Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “spatial mapping”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

ENVI-PV: An Interactive Web Client for Multi-Criteria Life Cycle Assessment of Photovoltaic Systems Worldwide

Solar photovoltaics (PV) is the second largest source of new capacity among renewable energies. The worldwide capacity encompassed 135 GW in 2013 and is estimated to increase to 1721 GW in 2030 and 4674 GW in 2050, according to a prospective high-renewable scenario. To achieve this production level while minimizing environmental impacts, decision makers must have access to environmental performance data that reflect their high spatial variability accurately. We propose ENVI-PV (http://viewer.webservice-energy.org/project_iea), a new interactive tool that provides maps and screening level data, based on weighted average supply chains, for the environmental performance of common PV technologies. Environmental impacts of PV systems are evaluated according to a life cycle assessment approach. ENVI-PV was developed using a state-of-the-art interoperable and open standard Web Service framework from the Open Geospatial Consortium (OGC). It combines the latest life cycle inventories, published in 2015 by the International Energy Agency (IEA) under the Photovoltaic Power Systems Program (PVPS) Task 12, and some inventories previously published from Ecoinvent v2.2 database with solar irradiation estimates computed from the worldwide NASA SSE database. ENVI-PV is the first tool to propose a worldwide coverage of environmental performance of PV systems using a multi-criteria assessment. The user can compare the PV environmental performance to the environmental footprint of country electricity mixes. ENVI-PV is designed as an environmental interactive tool to generate PV technological options and evaluate their performance in different spatial and techno-economic contexts. Its potential applications are illustrated in this paper with several examples.

14 SOLAR ENERGY↗
DOE OSTI2023

HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data

Abstract Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km 2 across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems.

Science & Technology - Other Topics↗
DOE OSTI2017

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

Abstract. This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks

Land cover datasets are essential for modeling and analysis of Arctic ecosystem structure and function and for understanding land–atmosphere interactions at high spatial resolutions. However, most Arctic land cover products are generated at a coarse resolution, often limited due to cloud cover, polar darkness, and poor availability of high-resolution imagery. A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5 m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. The fusion of hyperspectral, multispectral, and terrain datasets was performed using unsupervised and supervised classification techniques over a ~343 km 2 area, and a high-resolution (5 m) vegetation classification map was generated. An unsupervised technique was developed to classify high-dimensional remote sensing datasets into cohesive clusters. We employed a quantitative method to add supervision to the unlabeled clusters, producing a fully labeled vegetation map. We then developed convolutional neural networks (CNNs) using the multi-sensor fusion datasets to map vegetation distributions using the original classes and the classes produced by the unsupervised classification method. To validate the resulting CNN maps, vegetation observations were collected at 30 field plots during the summer of 2016, and the resulting vegetation products developed were evaluated against them for accuracy. Our analysis indicates the CNN models based on the labels produced by the unsupervised classification method provided the most accurate mapping of vegetation types, increasing the validation score (i.e., precision) from 0.53 to 0.83 when evaluated against field vegetation observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Nanoscale mapping of the three-dimensional deformation field within commercial nanodiamonds

Here, the unique properties of nanodiamonds make them suitable for use in a wide range of applications, including as biomarkers for cellular tracking in vivo at the molecular level. The sustained fluorescence of nanodiamonds containing nitrogen-vacancy (N-V) centres is related to their internal structure and strain state. Theoretical studies predict that the location of the N-V centre and the nanodiamonds' residual elastic strain state have a major influence on their photoluminescence properties. However, to date there have been no direct measurements made of their spatially resolved deformation fields owing to the challenges that such measurements present. Here we apply the recently developed technique of Bragg coherent diffractive imaging (BCDI) to map the three-dimensional deformation field within a single nanodiamond of approximately 0.5 µm diameter. The results indicate that there are high levels of residual elastic strain present in the nanodiamond which could have a critical influence on its optical and electronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-Throughput Nanoindentation Mapping of Additively Manufactured T91 Steel

