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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modeling regional precipitation over the Indus River basin of Pakistan using statistical downscaling

Complex processes govern spatiotemporal distribution of precipitation within the high-mountainous headwater regions (commonly known as the upper Indus basin (UIB)), of the Indus River basin of Pakistan. Reliable precipitation simulations particularly over the UIB present a major scientific challenge due to regional complexity and inadequate observational coverage. Here, we present a statistical downscaling approach to model observed precipitation of the entire Indus basin, with a focus on UIB within available data constraints. Taking advantage of recent high altitude (HA) observatories, we perform precipitation regionalization using K-means cluster analysis to demonstrate effectiveness of low-altitude stations to provide useful precipitation inferences over more uncertain and hydrologically important HA of the UIB. We further employ generalized linear models (GLM) with gamma and Tweedie distributions to identify major dynamic and thermodynamic drivers from a reanalysis dataset within a robust cross-validation framework that explain observed spatiotemporal precipitation patterns across the Indus basin. Final statistical models demonstrate higher predictability to resolve precipitation variability over wetter southern Himalayans and different lower Indus regions, by mainly using different dynamic predictors. The modeling framework also shows an adequate performance over more complex and uncertain trans-Himalayans and the northwestern regions of the UIB, particularly during the seasons dominated by the westerly circulations. However, the cryosphere-dominated trans-Himalayan regions, which largely govern the basin hydrology, require relatively complex models that contain dynamic and thermodynamic circulations. Furthermore, we also analyzed relevant atmospheric circulations during precipitation anomalies over the UIB, to evaluate physical consistency of the statistical models, as an additional measure of reliability. Overall, our results suggest that such circulation-based statistical downscaling has the potential to improve our understanding towards distinct features of the regional-scale precipitation across the upper and lower Indus basin. Additionally, such understanding should help to assess the response of this complex, data-scarce, and climate-sensitive river basin amid future climatic changes, to serve communal and scientific interests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

New insights into Mn 2+ and Mg 2+ inhibition of calcite growth

Impurity ion and isotope partitioning into carbonate minerals provide a window into the molecular processes occurring at the fluid-mineral interface during crystal growth. Here, we employ calcium isotope fractionation together with process-based modeling to elucidate the mechanisms by which two divalent cations with starkly contrasting compatibility, magnesium and manganese, inhibit calcite growth and incorporate into the mineral lattice. Calcite growth inhibition by Mg 2+ is log-linear and K Mg is on the order of 0.02–0.03 throughout the range of {Mg 2+ }/{Ca 2+ } studied here (0.01–2.6). Mn 2+ exhibits much stronger log-linear growth rate inhibition at low Mn 2+ concentrations (fluid {Mn 2+ }/{Ca 2+ } = 0.001–0.02). Mn 2+ is readily incorporated into the calcite lattice to form a calcite-rhodochrosite solid solution, with large partition coefficients (K Mn 4.6–15.6) inversely correlated to growth rate. For both Mn 2+ and Mg 2+ , calcium isotope fractionation is found to be invariant with {Me 2+ }/{Ca 2+ } despite more than an order of magnitude decline in growth rate. This invariant Δ 44/40 Ca suggests that the presence of Mn 2 + or Mg 2+ does not significantly change the relative rates of Ca 2+ attachment and detachment at kink sites during growth, indicative of a dominantly kink blocking inhibition mechanism. Because the partitioning behavior dictates that Mn 2+ must attach to the surface significantly faster than Ca 2+ , attachment of Mn 2+ is likely to be as a non-monomer species such as an ion pair or possibly a larger polynuclear cluster. We propose that calcite growth rate inhibition by Mn is determined by the kinetics of carbonate attachment at Mn-occupied kink sites, potentially due to slow re-orientation kinetics of carbonate ions that have formed an inner-sphere complex with Mn 2+ at the surface but must reorient to incorporate into the lattice. We demonstrate that patterns in Mg 2+ partitioning and inhibition behavior are broadly consistent with growth inhibition driven by slow Mg 2+ -aquo complex dehydration relative to Ca 2+ but argue that this mechanism likely represents one endmember scenario, seen in Mg-calcite growth at low supersaturations and net precipitation rates. During growth at faster net precipitation rates, some portion of Mg 2+ is likely incorporated as a partially hydrated or otherwise complexed species, but calcite growth remains significantly inhibited by the kinetics of CO 3 2- attachment at Mg 2+ kink sites. These findings suggest a hybrid classical/nonclassical growth mechanism whereby Ca 2+ incorporates largely as a free ion at kink sites while Mn 2+ and some portion of Mg 2+ are incorporated via non-monomer attachment. This pattern may be generalizable; trace constituent cations with aquo-complex desolvation rates significantly slower than the mineral growth rate preferentially incorporate as a non-monomer species during otherwise classical crystal growth.

