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At least 127 records · Page 7

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DOE OSTI2017

Role of the strange quark in the rho(770) meson

Recently, the GWU lattice group has evaluated high-precision phase-shift data for $\pi\pi$ scattering in the $I = 1$, $J = 1$ channel. Unitary Chiral Perturbation Theory describes these data well around the resonance region and for different pion masses. Moreover, it allows to extrapolate to the physical point and estimate the effect of the missing $K\bar{K}$ channel in the two-flavor lattice calculation. The absence of the strange quark in the lattice data leads to a lower $\rho$ mass, and the analysis with U$\chi$PT shows that the $K \bar{K}$ channel indeed pushes the $\pi\pi$-scattering phase shift upward, having a surprisingly large effect on the $\rho$-mass. The inelasticity is shown to be compatible with the experimental data. The analysis is then extended to all available two-flavor lattice simulations and similar mass shifts are observed. Chiral extrapolations of $N_f = 2 + 1$ lattice simulations for the $\rho(770)$ are also reported.

Molina Peralta, Raquel↗

DOE OSTI2021

The Ultra-High-Energy Source MGRO J1908+06

The TeV gamma-ray source MGRO J1908+06 is one of the highest-energy sources known, with observed emission by the High Altitude Water Cherenkov (HAWC) Observatory extending well past 100 TeV. The source exhibits both energy-dependent morphology and a spatially-dependent spectral index. The emission is likely to be dominantly leptonic, and associated with the radio-quiet PSR J1907+0602. However, one-population models do not describe the data well; a second particle population is needed to explain the shape of the spectral energy distribution at the highest energies. This component can be well-described by either leptonic or hadronic hypotheses. We discuss this feature and implications for detection by multi-wavelength and multi-messenger experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Basin and Petroleum System Modeling of Gas Hydrate Deposits in the Walker Ridge Area, Northern Gulf of Mexico - Poster

Poster presented by NETL at ICGH, 06/17 - Abstract: We are currently constructing an Earth model of the Terrebonne Basin for comprehensive 3D modeling. Well data and a high-quality 3D seismic survey underpin the geologic conditions for the model. Additional model constraints include basal heat flow, seafloor temperature, and paleowater depth through time. Our initial investigation comprises the development of a “pseudo” 2D model centered on the deep WR313 #001 well. We are using this test case to establish the workflow for integrating BPSM with gas hydrate analyses; this will eventually be applied to the entire mini-basin. A key aspect of investigating the gas hydrate system with BPSM is integrating it with the other active petroleum system(s) in the region, because the methane in hydrate deposits can derive from both biogenic and thermogenic sources. Some of the questions we may consider are: What is the history of these deposits with respect to the gas hydrate stability zone, recognizing that this area is not one characterized by simple continuous sedimentation and subsidence, but instead by periodic uplift, tilting, plate rotation, sea-level change, salt tectonics, and evolution of temperature gradients. In conclusion, BPSM has been called the ‘great integrator’ in petroleum exploration. Development of a BPSM model of gas hydrates in the Terrebonne Basin of the northern GoM will provide a vehicle within which to integrate other early exploration and assessment research being conducted on gas hydrates, such as in frontier areas like Japan, as a potential resource likely to provide many decades of energy if proven to be commercially producible

Dafov, Laura↗

DOE OSTI2018

Oklahoma Wellbore Rasters

Seven raster surfaces generated from wellbore information that are thought to influence fluid and or gas migration in the subsurface. Wellbore information was originally retrieved from the IHS Energy Group (current as of April 2015), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Processing of wellbore information into gridded cells was performed to provide a graphic solution to overcome the problem of displaying proprietary well data. No proprietary data are displayed or included in the cell maps. These rasters were developed to serve as inputs to the SIMPA (Spatially Weighted Multivariate Probabilistic Assessment) tool. Each raster surface is a derivative product of wellbore dataset. Each raster represents a single wellbore attribute or combination of attributes that speak to the following wellbore characteristics: number of recompletions, year spud, year abandoned, year completed, number of abandoned wells, hole direction, switch from production to injection. The original wellbore information, retrieved from the IHS Energy Group, are in the form of points – these derivative rasters aggregate point attributes to approximately 1,000-meter resolution grid cells. Each raster only includes cells that contain wellbores with the characteristics represented in each surface (i.e. if the wellbores in a given cell have no year abandoned data, the cell is not included in the raster). Since the raster cells combine data from multiple points in many cases, methods such as the average, minimum, and count are used to summarize the information in each cell. The specific operations used to develop each raster are detailed in its metadata.

