional proton counting rate data
Field expansion effects on omnidirectional proton counting rate data
COUNTING RATE COMPUTER↗
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Results for “Field data”
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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A compressed marine data set for geomagnetic field modeling
Some 13 million scalar magnetic field data points that have been collected from the world's ocean areas reside in the collection of the National Geophysical Data Center. In order to derive a suitable data set for modeling the geomagnetic field of the earth, each ship track is divided into 220 km segments. The distribution of the reduced data in position, time and local time is discussed. The along-track filtering process described has proved to be an effective method of condensing large numbers of shipborne magnetic data into a manageable and meaningful data set for field modeling. This process also provides the benefits of smoothing short-wavelength crystal anomalies, discarding data recorded during magnetically noisy periods, and assigning reasonable error estimates to be utilized in the least squares modeling.
Langel, R. A.↗
Bumblebee program, aerodynamic data. Part 2: Flow fields at Mach number 2.0
Available flow field data which can be used in validating theoretical procedures for computing flow fields around supersonic missiles are presented. Tabulated test data are given which define the flow field around a conical-nosed cylindrical body in a crossflow plane corresponding to a likely tail location. The data were obtained at a Mach number of 2.0 for an angle of attack of 0 to 23 degrees. The data define the flow field for cases both with and without a forward wing present.
Barnes, G. A.↗
Validation of finite-element models using full-field experimental data: Levelling finite-element analysis data through a digital image correlation engine
Full-field data from digital image correlation (DIC) provide rich information for finite-element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions and data filtering. As such, in this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other, and (2) the proposed DIC-levelling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to ‘level’ the FEA data to the DIC data in a regularisation sense. Synthetic ‘experimental’ DIC data were generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errorswere computed, even though therewas no model form error, because the filtering effect of theDIC enginewas neglected. In contrast, the levelling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the levelling approach, it was clearly observed. Finally, the ‘experimental’ DIC datawere purposefully misaligned slightly fromthe FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In conclusion, direct interpolation is insufficient, and the proposed levelling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data have been ‘levelled’ to the DIC data can meaningful, quantitative error maps be computed.
42 ENGINEERING↗
Using Temporal Information from Human Mobility Data to Detect Anchor Points
Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.
McBride, Liz [ORNL] (ORCID:0000000286925869)↗
Improved Open Data Sharing of NASA Airborne and Field Investigation Data
Explore the source record for details and available documents.
Deborah K Smith↗
Data Mining Field I-V and Weather Data for PV Module EQE and Suns-Voc.
Abstract not provided.
Braid, Jennifer↗
Jemez Pueblo Agriculture: Monitoring Rangeland Conditions to Inform Drought and Land Management in New Mexico
The Jemez Pueblo, a community located in the semi-arid high desert region of northcentral New Mexico, faces challenges with drought mitigation and livestock management. NASA DEVELOP partnered with the Pueblo of Jemez Natural Resources Department and The Nature Conservancy to provide recent and historical rangeland conditions to aid present decision-making, which relies on cultural practices, site familiarity, available resources, and physical data. This partnership offers the opportunity to support management practices by leveraging remote sensing and virtual fencing technologies. Our project explored Rangeland Analysis Platform (RAP) products incorporating NASA Earth observation Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2 remote-sensed imagery as an agricultural land management tool. We performed linear regression analysis to evaluate RAP data to field data and explored RAP annual herbaceous biomass, ground cover trends, and climatic factors at the pasture level. We then computed study area summary statistics, performed pixel-by-pixel trend analysis across the study period, and evaluated ground cover trends near water sources. Based on available data, RAP was poorly correlated to bare ground and herbaceous biomass, generally underestimating the former and overestimating the latter. To improve the evaluation of RAP products, we suggest increasing the spatiotemporal distribution of the field dataset. According to RAP, from 1986 to 2023, the site became hotter and drier, bare ground increased, and annual forbs and grasses increased while perennials decreased. RAP products did not agree with field-collected data; however, the trends over time may be useful for informing rangeland management actions.
cattle grazing management↗
The 1983 tail-era data series. Volume 2: ISEE 3 magnetic field
ISEE 3 spacecraft measurements within and near the Earth's magnetic tail is presented. Plots are shown of ISEE 3 magnetic field data. The plots in this volume showing observations from the ISEE 3 vector helium magnetometer experiment were produced from a tape of merged plasma/magnetic field data. The magnetometer produced six vector measurements/sec that were subsequently averaged over one minute intervals before merging with plasma data. Merging was accomplished by associating the nearest 1 minute field average with each plasma sample.