58 GEOSCIENCES↗
DOE OSTI2024

Mitigation for Removal of Building 01-103 in the Area 1 Subdock, Nevada National Security Site, Nye County, Nevada

Building 01-103, the Drill Bit Repair Building was originally recorded as SHPO Resource No. B18848 in 2020 during an architectural survey of the Area 1 Subdock (Collins et al. 2022). It was recommended individually eligible for listing in the NRHP under Criteria A and C and contributing to the significance of the Area 1 Subdock Historic District. The SHPO concurred with these determinations in a letter dated April 29, 2022 (Reed 2022). The Drill Bit Repair Building retains all seven aspects of integrity. The location, materials, workmanship, feeling, and association have not changed since its original construction. The design was modified slightly in 1996 with the addition of a removable and non-destructive chain-link fence. Nearby buildings 01-101 and 01-102 were removed (Collins and Menocal 2020) but the other buildings and storage yards remain. Therefore, the integrity of setting has been changed, but not to the degree that the building no longer conveys its significance (see Figures 4 and 5 for comparison). Building 01-103 was constructed in 1985 to coincide with the relocation of the Area 3 Subdock to Area 1. The design for the new Subdock provided a centralized cluster of buildings surrounded by two large storage yards. The buildings included administrative and engineering office space, warehouses, a radiograph building, and Building 01-103 as the drill bit maintenance and repair building, among others. The Drill Bit Repair Building was critical to the success of underground nuclear testing and is eligible under Criterion A for its contribution to broad patterns of history by maintaining specially designed equipment for underground nuclear testing at the NNSS. It is also eligible under Criterion C as it is the only recorded example of a facility built specifically for the maintenance of big-hole drill bits on the NNSS. As it retains both significance and integrity, it remains individually eligible under Criteria A and C. In addition to its individual significance, the Drill Bit Repair Building also contributes to the significance of the Area 1 Subdock Historic District as a representative of a big-hole drilling support facility necessary for underground nuclear testing. The building and the equipment therein were designed specifically for testing at the NNSS, where much of the early technology and methods for big-hole drilling were developed. Its removal will result in not only the demolition of a contributing element but also a change in the physical features of the district’s setting that contribute to its historic significance. The change in setting will diminish the district’s integrity. However, the district still contains numerous examples of other buildings constructed for the purpose of supporting big-hole drilling and remains eligible under Criteria A and C.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

A Multiwavelength Study of the Starburst Galaxy NGC 7771

We present a multiwavelength study of the interacting starburst galaxy NGC 7771, including new optical and ultra-violet spectra and a previously unpublished soft X-ray ROSAT image and spectrum. The far-infrared, radio, and X-ray fluxes suggest that a massive burst of star-formation is currently in progress but the small equivalent width of the Balmer emission lines (equivalent width H(alpha approximately equals 100 A), the weak UV flux, the low abundance of ionised oxygen, and the shape of the optical spectrum lead us to conclude that there are few 0 stars. This might normally suggest that star-formation has ceased but the galaxy's barred gravitational potential and large gas reserves imply that this should not be so, and we therefore consider other explanations. We argue that the observations cannot be due to effects of geometry, density bounded nebulae, or dust within the nebulae, and conclude that a truncated IMF is required. The dwarf galaxy NGC 7770 appears to be in the initial stages of a merger with NGC 7771, and the resulting tidal perturbations may have induced the apparent two-armed spiral pattern, and driven a substantial fraction of the disk gas inwards. The presence of a bulge in NGC 7771 may be moderating the starburst so that, while still occuring on a large scale with a supernova rate of 0.8-1/yr, it is less violent and the IMF has a relatively low upper mass limit. We find that there is a cluster of stars obscuring part of the starburst region, and we offer an explanation of its origin.

