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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 451 records · Page 25

DER Translate

SAND2024-13723O This software translates and maps any .xlsx-based distributed energy resource (DER) device from the SunSpec certification registry (https://sunspec.org/certified-registry/) to a JSON-based DER models map. It is then read by DER monitoring tools for applications such as network intrusion detection and system health monitoring. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fragkos, Georgios↗

pySimpleMask

SF-26-118 pySimpleMask is a tool for creating masks and Q-partition maps for X-ray scattering patterns, supporting SAXS, WAXS, and XPCS data reduction. It ships both a desktop GUI and a headless Python API that can drive the full pipeline from scripts.

Chu, Miaoqi [Argonne National Laboratory (ANL), Ar↗

Connecting Matrix Elements to Multi-Hadron Form-Factors

We discuss developments in calculating multi-hadron form-factors and transition processes via lattice QCD. Our primary tools are finite-volume scaling relations, which map spectra and matrix elements to the corresponding multi-hadron infinite-volume amplitudes. We focus on two hadron processes probed by an external current, and provide various checks on the finite-volume formalism in the limiting cases of perturbative interactions and systems forming a bound state. By studying model-independent properties of the infinite-volume amplitudes, we are able to rigorously define form-factors of resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Estimating snow cover from high-resolution satellite imagery by thresholding blue wavelengths: Supporting Data

The extent and duration of snow cover is predicted to be altered as the climate changes. Developing high-resolution estimates of snow cover change is crucial for estimating changes in snow cover and the effects of these changes on watershed and ecosystems processes. Remote sensing tools have been a common method for rapidly mapping snow covered area (SCA) across a landscape. The most common remote sensing method for estimating SCA uses satellite-based calculations of the normalized difference snow index (NDSI), which relies on spectral measurements in the shortwave-infrared wavelengths (SWIR). NDSI is effective at catchment- to regional-scale estimates of SCA, but due to spatial resolution limitations of SWIR measurements, NDSI cannot be used to assess fine-scale SCA. In this work, we develop a new algorithm, called the Blue Snow Threshold (BST) algorithm, that maps high-resolution SCA by calculating a threshold on the blue wavelengths from high-resolution satellite imagery. This data package includes Orthorectified IKONOS-2 imagery (IkonosTestImage.tif) from August 14, 2004 at 1.00 meters Ground Sample Distance for Cook Inlet, Alaska (59.966414 , -152.982975). The Blue Snow Threshold algorithm (BST.py) was then used to produce a snow cover estimate (IkonosTestImage_BST.tif) for this study area. Additional imagery metadata is included in the ImageInfo.txt file. See Thaler et al., 2023 (https://doi.org/10.1016/j.rse.2022.113403) for more information about the BST algorithm.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Ablative liner locates hotspots

Ablative liner quantifies local-heating effects in combustion chambers and other applications. By identifying hotspots and helping to map heat-flux patterns, liner is useful tool for research in engine design. Liner permanently records heat flux at each point by depth of ablation due to local heating. Technique determines best locations for thermocouples for more extensive testing.

Mercer, S. D.↗

The thermal properties of Martian surface materials at high lattitudes: Possible evidence for permafrost

Evidence is presented from analysis of Viking thermal mapping results that suggests a transition to high thermal inertial material at a depth of approx. 12 cm at +75 deg latitude. This was interpreted as reflecting the transition from ice poor soil to hard frozen permafrost. It was pointed out that such a transition would be expected on the basis of theoretical models of hard frozen permafrost distribution. Although permafrost is not the only plausible martian surface material with high thermal inertia, polar thermal mapping may turn out to be a powerful tool for determining the distribution of permafrost deposits and understanding their behavior. At this point, the circumstantial case for permafrost deposits in the north pole region of Mars is very strong.

Paige, D. A.↗

An interactive environment for the analysis of large Earth observation and model data sets

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X Data Slice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

Bowman, Kenneth P.↗

An interactive environment for the analysis of large Earth observation and model data sets

We propose to develop an interactive environment for the analysis of large Earth science observation and model data sets. We will use a standard scientific data storage format and a large capacity (greater than 20 GB) optical disk system for data management; develop libraries for coordinate transformation and regridding of data sets; modify the NCSA X Image and X DataSlice software for typical Earth observation data sets by including map transformations and missing data handling; develop analysis tools for common mathematical and statistical operations; integrate the components described above into a system for the analysis and comparison of observations and model results; and distribute software and documentation to the scientific community.