Abandoned↗

NASA NTRS2020

Central Valley Water Resources II: Groundwater Sustainability Management Support in the California Central Valley using GRACE and InSAR Datasets

California’s Central Valley is one of the most productive agricultural regions in the United States, producing a fourth of the nation’s food supply. The water demand in this region is heavily dependent on groundwater resources, resulting in over pumping of aquifers at unsustainable rates during recent periods of severe drought. Over the past century, Central Valley aquifers have experienced a significant decline in groundwater levels, resulting in land subsidence and irreversible loss in groundwater storage. In 2014, the state enacted the Sustainable Groundwater Management Act, requiring high and medium priority subbasins to suspend overdraft and achieve sustainable levels of pumping and recharge by 2042.The California Department of Water Resources (DWR) oversees subbasin groundwater management; however, monitoring remains challenging due to sparse and inconsistent in situ data. To assist the DWR, this project developed a user-friendly executable application and an interactive visualization tool to quantify groundwater storage and land subsidence trends using remotely sensed and in situ data. The team utilized NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GRACE-FO), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) interferograms, and Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2) interferograms in conjunction with well and GPS measurements to analyze groundwater and subsidence trends. GRACE and well data returns produced a strong Pearson correlation of .84, while Sentinel-1 and GPS data returns produced a Pearson correlation of .41 over the entire Central Valley. These findings suggest remotely sensed GRACE and interferometric SAR data can be used in the absence of in situ data.

DEVELOP Project Summary↗

NASA NTRS2019

Test and Analysis Correlation for Sandwich Composite Longitudinal Joint Specimens

The NASA Composite Technology for Exploration (CTE) project is tasked with evaluating methods to analyze and manufacture composite joints for potential use in block upgrades to the Space Launch System (SLS) launch-vehicle structures such as the Payload Attach Fitting (PAF). To perform this task, the CTE project has initiated test and analysis correlation studies for composite joints under various loading conditions. Herein, NASA-developed numerical models are correlated with the experimental results from a series of tension tests. Pretest strain results matched the far-field test data well, but did not capture the nonlinear response in the vicinity of the joint. A refined pretest analytical model was modified to represent progressive failure of the specimens at failure locations observed during the experimental tests. The nonlinear strain response from this progressive failure model predicted the delamination failure load within 15% of the test data, but underpredicted the nonlinearity of the strain response. Further study of composite material models that account for the nonlinear shear response of fabric composites is recommended for the composite joint structures considered in this paper.

Mason, Brian H.↗

DOE OSTI2018

Modelling and Optimization of Uranium (VI) Ions Adsorption Onto Nano-ZnO/Chitosan Bio-composite Beads with Response Surface Methodology (RSM)

Nano-ZnO-chitosan bio-composite beads were prepared for the sorption of UO{sub 2}{sup 2+} from aqueous media. The resulting nano-ZnO/CTS bio-composite beads were characterized by TEM, XRD etc. The sorption of UO{sub 2}{sup 2+} by bio-composite beads was optimized using RSM. The correlation between four variables was modelled and studied. According to RSM data, correlation coefficients (R{sup 2} = 0.99) and probability F-values (F = 2.24 × 10{sup − 10}) show that the model fits the experimental data well. Adsorption capacity for nano-ZnO/CTS bio-composite beads was obtained at 148.7 mg/g under optimum conditions. The results indicate that nano-ZnO/CTS bio-composite beads are appropriate for the adsorption of UO{sub 2}{sup 2+} ions from aqueous media. Also, the suitability of adsorption values to adsorption isotherms was researched and thermodynamic data were calculated.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

Integrating Analytical Solutions and U-Net Model for Predicting Groundwater Contaminant Plumes in Pump-and-Treat Systems

Pump-and-treat (P&T) is a common technique for groundwater remediation involving the extraction and treatment of contaminated water above ground. Optimizing the design and operation of the P&T well network is essential for maximizing the system’s effectiveness and efficiency. However, this optimization often necessitates many model evaluations, leading to computationally demanding tasks. This study introduces a novel approach that integrates analytical solutions for groundwater dynamics with the U-Net (Ronneberger et al., 2015) deep learning framework to predict groundwater contaminant plume migration under dynamic pumping conditions. By incorporating the Thiem equation (Thiem, 1906) into the input preprocessing, the U-Net model transforms sparse well data into a continuous spatial field that captures the hydraulic impacts of pumping activities. This integration enables the model to leverage both deep learning capabilities and classical physics-based groundwater theories, enhancing prediction accuracy and computational efficiency. These advancements can facilitate rapid, large-scale evaluations of P&T optimization simulations, allowing for timely and effective decision-making in well placement and system management. We demonstrate the model's robust performance across both simplified transient 2D models and a more complex 3D heterogeneous site model at the 200 West P&T facility at the Hanford Site. The U-Net-based model offers substantial computational advantages, reducing simulation times significantly compared to full physics-based models and providing a powerful tool for rapid site evaluation and P&T system optimization, such as evaluating alternative P&T well network designs. Our findings highlight the potential of advanced machine learning models to significantly enhance the efficiency and sustainability of groundwater remediation efforts, offering a novel application of U-Net architecture in environmental science.