Davies, Richard I.↗
NASA NTRS2010

Comparisons of Supergranule Properties from SDO/HMI with Other Datasets

While supergranules, a component of solar convection, have been well studied through the use of Dopplergrams, other datasets also exhibit these features. Quiet Sun magnetograms show local magnetic field elements distributed around the boundaries of supergranule cells, notably clustering at the common apex points of adjacent cells, while more solid cellular features are seen near active regions. Ca II K images are notable for exhibiting the chromospheric network representing a cellular distribution of local magnetic field lines across the solar disk that coincides with supergranulation boundaries. Measurements at 304 A further above the solar surface also show a similar pattern to the chromospheric network, but the boundaries are more nebulous in nature. While previous observations of these different solar features were obtained with a variety of instruments, SDO provides a single platform, from which the relevant data products at a high cadence and high-definition image quality are delivered. The images may also be cross-referenced due to their coincidental time of observation. We present images of these different solar features from HMI & AIA and use them to make composite images of supergranules at different atmospheric layers in which they manifest. We also compare each data product to equivalent data from previous observations, for example HMI magnetograms with those from MDI.

Pesnell, William Dean↗
DOE OSTI2025

Development of thin-gap GEM- μ RWELL hybrid detectors

Micro Pattern Gaseous Detectors (MPGDs) are used for tracking in High Energy Physics and Nuclear Physics because of their large area, excellent spatial resolution capabilities and low cost. However, for high energy charged particles impacting at a large angle with respect to the axis perpendicular to detector plane, the spatial resolution degrades significantly because of the long trail of ionization charges produced in clusters all along the track in the drift region of the detector. The long ionization charge trail results in registering hits from large number of strips in the readout plane which makes it challenging to precisely reconstruct the particle’s position using simple center of gravity algorithm. As a result, the larger the drift gap, the more severe the deterioration of spatial resolution for inclined tracks. For the same reason, the position resolution is also severely degraded in a large magnetic field, where the Lorentz E x B effect causes the ionization charges to follow a curved and longer path in the detector gas volume. In this paper, we report on the development of thin-gap MPGDs as a way to maintain excellent spatial resolution capabilities of MPGD detectors over a wide angular range of incoming particles. In a thin-gap MPGD, the thickness of the gas volume in the drift region is reduced from typically 3 mm to 1 mm or less. We present preliminary test beam results demonstrating the improvement in spatial resolution from 400 m with a standard 3 mm gap μ RWELL prototype to ~140 μ m with a double amplification GEM- μ RWELL thin-gap hybrid detector. Here, we also discuss the impact of a thin-gap drift volume on other aspects of the performance of MPGD technologies such as the efficiency and detector stability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2005

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies↗
NASA NTRS2011

Space Radiation Effects on Human Cells: Modeling DNA Breakage, DNA Damage Foci Distribution, Chromosomal Aberrations and Tissue Effects

Future long-tem space travel will face challenges from radiation concerns as the space environment poses health risk to humans in space from radiations with high biological efficiency and adverse post-flight long-term effects. Solar particles events may dramatically affect the crew performance, while Galactic Cosmic Rays will induce a chronic exposure to high-linear-energy-transfer (LET) particles. These types of radiation, not present on the ground level, can increase the probability of a fatal cancer later in astronaut life. No feasible shielding is possible from radiation in space, especially for the heavy ion component, as suggested solutions will require a dramatic increase in the mass of the mission. Our research group focuses on fundamental research and strategic analysis leading to better shielding design and to better understanding of the biological mechanisms of radiation damage. We present our recent effort to model DNA damage and tissue damage using computational models based on the physics of heavy ion radiation, DNA structure and DNA damage and repair in human cells. Our particular area of expertise include the clustered DNA damage from high-LET radiation, the visualization of DSBs (DNA double strand breaks) via DNA damage foci, image analysis and the statistics of the foci for different experimental situations, chromosomal aberration formation through DSB misrepair, the kinetics of DSB repair leading to a model-derived spectrum of chromosomal aberrations, and, finally, the simulation of human tissue and the pattern of apoptotic cell damage. This compendium of theoretical and experimental data sheds light on the complex nature of radiation interacting with human DNA, cells and tissues, which can lead to mutagenesis and carcinogenesis later in human life after the space mission.

Ponomarev, A. L.↗
DOE OSTI2020

Clustering-Based Predictive Analytics to Improve Scientific Data Discovery

Given the sheer volume of scientific data archived within the data-intensive projects at the US Department of Energy's Oak Ridge National Laboratory, finding precisely what data we are looking for may not be a trivial task; conversely, we may also miss a more prominent data product. To address such issues, we propose improving the data discovery system and using data analytics methods to comprehend what specific users might be interested in based on their physiological state, search patterns, and past data usage history. This work's primary goal is to prune the complexity, increase the visibility of popular data products, and direct users toward the data that best meet their needs. The proposed algorithm constructs a user profile based on the user's explicit or implicit interactions with the system, such as items they are currently looking at on-site and the key metadata mappings related to the data set. The pattern is then used to build a training data set, which will help find relevant data to recommend to the user.