Bowman, Kenneth P.↗

Self-Directed Cooperative Planetary Rovers

The project is concerned with the development of decision-theoretic techniques to optimize the scientific return of planetary rovers. Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We have developed a comprehensive solution to this problem that involves high-level tools to describe a mission; a compiler that maps a mission description and additional probabilistic models of the components of the rover into a Markov decision problem; and algorithms for solving the rover control problem that are sensitive to the limited computational resources and high-level of uncertainty in this domain.

Zilberstein, Shlomo↗

Self-Reacting Friction Stir Welding for Aluminum Alloy Circumferential Weld Applications

Friction stir welding is an innovative weld process that continues to grow in use, in the commercial, defense, and space sectors. It produces high quality and high strength welds in aluminum alloys. The process consists of a rotating weld pin tool that plasticizes material through friction. The plasticized material is welded by applying a high weld forge force through the weld pin tool against the material during pin tool rotation. The high weld forge force is reacted against an anvil and a stout tool structure. A variation of friction stir welding currently being evaluated is self-reacting friction stir welding. Self-reacting friction stir welding incorporates two opposing shoulders on the crown and root sides of the weld joint. In self-reacting friction stir welding, the weld forge force is reacted against the crown shoulder portion of the weld pin tool by the root shoulder. This eliminates the need for a stout tooling structure to react the high weld forge force required in the typical friction stir weld process. Therefore, the self-reacting feature reduces tooling requirements and, therefore, process implementation costs. This makes the process attractive for aluminum alloy circumferential weld applications. To evaluate the application of self-reacting friction stir welding for aluminum alloy circumferential welding, a feasibility study was performed. The study consisted of performing a fourteen-foot diameter aluminum alloy circumferential demonstration weld using typical fusion weld tooling. To accomplish the demonstration weld, weld and tack weld development were performed and fourteen-foot diameter rings were fabricated. Weld development consisted of weld pin tool selection and the generation of a process map and envelope. Tack weld development evaluated gas tungsten arc welding and friction stir welding for tack welding rings together for circumferential welding. As a result of the study, a successful circumferential demonstration weld was produced leading the way for future circumferential weld implementation.

Bjorkman, Gerry↗

Chemical Mixing Model and K-Th-Ti Systematics and HED Meteorites for the Dawn Mission

The Dawn mission will explore 4 Vesta, a large differentiated asteroid believed to be the parent body of the howardite, eucrite and diogenite (HED) meteorite suite. The Dawn spacecraft carries a gamma-ray and neutron detector (GRaND), which will measure the abundances of selected elements on the surface of Vesta. This study provides ways to leverage the large geochemical database on HED meteorites as a tool for interpreting chemical analyses by GRaND of mapped units on the surface of Vesta.

Usui, T.↗

Validation of ICESat-2 ATLAS Bathymetry and Analysis of ATLAS’s Bathymetric Mapping Performance

NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched in September, 2018. The satellite carries a single instrument, ATLAS (Advanced Topographic Laser Altimeter System), a green wavelength, photon-counting lidar, enabling global measurement and monitoring of elevation with a primary focus on the cryosphere. Although bathymetric mapping was not one of the design goals for ATLAS, pre-launch work by our research team showed the potential to map bathymetry with ICESat-2, using data from MABEL (Multiple Altimeter Beam Experimental Lidar), NASA’s high-altitude airborne ATLAS emulator, and adapting the laser-radar equation for ATLAS specific parameters. However, many of the sensor variables were only approximations, which limited a full assessment of the bathymetric mapping capabilities of ICESat-2 during pre-launch studies. Following the successful launch, preliminary analyses of the geolocated photon returns have been conducted for a number of coastal sites, revealing several salient examples of seafloor detection in water depths of up to ~40 m. The geolocated seafloor photon returns cannot be taken as bathymetric measurements, however, since the algorithm used to generate them is not designed to account for the refraction that occurs at the air–water interface or the corresponding change in the speed of light in the water column. This paper presents the first early on-orbit validation of ICESat-2 bathymetry and quantification of the bathymetric mapping performance of ATLAS using data acquired over St. Thomas, U.S. Virgin Islands. A refraction correction, developed and tested in this work, is applied, after which the ICESat-2 bathymetry is compared against high-accuracy airborne topo-bathymetric lidar reference data collected by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). The results show agreement to within 0.43—0.60 m root mean square error (RMSE) over 1 m grid resolution for these early on-orbit data. Refraction-corrected bottom return photons are then inspected for four coastal locations around the globe in relation to Visible Infrared Imaging Radiometer Suite (VIIRS) K(d)(490) data to empirically determine the maximum depth mapping capability of ATLAS as a function of water clarity. It is demonstrated that ATLAS has a maximum depth mapping capability of nearly 1 Secchi in depth for water depths up to 38 m and K(d)(490) in the range of 0.05–0.12 per m. Collectively, these results indicate the great potential for bathymetric mapping with ICESat-2, offering a promising new tool to assist in filling the global void in nearshore bathymetry.

