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All sources NASA NTRS DOE OSTI

DOE OSTI2019

High-sensitivity gas-mapping 3D imager and method of operation

Measurement apparatuses and methods are disclosed for generating high-precision and -accuracy gas concentration maps that can be overlaid with 3D topographic images by rapidly scanning one or several modulated laser beams with a spatially-encoded transmitter over a scene to build-up imagery. Independent measurements of the topographic target distance and path-integrated gas concentration are combined to yield a map of the path-averaged concentration between the sensor and each point in the image. This type of image is particularly useful for finding localized regions of elevated (or anomalous) gas concentration making it ideal for large-area leak detection and quantification applications including: oil and gas pipeline monitoring, chemical processing facility monitoring, and environmental monitoring.

Kreitinger, Aaron↗

DOE OSTI2021

High-sensitivity gas-mapping 3D imager and method of operation

Kreitinger, Aaron Thomas↗

DOE OSTI2023

High-sensitivity gas-mapping 3D imager and method of operation

Kreitinger, Aaron Thomas↗

NASA NTRS2017

Weathering the Storm: Unmanned Aircraft Systems in the Maritime, Atmospheric and Polar Environments

Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASAs Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

data collection↗

DOE OSTI2023

Extensive 3D mapping of dislocation structures in bulk aluminum

Abstract Thermomechanical processing such as annealing is one of the main methods to tailor the mechanical properties of materials, however, much is unknown about the reorganization of dislocation structures deep inside macroscopic crystals that give rise to those changes. Here, we demonstrate the self-organization of dislocation structures upon high-temperature annealing in a mm-sized single crystal of aluminum. We map a large embedded 3D volume ( $$100\times 300\times 300$$ 100 × 300 × 300 $$\upmu$$ μ m $$^3$$ 3 ) of dislocation structures using dark field X-ray microscopy (DFXM), a diffraction-based imaging technique. Over the wide field of view, DFXM’s high angular resolution allows us to identify subgrains, separated by dislocation boundaries, which we identify and characterize down to the single-dislocation level using computer-vision methods. We demonstrate how even after long annealing times at high temperatures, the remaining low density of dislocations still pack into well-defined, straight dislocation boundaries (DBs) that lie on specific crystallographic planes. In contrast to conventional grain growth models, our results show that the dihedral angles at the triple junctions are not the predicted 120 $$^{\circ }$$ ∘ , suggesting additional complexities in the boundary stabilization mechanisms. Mapping the local misorientation and lattice strain around these boundaries shows that the observed strain is shear, imparting an average misorientation around the DB of $$\approx$$ ≈ 0.003 to 0.006 $$^{\circ }$$ ∘ .

36 MATERIALS SCIENCE↗

NASA NTRS2016

Using Remotely Piloted Aircraft and Onboard Processing to Optimize and Expand Data Collection

Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASA’s Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