Fairfield, D. H.↗
Forest regeneration within Earth system models: current process representations and ways forward
Earth system models must predict forest responses to global change in order to simulate future global climate, hydrology, and ecosystem dynamics. These models are increasingly adopting vegetation demographic approaches that explicitly represent tree growth, mortality, and recruitment, enabling advances in the projection of forest vulnerability and resilience, as well as evaluation with field data. To date, simulation of regeneration processes has received far less attention than simulation of processes that affect growth and mortality, in spite of their critical role maintaining forest structure, facilitating turnover in forest composition over space and time, enabling recovery from disturbance, and regulating climate-driven range shifts. Here, our critical review of regeneration process representations within current Earth system vegetation demographic models reveals the need to improve parameter values and algorithms for reproductive allocation, dispersal, seed survival and germination, environmental filtering in the seedling layer, and tree regeneration strategies adapted to wind, fire, and anthropogenic disturbance regimes. These improvements require synthesis of existing data, specific field data-collection protocols, and novel model algorithms compatible with global-scale simulations. Vegetation demographic models offer the opportunity to more fully integrate ecological understanding into Earth system prediction; regeneration processes need to be a critical part of the effort.
54 ENVIRONMENTAL SCIENCES↗
Field Model: An Object-Oriented Data Model for Fields
We present an extensible, object-oriented data model designed for field data entitled Field Model (FM). FM objects can represent a wide variety of fields, including fields of arbitrary dimension and node type. FM can also handle time-series data. FM achieves generality through carefully selected topological primitives and through an implementation that leverages the potential of templated C++. FM supports fields where the nodes values are paired with any cell type. Thus FM can represent data where the field nodes are paired with the vertices ("vertex-centered" data), fields where the nodes are paired with the D-dimensional cells in R(sup D) (often called "cell-centered" data), as well as fields where nodes are paired with edges or other cell types. FM is designed to effectively handle very large data sets; in particular FM employs a demand-driven evaluation strategy that works especially well with large field data. Finally, the interfaces developed for FM have the potential to effectively abstract field data based on adaptive meshes. We present initial results with a triangular adaptive grid in R(sup 2) and discuss how the same design abstractions would work equally well with other adaptive-grid variations, including meshes in R(sup 3).
Moran, Patrick J.↗
Electric fields in the plasma sheet and plasma sheet boundary layer
Results obtained by Forbes et al. (1981) on the basis of time delay measurements between ISEE 1 and ISEE 2 imply that the plasma flow and the boundary contracting velocity were nearly the same, whereas the expanding boundary velocity was not accompanied by any significant plasma sheet plasma motion. In the present study, this observation is discussed in conjunction with electric field data. The study is based on electric field data from the spherical double probe experiment on ISEE 1. Electric field data from GEOS 2 are used to some extent to monitor the electric fields near the geostationary orbit during the considered eve nts. Electric field data during CDAW 6 events are discussed, taking into account positions of ISEE 1/ISEE 2 and GEOS 2; March 22, 0600-1300 UT; and March 22, UT; and March 31, 1400-2400 UT.
Pedersen, A.↗
Role of sudden commencements in triggering magnetospheric substorms
Sudden commencement events are examined in terms of available auroral-zone and low-latitude magnetic field, data, interplanetary plasma and magnetic field data, and magnetospheric electron flux and magnetic field data from the geostationary satellite ATS 1.
Newell, R. E.↗
Utah FORGE 2439: Well 16B(78)-32 Field-Test Data from Mini-Frac Tests
This submittal includes the field-test data collected during stress tests conducted in the Utah FORGE 16B(78)-32 wellbore to measure/characterize the stresses in the geothermal reservoir. The type of stress test performed is referred to as a mini-frac test or a micro-frac test. The test is a hydraulic fracture test that involves injecting a small volume of water into a short interval of the reservoir that is isolated by a straddle packer to create a fracture. The test provides information about the minimum and maximum horizontal stress at the test depths. A total of seven mini-frac tests were performed within the upper (vertical or nearly vertical) section of the 9-5/8-inch diameter uncased wellbore, between depths of 5,202 ft MD [5,202 ft TVD] and 5,980 ft MD [5966.18 ft TVD]. Two types of data were generated as part of the mini-frac tests. The first type of data is time-series data for each mini-frac test (e.g., injection-rate, test-interval pressure), and are contained in the "Mini-Frac Test Data.zip" file below. The second type is geophysical log data, attached below in the "Geophysical Logs.zip" file. Here, two types of image logs and acoustic logs were obtained before and after the mini-frac tests to examine each test depth for visual evidence of induced fracture(s) and to measure the azimuth (orientation) of any observed fractures. The attached Readme file includes the test depth information and contents of each data file included here. Analysis of the field-test data was conducted and is documented in the attached report below.
