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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Dating native gold by noble gas analyses

Our recent work on He, Ne, and Ar in Alpine gold samples has demonstrated that gold is extremely retentive for He and could thus, in principle, be used for U/Th-He-4 dating. For vein-type gold from Brusson, Northern Italy, we derived a U/Th-He-4 age of 36 Ma, in agreement with the K-Ar formation age of associated muscovites and biotites. However, in placer gold from the Napf area, Central Switzerland, we observed large excesses of both He-4 and radiogenic Ar-40 (Ar-40 sub rad, defined as Ar-40-295.5-Ar-.36). The gas release systematics indicate two distinct noble gas components, one of which is released below about 800 C and the other one at the melting point of gold (1064 C). We now present results of He and Xe measurements in a 1 g placer gold sample from the river Kruempelgraben, as well as He and Ar data for Brusson vein-type gold and for gold from the Lily Gold Mine, South Africa. We calculate reasonable U/Th-He-4 as well as U-Xe ages based on those gases which are released at approximately 800 C. Probably the low-temperature components represent in-situ-produced radiogenic He and fission Xe, whereas the gases evolving when gold melts have been trapped during gold formation. Therefore, only the low-temperature components are relevant for dating purposes.

Niedermann, S.↗
NASA NTRS2002

Continuing Development of a Collaborative Plan to Further Engage South Dakota in NASA's Earth Science Enterprise

An ongoing set of research planning activities have occurred in South Dakota as a consequence of the past two years of NASA-EPSCoR Preparation Grants. During this time a group of approximately 60 scientists, engineers, and university administrators in South Dakota have been directly involved as "theme team" members in a series of five all-day meetings to identify the research and technological priorities that are consistent both with NASA-ESE's interests and the State's expertise. Institutions represented within the group's membership include: South Dakota School of Mines & Technology, South Dakota State University, Augustana College, University of South Dakota, USGS EROS Data Center, Si ranks College, Santa Gleska University, Sisseton Wahpeton Community College, USGS Water Resources Division, US National Weather Service, and the SD Department of Environment & Natural Resources. Many of these organizations are also members and affiliates of the SD Space Grant Consortium. The evolving plan has been guided by the following desirable actions: 1. To establish new contacts and strengthen existing linkages with NASA Centers, relevant NASA researchers, and key personnel at the USGS EROS Data Center. 2. To promote participation from the State's major research institutions, State agencies, and relevant businesses in South Dakota that are interested in strengthening our scientific and technological enterprises. 3. To develop the State's scientific talent and infrastructure for enhanced competitiveness in research, development, and technology-based economic development. 4. To encourage greater participation by under represented groups, especially Native Americans, in scientific education and research. 5. To build greater public and political support in South Dakota for the overall science, engineering, and technology enterprise. 6. To communicate the benefits of current and future NASA programs to the progress and development of South Dakota, the Northern Great Plains Region, and the Nation.

Farwell, Sherry O.↗
NASA NTRS2020

A Fresh Look at the Stratigraphy of Northern Australe

The roughly circular collection of mare deposits centered at ~38.9°S, 93°E is often re- ferred to as Mare Australe. It is located outside of the Procellarum KREEP Terrain. The circular arrangement of Australe’s mare patches has suggested an ancient, heavily degraded or relaxed impact basin roughly 900 km in diameter. The mare deposits are generally thought to have erupted into smaller post- basin craters. The type, volume, and distribution of mare eruptions potentially resembles the early stages of basin-filling mare events, but which are preserved in Australe and some farside locations. Gravity data suggest that if there was a basin, it is much smaller than originally proposed (now ~600 km) and located in the northern part of Mare Australe, between Humboldt, Milne, and Jenner craters. As a whole, Mare Australe lacks the topography typically associated with a basin; however, northern Australe has a slight topographic depression that roughly corresponds to the basin-like Bouguer gravity signature in the same area. The compositions exposed in Humboldt crater suggest that a preexisting basin might have excavated deeper crustal material. However, the underlying cause of the circularity of Mare Australe’s deposits, particularly those extending outside of the potential impact basin setting, is not yet understood. Thus, Australe may preserve fundamental information about mare volcanism potentially uncoupled from basin formation and structure. The objectives of this study are to use new high- resolution data (images, gravity, topography, and com- position) to reassess Australe’s mare deposits, deter- mine the timing and style of volcanism, identify discrete basalt deposits, and to further characterize the evolution of magmatism and subsurface structure in this area. Here, we focus on the northern Australe deposits (between Humboldt, Jenner, and Milne). As originally noted by Whitford-Stark (1979), Humboldt crater and its ejecta make an excellent stratigraphic marker that can be traced across much of the Australe region. The ejecta serves as a stratigraphic constraint for absolute model ages (AMAs) derived from crater size-frequency distributions (CSFDs).