Fladeland, Matthew M.↗

NASA NTRS2021

LiDAR-Based Map Relative Localization Performance Analysis for Landing on Europa

This paper presents preliminary simulations andanalyses done to assess the feasibility of performing Map RelativeLocalization (MRL) with the Europa Lander LiDAR beingdeveloped for the Europa Lander Pre-Phase A concept. MapRelative Localization is the process of determining the horizontalposition of a lander with respect to an onboard, a-priori map,by comparing the map to sensor observations of the terrain duringdeorbit, descent, and landing (DDL). Although kilometerscaleposition knowledge is commonly available during DDL,landing in hazard-rich environments requires position errors of100 m or less. Prior knowledge in the case of Europa Landerwill be visual and topographic maps collected by the upcomingEuropa Clipper mission. The Mars 2020 Lander Vision System(LVS) uses images from a camera to localize with respect tovisual maps. This technology, as well as a 3D imaging LiDAR indevelopment for hazard detection, is currently baselined for theEuropa Lander Pre-Phase A concept. This paper investigatesthe potential use of the hazard detection LiDAR to performMRL with respect to a 3D digital elevation model (DEM)provided by the Europa Clipper mission, as an alternative orbackup solution to passive optical MRL. Compared to passiveoptical MRL, one advantage of LiDAR-based localization isthat it is insensitive to lighting conditions, potentially relaxingrequirements on synchronizing map acquisition and landingtime of day. To analyze LiDAR based MRL performance,six representative terrains are synthetically up-sampled fromGalileo-derived maps of Europa to a resolution of 0.5 m/pxand covering an area of 4 km by 4 km. These maps are usedas ground-truth to generate simulated noisy a-priori onboardtopographic maps expected from Europa Clipper as well assimulated LiDAR DEMs generated at an altitude of 5 km duringEuropa Lander DDL. The simulated LiDAR DEM is matchedagainst the simulated map via 2D normalized cross-correlation,exploiting the accurately known spacecraft attitude to avoidthe need for more computationally intensive algorithms such asIterative Closest Point (ICP). Two sources of measurement errorare identified for analysis: 1) additive Gaussian noise in therange measurements from the Europa Lander LiDAR and theEuropa Clipper derived maps and 2) errors in the LiDAR DEMinduced by errors in the Europa Lander state estimate which isused to de-warp the LiDAR scan data into a DEM format. Weassess the effect of each of these types of errors independently onmatching performance as well as the overall performance whenall types of error are introduced. Additionally, we present theresult of a sensitivity study to terrain frequency content.

Trawny, Nikolas↗

DOE OSTI2026

PFLOTRAN modeling data and scripts associated with “Refining the Hydrogeologic Framework of a Large River Corridor Model Using Waterborne Transient Electromagnetics”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Refining the Hydrogeologic Framework of a Large River Corridor Model Using Waterborne Transient Electromagnetics” submitted to Water Resources Research (Terry et al. 2025). The data package contains the groundwater modeling dataset from PFLOTRAN software. It includes the python script for mesh generation, boundary condition setting, PFLOTRAN input deck formation and postprocessing. It couples groundwater flow and species transport for Hanford Reach river corridor and pipelines the model generation and processing. This model can be used to easily generate the model and analysis for Hanford site. It can also be adjusted to other hydrologic area with ease. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. The data package consists of 6 folders: (1) “data” contains all necessary data as input and intermediate data for processing; (2) “mesh” contains all mesh related files to generate mesh in Hanford Reach river corridor; (3) “model_run” contains the generated script for PFLOTRAN modeling; (4) “notebooks” contains all the Python script to generate the model; (5) “output” contains all the output from the computation; (6) “postprocessing” contains the Python script to generate scientific figure for manuscript. All files are .csv (comma-separated values), .h5 (HDF5 format), .in (input files), .ipynb (Jupyter notebooks), .p (Python pickle), .png (images), .PNG (images), .py (Python scripts), .pyc (Python bytecode), .r (R scripts), .sh (shell scripts), .txt (text files), .vtu (3D mesh/visualization format), .xz (compressed archive), or .zip (compressed archive).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP), in collaboration with the Behavioral Health and Performance (BHP) Element, is conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within that volume. NASA is looking for innovative methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods for collecting such data exist yet many are obtrusive and require significant post‐processing. Example technologies used in terrestrial settings include infrared (IR) retro‐reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multiple camera filmography. However due to constraints of space operations many such methods are infeasible, such as inertial tracking systems which typically rely upon a gravity vector to normalize sensor readings, and traditional IR systems which are large and require extensive calibration. However multiple technologies have not yet been applied to space operations for these explicit purposes. Two of these include 3‐Dimensional Radio Frequency Identification Real‐Time Localization Systems (3D RFID‐RTLS) and depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR‐depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light‐Radar systems, referred to as LIDAR).