ICESat-2↗

Assessing Sediment Inputs into the Shoshone River in Wyoming to Determine Areas for Protection and Restoration Practices

In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and killing thousands of fish. This release greatly concerned the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming-Montana Water Science Center, this multipart project illustrated the application of high-resolution satellite imagery and hydrological modeling techniques to identify major tributaries contributing to sediment influxes into the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. The team used PlanetScope and Sentinel-2 Multi-Spectral Instrument (MSI) satellite images to assess changes in the surface reflectance of the river in response to precipitation events. To determine these storm events, the team selected dates of interest using Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) and gauge precipitation data from the Global Historical Climatology Network Daily (GHCNd). The continuation of this research further quantified sediment influx in the Shoshone River following snowfall and melt events using the Soil & Water Assessment Tool (SWAT). The precipitation analysis and sediment contribution maps helped the partner organizations prioritize their current decision making and best management practices to specific sites along the river. The results demonstrated the feasibility of using PlanetScope data for categorizing sediment in the Shoshone River.

Caroline Williams↗

Implementation Plan for a NASA Integrated Lunar Science Strategy in the Artemis Era

This Implementation Plan provides a snapshot of NASA’s plans to implement the strategy recommended in OWL and to address the M2M objectives relevant to lunar science. The word “integrated” in the title refers to integrating the capabilities and new opportunities afforded by Artemis and CLPS alongside more traditional mechanisms such as The Discovery and New Frontiers Programs and various Research and Analysis (R&A) elements to achieve our lunar science objectives. It is an opportunity to present the full scope of tools currently available to NASA and how they map to high-priority lunar science that can be accomplished on and at the Moon. It is also an opportunity to build a plan for future NASA-led, lunar focused science and exploration activities that is flexible and can be adapted to a changing landscape (i.e., capability growth, priority evolution, and budgetary fluctuation).

Moon↗

Basin-wide gradients in dolomite d26Mg and 87Sr/86Sr identify the structural centre of the Williston Basin as a source of magnesium for dolomitization of the Middle Devonian Winnipegosis Formation

Dolomitized carbonates in the Williston Basin are common below the Middle Devonian Prairie Evaporite Formation, indicating a plausible role for brine-reflux as the source of Mg for dolomitization. However, the Lower Member Winnipegosis Formation, which directly underlies the evaporite sequence, exhibits dolomite 87Sr/86Sr ratios that are higher than expected for Middle Devonian seawater, instead suggesting that the dolomitizing fluids ascended from the deep basin where present-day formation waters are known to be more radiogenic. This interpretation is supported in this study by Mg isotope data showing a basin-scale gradient of increasing d26Mg values from the deep center (–2.03‰) to the edge (–1.34‰) of the Williston Basin along the lower Member Winnipegosis bed. Dolomite favors light isotopes of Mg when it forms, thus driving dolomitizing solutions, and the produced dolomite, towards heavier isotopic compositions in the direction of fluid flow. However, dolomite is also Mg-deficient when it forms, and its initial Mg isotope composition is susceptible to alteration by fluid-rock interactions occurring later in the depositional history of the deposit. We argue that the Mg isotope gradient in the Lower Member Winnipegosis was created by an ascending flow of isotopically light Mg-bearing fluid that differentially altered an earlier formed brine-reflux dolomite, with more alteration occurring deeper in the basin and less towards to edges. Alteration of pre-existing dolomite by an Mg isotope exchange mechanism requires large supplies of Mg. This fact, and the direction of fluid flow point to the underlying crystalline basement as an important Mg source for dolomitization in the Williston Basin. We speculate that ultramafic rocks supplied the Mg when they were hydrothermally altered during an anomalous heating event that affected the Williston Basin in the Late Devonian / Early Carboniferous. Seismic pumping drove these fluids upwards through fracture networks in the crust, and eventually into the deep center of the Williston Basin along vertically-oriented down-to-the-basement faults, pressuring deep aquifers like the Winnipegosis, which resulted in fluids migrating up the stratigraphic dip of the beds towards the edges of the basin. Plotting and contouring the dolomite d26Mg data on a map of the Williston Basin reveals the pathways taken by the migrating fluids. One prominent pathway extending outwards from the center of the basin towards the northeast bears a strong resemblance to petroleum migration fairways deduced for the underlying Late Ordovician Red River Formation. This study demonstrates that Mg isotopic mapping of large dolomite bodies is a useful tool for deciphering fluid flow histories in sedimentary basins and may assist in locating migrated petroleum and Mississippi Valley Type ore deposits.