Devarakonda, Ranjeet↗
NASA NTRS1983

Directivity of planar array feeds for satellite reflector applications

Array-fed reflector antennas are used extensively in today's contour and multiple beam satellite antennas. To determine the directivity of these antennas theoretically, the total radiated power of the array feed must be accurately computed. In this paper, a closed-form expression for the radiated power is obtained for arrays with the well-known (cos theta q-type element patterns. The formulation is general, and takes into account polarization, nonsymmetric E- and H-plane element patterns, nonuniform element spacings and arbitrary complex excitation coefficients. Selective numerical data are presented to demonstrate the usefulness of this result. Comparisons are made with the available results obtained using direct numerical integration techniques, and with other available data based on less general formulations. Excellent agreement is observed for all cases. In particular, data are presented on the directivity of seven-element cluster feeds used in multiple beam designs, and an array feed for producing a contour beam covering the United States Eastern Time Zone (ETZ).

Rahmat-Samii, Y.↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
NASA NTRS2004

Phylogenetic and physiological diversity of microorganisms isolated from a deep greenland glacier ice core

We studied a sample from the GISP 2 (Greenland Ice Sheet Project) ice core to determine the diversity and survival of microorganisms trapped in the ice at least 120,000 years ago. Previously, we examined the phylogenetic relationships among 16S ribosomal DNA (rDNA) sequences in a clone library obtained by PCR amplification from genomic DNA extracted from anaerobic enrichments. Here we report the isolation of nearly 800 aerobic organisms that were grouped by morphology and amplified rDNA restriction analysis patterns to select isolates for further study. The phylogenetic analyses of 56 representative rDNA sequences showed that the isolates belonged to four major phylogenetic groups: the high-G+C gram-positives, low-G+C gram-positives, Proteobacteria, and the Cytophaga-Flavobacterium-Bacteroides group. The most abundant and diverse isolates were within the high-G+C gram-positive cluster that had not been represented in the clone library. The Jukes-Cantor evolutionary distance matrix results suggested that at least 7 isolates represent new species within characterized genera and that 49 are different strains of known species. The isolates were further categorized based on the isolation conditions, temperature range for growth, enzyme activity, antibiotic resistance, presence of plasmids, and strain-specific genomic variations. A significant observation with implications for the development of novel and more effective cultivation methods was that preliminary incubation in anaerobic and aerobic liquid prior to plating on agar media greatly increased the recovery of CFU from the ice core sample.

Bacteria/classification/genetics/isolation & purif↗
NASA NTRS2005

Identification of a typical flight patterns

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous- valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding a typicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

Irving C Statler↗
NASA NTRS2005

Identification of atypical flight patterns

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

Statler, Irving C.↗
DOE OSTI2021

Analyzing acoustic emission data to identify cracking modes in cement paste using an artificial neural network

This research is focused on the identification of cracking mechanisms for cement paste using acoustic emission data, recorded from compression and notched four-point bending tests. A procedure is developed for analyzing the data by employing an agglomerative hierarchical clustering method, an artificial neural network, and a ray-tracing source location algorithm. An agglomerative hierarchical clustering method is utilized to cluster the AE data from a compression test using frequency-dependent features. A neural network is trained using the compression test data and applied to the AE data emitted during the four-point bending test. The clustered data from the four-point bending test is localized using a ray-tracing algorithm. Based on the occurrence and locations of the clustered events and signal feature analyses, potential cracking mechanisms are identified and assigned.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computational multiphysics modeling of radioactive aerosol deposition in diverse human respiratory tract geometries

The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2004

Chandra X-ray Observations of Young Clusters: Orion Flanking Fields Data - Volume II

We present results of Chandra observations of two flanking fields (FFs) in Orion, outside the Orion Nebula Cluster (ONC). The observations were taken with the ACIS-I camera with an exposure time of about 48 ks each field. We present a catalog of 417 sources, which includes X-ray luminosity, optical and infrared photometry, and X-ray variability information. We have found 91 variable sources, 33 of which have a flarelike light curve and 11 of which have a pattern of a steady increase or decrease over a 10 hr period. The optical and infrared photometry for the stars identified as X-ray sources are consistent with most of these objects being pre-main-sequence stars with ages younger than 10 Myr. We present evidence for an age difference among the X-ray-selected samples of NGC 2264, Orion FFs, and ONC, with NGC 2264 being the oldest and ONC being the youngest.

pre-main sequence↗