Vos, Gordon A.↗

NASA NTRSDate not supplied

Mineralogical, Elemental and Tomographic Reconnaissance Investigation for CLPS (“METRIC”)

METRIC comprises a suite of two instruments in a Lunar lander that perform X-ray diffraction (XRD) for mineral structure, X-ray fluorescence (XRF) for elemental composition, and X-ray Micro Computed Tomography (XCT) for 3D internal micromorphology. The instruments are accompanied by optical-near IR cameras to provide local geologic context. The Honeybee Robotics PlanetVac pneumatic sampling and transfer system [1],positioned on a lander footpad, will deliver sieved regolith to the X-ray instruments for analysis. The instrument suite is intended for delivery to the lunar surface on a Commercial Lunar Payload Services (CLPS) lander. The METRICXRD/F instrument draws on heritage from the Mars Science Laboratory CheMin instrument [2] and improves upon the design in multiple ways [3]. Like CheMin, Rietveld refinement and full-pattern fitting of METRIC XRD data can identify minerals at a detection limit of ~1 wt.%, quantify their abundances when present at >3 wt.%, and determine mineral composition (e.g., Fo#in olivine) from lattice parameters for minerals present at >5 wt.%[4,5]. An optimized XRF geometry provides for improved detection and quantification of major, minor and trace elements. The METRIC XCT instrument is a miniaturized X-ray Computed Tomography scanner[6]. Lunar regolith is delivered to a 3 mm diameter, 10 mm long graphite tube inside the instrument. The tube is rotated through 360°in 0.9deg.incrementsand a divergent point source X-ray beam is directed through the material. A Charge Coupled Device (CCD)records attenuation images whose brightness and contrast area function of average atomic number and density. Quantitative data, including particle and void sizes, 3D particle shape parameters, modal volumes and pore geometry can be derived from the resulting 3D reconstructions(voxel resolution: 30 μm). Crystal morphologies derived from METRIC XCT data complement the bulk mineralogy determined by the METRIC XRD/F and provide a measure of grain size distribution for the different phases. Taken together, the METRIC instrument suite determines crystal structure, elemental composition and morphology, three principal characteristics of geological materials that are highly useful in determining the origin and subsequent processing of lunar regolith.

Moon↗

DOE OSTI2022

Deblurring for nuclei: 3D characteristics of heavy-ion collisions

Observables from nuclear and high-energy experiments can be degraded by detector performance and/or methodology in extracting the observables, such as of the final-state characteristics of heavy-ion collisions in relation to a coarsely estimated reaction-plane direction. We propose the use of deblurring methods, such as in optics, to correct for observable degradation. Our main focus is the restoration of triple-differential particle distributions in heavy-ion collisions. We demonstrate that these could be extracted from collision measurements following the Richardson-Lucy deblurring method from optics. We illustrate basic features of the restoration methodology in a schematic model assuming either ideal or more realistic particle detection. Here, the inferred three-dimensional (3D) distributions for collisions may be easier to interpret in terms of collision dynamics and sought properties of bulk matter than the currently employed Fourier coefficients, that combine information from different azimuthal angles relative to the reaction plane.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1993

Computer-controlled multi-parameter mapping of 3D compressible flowfields using planar laser-induced iodine fluorescence

A computer-controlled technique, using planar laser-induced iodine fluorescence, for measuring complex compressible flowfields is presented. A new laser permits the use of a planar two-line temperature technique so that all parameters can be measured with the laser operated narrowband. Pressure and temperature measurements in a step flowfield show agreement within 10 percent of a CFD model except in regions close to walls. Deviation of near wall temperature measurements from the model was decreased from 21 percent to 12 percent compared to broadband planar temperature measurements. Computer-control of the experiment has been implemented, except for the frequency tuning of the laser. Image data storage and processing has been improved by integrating a workstation into the experimental setup reducing the data reduction time by a factor of 50.