Magnesium Isotopes, Strontium Isotopes, Dolomitiza↗

Resource Prospector Instrumentation for Lunar Volatiles Prospecting, Sample Acquisition and Processing

Data gathered from lunar missions within the last two decades have significantly enhanced our understanding of the volatile resources available on the lunar surface, specifically focusing on the polar regions. Several orbiting missions such as Clementine and Lunar Prospector have suggested the presence of volatile ices and enhanced hydrogen concentrations in the permanently shadowed regions of the moon. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission was the first to provide direct measurement of water ice in a permanently shadowed region. These missions with other orbiting assets have laid the groundwork for the next step in the exploration of the lunar surface; providing ground truth data of the volatiles by mapping the distribution and processing lunar regolith for resource extraction. This next step is the robotic mission Resource Prospector (RP). Resource Prospector is a lunar mission to investigate 'strategic knowledge gaps' (SKGs) for in-situ resource utilization (ISRU). The mission is proposed to land in the lunar south pole near a permanently shadowed crater. The landing site will be determined by the science team with input from broader international community as being near traversable landscape that has a high potential of containing elevated concentrations of volatiles such as water while maximizing mission duration. A rover will host the Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) payload for resource mapping and processing. The science instruments on the payload include a 1-meter drill, neutron spectrometer, a near infrared spectrometer, an operations camera, and a reactor with a gas chromatograph-mass spectrometer for volatile analysis. After the RP lander safely delivers the rover to the lunar surface, the science team will guide the rover team on the first traverse plan. The neutron spectrometer (NS) and near infrared (NIR) spectrometer instruments will be used as prospecting tools to guide the traverse path. The NS will map the water-equivalent hydrogen concentration as low as 0.5% by weight to an 80 centimeter depth as the rover traverses the lunar landscape. The NIR spectrometer will measure surficial H2O/OH as well as general mineralogy. When the prospecting instruments identify a potential volatile-rich area during the course of a traverse, the prospect is then mapped out and the most promising location identified. An augering drill capable of sampling to a depth of 100 centimeters will excavate regolith for analysis. A quick assay of the drill cuttings will be made using an operations camera and NIR spectrometer. With the water depth confirmed by this first auguring activity, a regolith sample may be extracted for processing. The drill will deliver the regolith sample to a crucible that will be sealed and heated. Evolved volatiles will be measured by a gas chromatograph-mass spectrometer and the water will be captured and photographed. RP is a solar powered mission, which given the polar location translates to a relatively short mission duration on the order of 4-15 days. This short mission duration drives the concept of operations, instrumentation, and data analysis towards critical real time analysis and decision support. Previous payload field tests have increased the fidelity of the hardware, software, and mission operations. Current activities include a mission level field test to optimize interfaces between the payload and rover as well as better understand the interaction of the science and rover teams during the mission timeline. This paper will include the current status of the science instruments on the payload as well as the integrated field test occurring in fall of 2015. The concept of operations will be discussed, including the real time science and engineering decision-making process based on the critical data from the instrumentation. The path to flight will be discussed with the approach to this ambitious low cost mission.

ISRU↗

Computing Sparse Tensor Decompositions via Chapel and C++/MPI Interoperability without Intermediate I/O

We extend an existing approach for efficient use of shared mapped memory across Chapel and C++ for graph data stored as 1-D arrays to sparse tensor data stored using a combination of 2-D and 1-D arrays. We describe the specific extensions that provide use of shared mapped memory tensor data for a particular C++ tensor decomposition tool called GentenMPI. We then demonstrate our approach on several real-world datasets, providing timing results that illustrate minimal overhead incurred using this approach. Finally, we extend our work to improve memory usage and provide convenient random access to sparse shared mapped memory tensor elements in Chapel, while still being capable of leveraging high performance implementations of tensor algorithms in C++.

97 MATHEMATICS AND COMPUTING↗

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