Here, this work aims to adapt nanoindentation mapping combined with a k-means algorithm as a high-throughput technique to study the nano-scale spatial changes in mechanical properties for a heterogeneous material. This technique can also classify the individual data points based on their properties. Hundreds to thousands of indents were performed on additively manufactured T91 at room temperature, 300°C, 400°C, and 500°C across a square area with a side length of 120 μm to 400 μm. From this data, the hardness and reduced modulus at each point could be calculated and mapped. Using k-means clustering, we were able to arrange the data into three or four clusters corresponding roughly to the ferritic and martensitic phases as well as one or two intermediate clusters sampling both the phases. The hardness of these two phases appears to be quite stable as a function of temperature. Nanoindentation mapping and the k-means algorithm can therefore be used to rapidly assess the feasibility of heterogeneous materials under extreme conditions, such as nuclear reactor steels.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Capturing Hidden Geochemical Anomalies in Scarce Data by Fractal Analysis and Stochastic Modeling

Fractal/multifractal modeling is a widely used geomathematical approach to capturing different populations in geochemical mapping. The rationale of this methodology is based on empirical frequency density functions attained from global or local distributions. This approach is quite popular because of its simplicity and versatility; it accounts for the frequency and spatial distribution of geochemical data considering self-similarity across a range of scales. Using this technique for detection of geochemical anomalies in scarce data, however, is problematic and can lead to systematic bias in the characterization of the underlying populations. In this paper, an innovative technique is presented that provides good results without a priori assumptions. A simulation approach is adopted for fractal analysis by generating different possible distribution scenarios for the variable under study to reveal the underlying populations that are frequently hidden due to lack of data. The proposed technique is called the global simulated size–number method, and it is validated in a case study with two synthetic datasets and another case study with real dataset from the Ushtagan gold deposit in northeast Kazakhstan.

58 GEOSCIENCES↗
DOE OSTI2024

Thermal Transport and Mechanical Stress Mapping of a Compression Bonded GaN/Diamond Interface for Vertical Power Devices

Bonding diamond to the back side of gallium nitride (GaN) electronics has been shown to improve thermal management in lateral devices; however, engineering challenges remain with the bonding process and characterizing the bond quality for vertical device architectures. Here, in this study, integration of these two materials is achieved by room-temperature compression bonding centimeter-scale GaN and a diamond die via an intermetallic bonding layer of Ti/Au. Recent attempts at GaN/diamond bonding have utilized a modified surface activation bonding (SAB) method, which requires Ar fast atom bombardment immediately followed by bonding within the same tool under ultrahigh vacuum (UHV) conditions. The method presented here does not require a dedicated SAB tool yet still achieves bonding via a room-temperature metal–metal compression process. Imaging of the buried interface and the total bonding area is achieved via transmission electron microscopy (TEM) and confocal acoustic scanning microscopy (C-SAM), respectively. The thermal transport quality of the bond is extracted from spatially resolved frequency-domain thermoreflectance (FDTR) with the bonded areas boasting a thermal boundary conductance of >100 MW/m 2 ·K. Additionally, Raman maps of GaN near the GaN–diamond interface reveal a low level of compressive stress, <80 MPa, in well-bonded regions. FDTR and Raman were coutilized to map these buried interfaces and revealed some poor thermally bonded areas bordered by high-stress regions, highlighting the importance of spatial sampling for a complete picture of bond quality. Overall, this work demonstrates a novel method for thermal management in vertical GaN devices that maintains low intrinsic stresses while boasting high thermal boundary conductances.

Raman↗
DOE OSTI2018

iCHORD-SI combination as an alternative to EDS-EBSD coupling for the characterization of γ-γ′ nickel-based superalloy microstructures