Donohue, James M.↗

DOE OSTI2025

Preliminary hyperspectral neutron radiography of binder jet 3D printed and melt infiltrated Si–SiC

The preliminary results of hyperspectral neutron radiography of Si–SiC made with binder jet additive manufacturing, subsequent carbon addition, and silicon melt infiltration are presented. The samples were measured in the processing states before and after the melt infiltration to determine if neutrons would help characterize the microstructure to better understand the melt infiltration process. Theoretical Bragg edges were calculated for comparison with the radiographic results. The changes in the Bragg edges from pre- to post-infiltrated reaction-bonded SiC were evident, that could be used to address the differences in microstructures. In conclusion, the preliminary results presented in this study demonstrated that neutron Bragg-edge imaging is possible with Si–SiC reaction-bonded ceramics and can help determine the microstructure of melt infiltrated samples.

SiC↗

DOE OSTI2025

Insight into the deformation features and capacity loss mechanisms of lithium-ion pouch cells under spherical indentation conditions

Mechanical deformation under extreme conditions is one of the important reasons for the failure of lithium-ion batteries in automotive application. However, the deformation features and component failure of lithium-ion cells to external loading has never been a design consideration. Here, in this study, we conduct spherical indentation tests on a dozen of lithium-ion cells with different capacities under different control mode conditions to investigate their deformation features and capacity loss mechanisms. The experimental results show that, under mechanical deformation conditions, internal faults of cells occur in stages, and energy accumulation and sudden release are two key processes of cell's mechanical failure. The cells' state of charge is the main factor affecting their thermal runaway behaviors. In addition, a finite element model is developed to simulate the deformation features and the failure mechanism of key components of lithium-ion pouch cells; the 3D x-ray computed tomography is employed to demonstrate its internal configuration. With this model, the force-strain response, the deformation features as well as the size of the failure area of lithium-ion cells under spherical indentation conditions are accurately predicted. In 3D x-ray computed tomography images, unique mud cracks in cooper current collector are observed, and the influence mechanisms of the isolated fragments on the cell capacities are revealed. These results may provide useful information for the mechanical structure design of the components of lithium-ion pouch cells.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

Establishing an Urban Heat Exposure Severity Index for Infrastructure Prioritization in Tempe, Arizona, Using NASA Earth Observations and LiDAR

Located on the banks of the Salt River in the Sonoran Desert, Tempe, Arizona, features a semi-arid climate with summer daily maximum temperatures regularly exceeding 37.8°C. Tempe is also subject to the southwestern monsoon season from July-September and the humidity exacerbates the high temperatures. Furthermore, the rapid urbanization experienced in Tempe has resulted in an intensification of the urban heat island. The summer of 2020 shattered the previous record of days exceeding 43.4°C, leading to higher energy and water costs, lower comfort, and increased risk of heat stroke for residents. Recognizing the impacts of extreme heat, the City of Tempe partnered with the Healthy Urban Environments initiative and NASA DEVELOP to identify census tracts that experience a higher mean land surface temperature than the city average. The NASA DEVELOP team used remotely sensed land surface temperature (LST), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and albedo data calculated from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments from 2015 to 2020 to create heat hazard and exposure maps. LiDAR point cloud data, provided by the United States Geological Survey through Arizona State University’s Map and Geospatial Hub, were used to derive 3D buildings, building footprints, and tree point data for a shading analysis of walking paths, roads, and buildings at the census tract level. In situ meteorological measurements including air temperature and humidity were used to compare the macro-scale temperature measurements. The team worked with the City of Tempe to develop a methodology to process available data and identify areas of highest concern for urban heat effects within the city. With these insights, Tempe, Arizona can better address these issues with data-driven information to make decisions regarding heat mitigation and adaptation efforts.