Stopar, J. D.↗
DOE OSTI2021

Convolutional Neural Networks for the CHIPS Neutrino Detector R&D Project.

The CHerenkov detectors In mine PitS (Chips) neutrino detector R&D project aims to develop novel strategies and technologies for very large yet ‘cheap as chips’ water Cherenkov neutrino detectors. Via deployment in a body of water, use of commercially available components, and instrumentation coverage optimisation for the study of exclusively accelerator beam neutrinos, Chips will enable megaton scale detectors to become a reality at the cost of $200k-$300k per kt of sensitive mass. During the summer of 2019 a prototype Chips detector, Chips-5, was deployed into the Wentworth 2W disused mine pit in northern Minnesota, 7 mrad off the NuMI beam axis. A novel data acquisition system was introduced using cheap single-board computers and open-source software. This work presents a novel approach to water Cherenkov neutrino detector event reconstruction and classification. Three forms of a Convolutional Neural Network, a type of deep learning algorithm, have been trained to reject cosmic muon events, classify beam events, and estimate neutrino energies, all using only the raw detector event as input. When evaluated on the expected distribution of Chips-5 events, this new approach is shown to be robust and explainable as well as providing a significant performance increase over the standard likelihood-based reconstruction and simple neural network classification. Promisingly, the performance presented here is comparable to the more complex (and expensive) neutrino oscillation experiments within the field.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1999

Using a Genetic Algorithm to Model Broadband Regional Waveforms for Crustal Structure in the Western United States

In this study, we analyze regional seismograms to obtain the crustal structure in the eastern Great Basin and western Colorado plateau. Adopting a for- ward-modeling approach, we develop a genetic algorithm (GA) based parameter search technique to constrain the one-dimensional crustal structure in these regions. The data are broadband three-component seismograms recorded at the 1994-95 IRIS PASSCAL Colorado Plateau to Great Basin experiment (CPGB) stations and supplemented by data from U.S. National Seismic Network (USNSN) stations in Utah and Nevada. We use the southwestern Wyoming mine collapse event (M(sub b) = 5.2) that occurred on 3 February 1995 as the seismic source. We model the regional seismograms using a four-layer crustal model with constant layer parameters. Timing of teleseismic receiver functions at CPGB stations are added as an additional constraint in the modeling. GA allows us to efficiently search the model space. A carefully chosen fitness function and a windowing scheme are added to the algorithm to prevent search stagnation. The technique is tested with synthetic data, both with and without random Gaussian noise added to it. Several separate model searches are carried out to estimate the variability of the model parameters. The average Colorado plateau crustal structure is characterized by a 40-km-thick crust with velocity increases at depths of about 10 and 25 km and a fast lower crust while the Great Basin has approximately 35- km-thick crust and a 2.9-km-thick sedimentary layer.

Bhattacharyya, Joydeep↗
DOE OSTI2025

STILGAR: Subsurface Models for Graymont Pleasant Gap Mine

The detection, location, and monitoring of underground structures are of great importance to national and global security. Tunnels and voids generate seismic signatures detectable at the surface, but using non-invasive seismic data to image near-surface presents several challenges in real-world applications. In this report, we describe the use of a dense surface seismic deployment to generate subsurface models of the Graymont Pleasant Gap mine - a single-layer mine with a complex structure embedded in a high-velocity P-wave limestone bedrock. Our approach consists of three key methods. We use P-wave arrival times from local blast events to perform a tomography inversion with the tomoTD method, constructing a P-wave velocity model of the subsurface. We model the layer above the mine using Rayleigh wave ellipticity and inversion techniques. We leverage ongoing anthropogenic activities to identify and locate noise sources both on the surface and within the subsurface. With this integrated approach we aim to overcome the challenges and enhance our ability to non-invasively characterize underground structures, contributing to improved seismic monitoring techniques.