Highlights: • A new method to get orientation maps discriminating the gamma and gamma’ phases of Ni superalloys is described. • The method combines the iCHORD technique with secondary ion imaging. • The new method resolves precipitates down to 150 nm within a reasonable acquisition time. - Abstract: Because they exhibit very similar diffraction patterns, the γ and γ′ phases of nickel-based superalloys cannot be distinguished by the conventional EBSD technique alone. This paper presents an original method which discriminates those phases on an orientation map by exploiting their chemical differences. Performed with a Focused Ion Beam (FIB) microscope, the method is the combination of the ion CHanneling ORientation Determination technique (iCHORD) – recently developed by Langlois et al. [1] – with the chemical information obtained from Secondary Ion (SI) images. The performances of the method are compared to the EDS-EBSD coupling which also discriminates phases based on their chemical compositions. Applied filters, angular resolution, spatial resolution of the phase discrimination and acquisition time are discussed. It results that the iCHORD–SI combination offers an orientation map with an angular resolution slightly decreased compared to that of the EBSD technique, but with a good phase resolution (down to 150 nm) and within a reasonable acquisition time. Thus, the iCHORD–SI combination appears to be an interesting method for the crystallographic systems where phases are difficult to discriminate by the EBSD technique alone but present a significant chemical contrast.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Areas with Surface Thermal Anomalies as Detected by ASTER and LANDSAT Data in Southwest Steamboat Springs, Garfield County, Colorado

This map shows areas of anomalous surface temperature around south Steamboat Springs as identified from ASTER and LANDSAT thermal data and spatial based insolation model. The temperature for the ASTER data was calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas having anomalous temperature in the ASTER data are shown in blue diagonal hatch, while areas having anomalous temperature in the LANDSAT data are shown in magenta on the map. Thermal springs and areas with favorable geochemistry are also shown. Springs or wells having non-favorable geochemistry are shown as blue dots.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Self-sensing cantilevers with integrated conductive coaxial tips for high-resolution electrical scanning probe metrology

The lateral resolution of many electrical scanning probe techniques is limited by the spatial extent of the electrostatic potential profiles produced by their probes. Conventional unshielded conductive atomic force microscopy probes produce broad potential profiles. Shielded probes could offer higher resolution and easier data interpretation in the study of nanostructures. Electrical scanning probe techniques require a method of locating structures of interest, often by mapping surface topography. As the samples studied with these techniques are often photosensitive, the typical laser measurement of cantilever deflection can excite the sample, causing undesirable changes electrical properties. In this work, we present the design, fabrication, and characterization of probes that integrate coaxial tips for spatially sharp potential profiles with piezoresistors for self-contained, electrical displacement sensing. With the apex 100 nm above the sample surface, the electrostatic potential profile produced by our coaxial tips is more than 2 times narrower than that of unshielded tips with no long tails. In a scan bandwidth of 1 Hz–10 kHz, our probes have a displacement resolution of 2.9 Å at 293 K and 79 Å at 2 K, where the low-temperature performance is limited by amplifier noise. We show scanning gate microscopy images of a quantum point contact obtained with our probes, highlighting the improvement to lateral resolution resulting from the coaxial tip.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Spatial top-down proteomics for the functional characterization of human kidney

Background: The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. Results: Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions. Conclusions: We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Three-dimensional electronic scaffold for cardiac applications

Disclosed here is a three-dimensional electronic scaffold, comprising a porous scaffold and a plurality of micro-strain gauges distributed spatially inside the porous scaffold, wherein the micro-strain gauges are adapted to detect contraction force. Also disclosed is a method comprising detecting and mapping intra-tissue cardiac contraction force of one or more cardiac cells or tissues disposed in a three-dimensional electronic scaffold, wherein the three-dimensional electronic scaffold comprises a porous scaffold and a plurality of micro-strain gauges distributed spatially inside the porous scaffold and in contact with the cardiac cells or tissues, and wherein the micro-strain gauges are adapted to detect contraction force of the cardiac cells or tissues.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