John Dialesandro↗

DOE OSTI2018

Analysis of moisture migration in concrete at high temperature through in-situ neutron tomography

Spalling, which is a phenomenon encountered when high-performance concrete is exposed to high temperature, can lead to large economical damage and can be a major safety hazard. Moisture distribution in concrete during exposure to fire is of paramount importance for understanding the complex mechanism of this phenomenon. To capture in its fullness this mechanism, it is crucial to account for the heterogeneous nature of concrete. In this paper, the first 3D analysis of moisture distribution in concrete at high temperature through in-situ neutron tomography is presented. The world-leading flux at the Institute Laue Langevin in Grenoble, France allowed capturing one 3D scan per minute, which is sufficient to follow the fast dehydration process. The paper describes the experimental setup with the heating system and discusses in detail the framework of the neutron tomography test. Quantitative analysis showing the effect of the aggregate size on the moisture distribution is presented.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Scaling Building Energy Audits through Machine Learning Methods on Novel Drone Image Data

Building energy audits are time-consuming and labor-intensive. This paper describes a new method using machine learning (ML) techniques on novel data sources (drone images) to improve the identification of building characteristics and retrofit opportunities, and thereby reduce the effort for audits. The new ML method includes: (1) Building footprint extraction using line extraction, polygonization, and polygon-merging, (2) Building envelope extraction using PIX4d modeling software to reconstruct a building 3D model, (3) Visualization tool for viewing images from the 3D model, (4) Window-to-wall ratio (WWR) using state-of-art deep neural network semantic segmentation, (5) Envelope thermal anomaly detection using an unsupervised machine learning clustering algorithm, and (6) Rooftop energy equipment detection based on an object detection algorithm. The testing of this method involved a comparison of additional ML-generated information overlaid on current ‘state-of-practice’ audit and remote assessment baselines using evaluation metrics: labor time and associated cost, marginal benefits of using ML-generated information in workflows for audits and remote assessments, integration potential with existing processes and tools, and replicability/scalability of the method. In two test buildings in California that had comprehensive drawings and meter data available, the ML method effectively generated a building footprint, envelope, rooftop equipment, WWR, and locations of envelope thermal anomalies. Projected target segments of the ML method are sites with minimal drawings and energy data, and underserved sectors such as multistoried housing, disadvantaged communities, and schools for which the ML method can enable identification of building asset characteristics and prioritization of envelope retrofits and decentralized energy equipment retrofits.

Singh, Reshma↗

DOE OSTI2017

Three-dimensional Image Fusion Guidance for Transjugular Intrahepatic Portosystemic Shunt Placement

IntroductionTo assess the safety, feasibility and effectiveness of image fusion guidance with pre-procedural portal phase computed tomography with intraprocedural fluoroscopy for transjugular intrahepatic portosystemic shunt (TIPS) placement.Materials and methodsAll consecutive cirrhotic patients presenting at our interventional unit for TIPS creation from January 2015 to January 2016 were prospectively enrolled. Procedures were performed under general anesthesia in an interventional suite equipped with flat panel detector, cone-beam computed tomography (CBCT) and image fusion technique. All TIPSs were placed under image fusion guidance. After hepatic vein catheterization, an unenhanced CBCT acquisition was performed and co-registered with the pre-procedural portal phase CT images. A virtual path between hepatic vein and portal branch was made using the virtual needle path trajectory software. Subsequently, the 3D virtual path was overlaid on 2D fluoroscopy for guidance during portal branch cannulation. Safety, feasibility, effectiveness and per-procedural data were evaluated.ResultsSixteen patients (12 males; median age 56 years) were included. Procedures were technically feasible in 15 of the 16 patients (94%). One procedure was aborted due to hepatic vein catheterization failure related to severe liver distortion. No periprocedural complications occurred within 48 h of the procedure. The median dose-area product was 91 Gy cm{sup 2}, fluoroscopy time 15 min, procedure time 40 min and contrast media consumption 65 mL. Clinical benefit of the TIPS placement was observed in nine patients (56%).ConclusionThis study suggests that 3D image fusion guidance for TIPS is feasible, safe and effective. By identifying virtual needle path, CBCT enables real-time multiplanar guidance and may facilitate TIPS placement.

62 RADIOLOGY AND NUCLEAR MEDICINE↗