58 GEOSCIENCES↗
DOE OSTI2020

Feature Engineering and Process Mining to Enable Hazard Detection in Health Information Technology

Motivation for this work originates from a recognized need for developing data-driven approaches through analysis of complex electronic health records. Specifically, we aim to enhance the reliability of health information technology (HIT) systems by detection of plausible HIT hazards in clinical order transactions. In the absence of well-defined event logs in corporate data warehouses, our proposed approach identifies relevant timestamped data fields that could indicate transactions in the clinical order life cycle generating raw event sequences. Subsequently, we adopt state transitions of the OASIS Human Task standard to map the raw event sequences and simplify the complex process that clinical radiology orders go through. We describe how the current approach provides the potential to investigate areas of improvement and potential hazards in HIT systems. The discussion concludes with a use case and opportunities for future applications.

Ozmen, Ozgur↗
DOE OSTI2020

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
DOE OSTI2021

LL18-Signal Analysis-NDD2Ad (Final Report)

Under favorable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially-distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection, and scaling with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning, and possible application to studies of repeating events in induced, volcanic, and glacial seismicity. Our results place limits on the widely-held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
NASA NTRS1983

New applications for phosphoric acid fuel cells

New applications for phosphoric acid fuel cells were identified and evaluated. Candidates considered included all possibilities except grid connected electric utility applications, on site total energy systems, industrial cogeneration, opportunistic use of waste hydrogen, space and military applications, and applications smaller than 10 kW. Applications identified were screened, with the most promising subjected to technical and economic evaluation using a fuel cell and conventional power system data base developed in the study. The most promising applications appear to be the underground mine locomotive and the railroad locomotive. Also interesting are power for robotic submersibles and Arctic villages. The mine locomotive is particularly attractive since it is expected that the fuel cell could command a very high price and still be competitive with the conventionally used battery system. The railroad locomotive's attractiveness results from the (smaller) premium price which the fuel cell could command over the conventional diesel electric system based on its superior fuel efficiency, and on the large size of this market and the accompanying opportunities for manufacturing economy.

Stickles, R. P.↗
NASA NTRS1981

Steam Turbines

Turbonetics Energy, Inc.'s steam turbines are used as power generating systems in the oil and gas, chemical, pharmaceuticals, metals and mining, and pulp and paper industries. The Turbonetics line benefited from use of NASA research data on radial inflow steam turbines and from company contact with personnel of Lewis Research Center, also use of Lewis-developed computer programs to determine performance characteristics of turbines.

Source record↗
NASA NTRS2002

Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering

This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.

Tilton, James C.↗
DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Analyses to Inform Equitable Investment Prioritization

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where indicators of disadvantaged communities intersect with high generation potential from cost- effective renewable energy opportunities. This presentation highlights the geospatial intersection of the technical potential and levelized cost of energy for three renewable technologies (residential solar, utility solar, and land-based wind) and three sociodemographic metrics (energy burden, unemployment, and employment in mining, quarrying, and oil and gas extraction). This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

disadvantaged communities↗
DOE OSTI2024

Rare earth element enrichment in coal and coal-adjacent strata of the Uinta Region, Utah and Colorado

This study aims to quantify rare earth element enrichment within coal and coal-adjacent strata in the Uinta Region of central Utah and western Colorado. Rare earth elements are a subset of critical minerals as defined by the U.S. Geological Survey. These elements are used for a wide variety of applications, including renewable energy technology in the transition toward carbon-neutral energy. While rare earth element enrichment has been associated with Appalachian coals, there has been a more limited evaluation of western U.S. coals. Here, samples from six active mines, four idle/historical mines, four mine waste piles, and seven stratigraphically complete cores within the Uinta Region were geochemically evaluated using portable X-ray fluorescence ( n = 3,113) and inductively coupled plasma-mass spectrometry ( n = 145) elemental analytical methods. Results suggest that 24%–45% of stratigraphically coal-adjacent carbonaceous shale and siltstone units show rare earth element enrichment (>200 ppm), as do 100% of sampled igneous material. A small subset (5%–8%) of coal samples display rare earth element enrichment, specifically in cases containing volcanic ash. This study proposes two multi-step depositional and diagenetic models to explain the enrichment process, requiring the emplacement and mobilization of rare earth element source material due to hydrothermal and other external influences. Historical geochemical evaluations of Uinta Region coal and coal-adjacent data are sparse, emphasizing the statistical significance of this research. These results support the utilization of active mines and coal processing waste piles for the future of domestic rare earth element extraction, offering economic and environmental solutions to pressing global demands.