The RINGS Survey. III. Medium-resolution Hα Fabry–Pérot Kinematic Data Set

The distributions of stars, gas, and dark matter in disk galaxies provide important constraints on galaxy formation models, particularly on small spatial scales (<1 kpc). We have designed the RSS Imaging spectroscopy Nearby Galaxy Survey (RINGS) to target a sample of 19 nearby spiral galaxies. For each of these galaxies, we obtain and model Hα and H i 21 cm spectroscopic data as well as multi-band photometric data. We intend to use these models to explore the underlying structure and evolution of these galaxies in a cosmological context, as well as whether the predictions of ΛCDM are consistent with the mass distributions of these galaxies. In this paper, we present spectroscopic imaging data for 14 of the RINGS galaxies observed with the medium spectral resolution Fabry–Pérot etalon on the Southern African Large Telescope. From these observations, we derive high spatial resolution line-of-sight velocity fields of the Hα line of excited hydrogen, as well as maps and azimuthally averaged profiles of the integrated Hα and [N ii] emission and oxygen abundances. We then model these kinematic maps with axisymmetric models, from which we extract rotation curves and projection geometries for these galaxies. We show that our derived rotation curves agree well with other determinations, and the similarity of the projection angles with those derived from our photometric images argues against these galaxies having intrinsically oval disks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A mapped dataset of surface ocean acidification indicators in large marine ecosystems of the United States

Mapped monthly data products of surface ocean acidification indicators from 1998 to 2022 on a 0.25° by 0.25° spatial grid have been developed for eleven U.S. large marine ecosystems (LMEs). The data products were constructed using observations from the Surface Ocean CO 2 Atlas, co-located surface ocean properties, and two types of machine learning algorithms: Gaussian mixture models to organize LMEs into clusters of similar environmental variability and random forest regressions (RFRs) that were trained and applied within each cluster to spatiotemporally interpolate the observational data. The data products, called RFR-LMEs, have been averaged into regional timeseries to summarize the status of ocean acidification in U.S. coastal waters, showing a domain-wide carbon dioxide partial pressure increase of 1.4 ± 0.4 μatm yr -1 and pH decrease of 0.0014 ± 0.0004 yr -1 . RFR-LMEs have been evaluated via comparisons to discrete shipboard data, fixed timeseries, and other mapped surface ocean carbon chemistry data products. Regionally averaged timeseries of RFR-LME indicators are provided online through the NOAA National Marine Ecosystem Status web portal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Review of environmental metrics used across multiple sectors and geographies to evaluate the effects of hydropower development

In this paper, as U.S. hydropower development continues to expand, a thorough inventory of potentially relevant environmental metrics will provide a comprehensive and transparent starting point for stakeholders seeking to evaluate the sustainability and environmental effects of this anticipated expansion. To address this need, we conducted a literature review to extract and analyze a swath of environmental metrics related to previous hydropower projects. Our examination of several U.S. Federal Energy Regulatory Commission licensing documents, several certification documents prepared by the Low Impact Hydropower Institute and the International Hydropower Association, and a set of peer-reviewed journal articles led to creation of a database of > 3000 current environmental metrics related to hydropower projects in 231 locations worldwide. Information recorded for each environmental metric was used to map the comprehensiveness and consistency of environmental measurements gathered across primary categories, dam life cycle stages, spatial scales and locations. We found that a majority of environmental metrics were related to water quantity and water quality, a large number of metrics were related to biota and biodiversity, and relatively few metrics were related to the categories of geomorphology, land cover, connectivity and fragmentation, and infrastructure and design. However, the categories of environmental metrics represented in each type of literature varied significantly. Forty-five subcategories of environmental metrics emerged from our analysis, thereby suggesting a potential envelope of environmental measurements that might be used to improve efficiency in evaluating the potential environmental effects of new U.S. hydropower projects.

13 HYDRO ENERGY↗
DOE OSTI2013

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Experimental data for damage mechanics simulation challenge

While there are many computational approaches for simulating damage in rock and other materials, few have been ground truth tested with either known experimental data or with blind data sets. Here, in this work, we present a bench-mark laboratory data set for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile materials. The samples were fabricated through additive manufacturing to produce repeatable specimens designed to fail in controlled ways. The failure was induced in the samples using a 3-point bending test to produce different Modes such as Mode I and mixed Modes including I-II, I-III and I-II-III Modes to generate a calibration data set and a blind challenge data set. Data collected included spatial and temporal measurements from traditional digital load–displacement sensors, 2D digital image correlation measurement to map surface deformations, 3D X-ray microscopy to ground-truth the crack-failure geometry, and laser profilometry to capture surface roughness. The data sets are available, on a data repository, to the community to advance computational models to improve our ability to predict damage in brittle-ductile materials.

3-point bending↗