15 GEOTHERMAL ENERGY↗
Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach
The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.
Smith, James A.↗
Time-lapse seismic inversion for CO 2 saturation with SeisCO2Net: An application to Frio-II site
Seismic monitoring of geological CO 2 storage (GCS) involves highly nonlinear seismic inversion and petrophysical inversion, making it challenging to estimate CO 2 volume efficiently and detect possible early CO 2 leakages. Deep learning (DL) using convolutional neural networks (CNNs) has shown promise in solving highly nonlinear seismic inversion problems. However, direct estimation of CO 2 plume extent/saturation from time-lapse seismic gathers using DL is still underexplored, with no reported field applications to date. The investigation of field data is primarily hindered by scarcity of field data for neural network training. Other obstacles include highly nonlinear seismic-petrophysics inverse relationship, and presence of noise in field seismic data. We introduce SeisCO2Net, a deep CNN that predicts CO 2 saturation maps directly from time-lapse full waveform shot gathers. For training, we use site-specific geological information, fluid flow physics, rock physics, and seismic modeling to generate synthetic datasets that closely resemble the CO 2 storage site. Synthetic tests show promising results, inspiring us to apply SeisCO2Net's trained weights on field data collected at Frio-II GCS site by leveraging transfer learning principles. As reference, we compare SeisCO2Net's predicted CO 2 saturation maps with results obtained from physics-based inversion. Our analyses show both methods display similar CO 2 plume shapes, reasonable CO 2 plume characteristics, and comparable saturation values. Our results suggest pre-training CNNs on physics-informed synthetic datasets and then applying the learned weights to field data is a viable approach to estimating field CO 2 saturation. This method effectively addresses the scarcity of field training data, thus encouraging the feasibility of long-term GCS monitoring.
58 GEOSCIENCES↗
Annual Sea Level Variability Induced by Changes in Sea Ice Extent and Accumulation on Ice Sheets: An Assessment Based on Remotely Sensed Data
Changes of mean annual net accumulation at the surface on the grounded ice sheets of East Antarctica, West Antarctica, and Greenland in response to variations in sea ice extent are estimated using grid-point values 100 km apart. The data bases are assembled principally by bilinear interpolation of remotely sensed brightness temperature (Nimbus-5 ESMR, Nimbus-7 SMMR), surface temperature (Nimbus-7 THIR), and surface elevation (ERS-1 radar altimeter). These data, complemented by field data where remotely sensed data are not available, are used in multivariate analyses in which mean annual accumulation (derived from firn emissivity) is the dependent variable; the independent variables are latitude, surface elevation, mean annual surface temperature, and mean annual distance to open ocean (as a source of energy and moisture). The last is the shortest distance measured between a grid point and the mean annual position of the 10% sea ice concentration boundary, and is used as an index of changes in sea ice extent as well as of mean concentration. Stepwise correlation analyses indicate that variations in sea ice extent of +/-50 km would lead to changes in accumulation inversely of +/-4% on East Antarctica, +/- 10% on West Antarctica, and +4% on Greenland. These results are compared with those obtained in a previous study using visually interpolated values from contoured compilations of field data; they substantiate the findings for the Antarctic ice sheets (+/-4% on East Antarctica, +/-9% in West Antarctica), and suggest a reduction by one half of the probable change of accumulation on Greenland (from +/-8%). The results also suggest a reduction of the combined contribution to sea level variability to +/- 0.19 mm/a (from +/- 0.22 mm/a).
Zwally, H. J.↗
ESnet Watershed Field Science Data Backhaul Campaign Report
ESnet’s Watershed Field Science Data Backhaul Campaign is intended to improve the ability to gather data from sensors deployed across the East River and Trail Creek watersheds, with a special focus on the Snodgrass distributed sensor area, the Pumphouse instruments with co-located U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Surface Atmosphere Integrated Field Laboratory (SAIL) tethered balloon setup, and the former ARM SAIL campaign’s second ARM Mobile Facility (AMF2) site by the Watershed Function Science Focus Area (WFSFA) program. This program is not funded by ARM, but collaborates with ARM as part of the SAIL campaign, collocated with the WFSFA field sites in Colorado’s East River Watershed.
54 ENVIRONMENTAL SCIENCES↗