Coe, Haley H.↗
NASA NTRS1992

Lunar Resource Assessment: an Industry Perspective

The goals of the U.S. space program are to return to the Moon, establish a base, and continue onward to Mars. To accomplish this in a relatively short time frame and to avoid the high costs of transporting materials from the Earth, resources on the Moon will need to be mined. Oxygen will be one of the most important resources, to be used as a rocket propellant and for life support. Ilmenite and lunar regolith have both been considered as ores for the production of oxygen. Resource production on the Moon will be a very important part of the U.S. space program. To produce resources we must explore to identify the location of ore or feedback and calculate the surface and underground reserves. Preliminary resource production tests will provide the information that can be used in final plant design. Bechtel Corporation's experience in terrestrial engineering and construction has led to an interest in lunar resource assessment leading to the construction of production facilities on the Moon. There is an intimate link between adequate resource assessment to define feedstock quantity and quality, material processing requirements, and the successful production of lunar oxygen. Although lunar resource assessment is often viewed as a research process, the engineering and production aspects are very important to consider. Resource production often requires the acquisition of different types, scales, or resolutions of data than that needed for research, and it is needed early in the exploration process. An adequate assessment of the grade, areal extent, and depth distribution of the resources is a prerequisite to mining. The need for a satisfactory resource exploration program using remote sensing techniques, field sampling, and chemical and physical analysis is emphasized. These data can be used to define the ore for oxygen production and the mining, processing facilities, and equipment required.

Feldman, S. C.↗
DOE OSTI2022

Auto-generating databases of Yield Strength and Grain Size using ChemDataExtractor

Abstract The emerging field of material-based data science requires information-rich databases to generate useful results which are currently sparse in the stress engineering domain. To this end, this study uses the’materials-aware’ text-mining toolkit, ChemDataExtractor, to auto-generate databases of yield-strength and grain-size values by extracting such information from the literature. The precision of the extracted data is 83.0% for yield strength and 78.8% for grain size. The automatically-extracted data were organised into four databases: a Yield Strength, Grain Size, Engineering-Ready Yield Strength and Combined database. For further validation of the databases, the Combined database was used to plot the Hall-Petch relationship for, the alloy, AZ31, and similar results to the literature were found, demonstrating how one can make use of these automatically-extracted datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗
DOE OSTI2020

Detecting an underground tunnel by applying joint traveltime and waveform inversion

Underground tunnel and void detection is a challenging geophysical problem, and many methods have been proposed. Seismic techniques are promising because of the large seismic velocity contrasts between the air-filled void and the surrounding sediment and concrete. We apply a joint seismic traveltime and waveform inversion method to image a buried tunnel with concrete walls and a void space inside. The joint inversion images the top of the concrete tunnel as a high-velocity anomaly and the void space as a low-velocity anomaly. The location of the velocity anomalies predicted by the method agrees with the known location of the tunnel. As a comparison, the stand-alone full waveform inversion is also applied to the data. The first-arrival traveltime tomography shows weak nonlinearity but fails to image the hidden low-velocity layer. Full waveform inversion is able to image complex near-surface structures, but fitting waveforms may not honor the traveltime fit, especially when the data contain noise. Synthetic and real data tests show that the joint inversion method retains the advantages of both traveltime inversion and full waveform inversion and overcomes their respective drawbacks at the same time. The field example shows the joint inversion provides a better reconstruction of the high-velocity feature representing the top of the concrete wall in terms of its magnitude and location.

58 GEOSCIENCES↗