Pump-and-treat↗

NASA NTRS2006

Representation of the Geosynchronous Plasma Environment in Spacecraft Charging Calculations

Historically, our ability to predict and postdict spacecraft surface charging has been limited by the characterization of the plasma environment. One difficulty lies in the common practice of fitting the plasma data to a Maxwellian or Double Maxwellian distribution function, which may not represent the data well for charging purposes. We use electron and ion flux spectra measured by the Los Alamos National Laboratory (LANL) Magnetospheric Plasma Analyzer (MPA) to examine how the use of different spectral representations of the charged particle environment in computations of spacecraft potentials during magnetospheric substorms affects the accuracy of the results. We calculate the spacecraft potential using both the measured fluxes and several different fits to these fluxes. These measured fluxes have been corrected for the difference between the measured and calculated potential. The potential computed using the measured fluxes and the best available material properties of graphite carbon, with a secondary electron escape fraction of 81%, is within a factor of three of the measured potential for 87% of the data. Potentials calculated using a Kappa function fit to the incident electron flux distribution function and a Maxwellian function fit to the incident ion flux distribution function agree with measured potentials nearly as well as do potentials calculated using the measured fluxes. Alternative spectral representations gave less accurate estimates of potential. The use of all the components of the net flux, along with spacecraft specific average material properties, gives a better estimate of the spacecraft potential than the high energy flux alone.

Davis, V. A.↗

DOE OSTI2022

Electrical Conductivity of Clayey Rocks and Soils: A Non-Linear Model

It is well-accepted that Archie's law is only applicable to “clean” rocks and soils but fails in “dirty” ones where clay minerals possess an additional component of surface conductivity. Although several models, for example, Waxman-Smits model, were presented to account for this phenomenon, surface conductivity is always inappropriately treated as constant, which actually only holds at high salinities. The essential non-linear characteristic differing over fluid salinities has not been physically or mathematically explained well in those models. Here, we scrutinize the conduction mechanism of clayey rocks and soils and ascribe this non-linear feature to (a) variation of the electrical double layer and (b) the intrinsic clay-and-water conduction pattern. With effective medium theory, we develop an easy-to-use non-linear model that both reflects electrochemical theories and explains the measurement data well. Our model can be used to produce more accurate results for laboratory- and field-scale petrophysical parameter evaluations than the previous models.

58 GEOSCIENCES↗

DOE OSTI2024

Deep energy-pressure regression for a thermodynamically consistent EOS model

Abstract In this paper, we aim to explore novel machine learning (ML) techniques to facilitate and accelerate the construction of universal equation-Of-State (EOS) models with a high accuracy while ensuring important thermodynamic consistency. When applying ML to fit a universal EOS model, there are two key requirements: (1) a high prediction accuracy to ensure precise estimation of relevant physics properties and (2) physical interpretability to support important physics-related downstream applications. We first identify a set of fundamental challenges from the accuracy perspective, including an extremely wide range of input/output space and highly sparse training data. We demonstrate that while a neural network (NN) model may fit the EOS data well, the black-box nature makes it difficult to provide physically interpretable results, leading to weak accountability of prediction results outside the training range and lack of guarantee to meet important thermodynamic consistency constraints. To this end, we propose a principled deep regression model that can be trained following a meta-learning style to predict the desired quantities with a high accuracy using scarce training data. We further introduce a uniquely designed kernel-based regularizer for accurate uncertainty quantification. An ensemble technique is leveraged to battle model overfitting with improved prediction stability. Auto-differentiation is conducted to verify that necessary thermodynamic consistency conditions are maintained. Our evaluation results show an excellent fit of the EOS table and the predicted values are ready to use for important physics-related tasks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Filling the Gaps: A Bayesian Mixture Model for Imputing Missing Soil Water Content Data

ABSTRACT Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water‐limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well ( R 2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap‐fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries.

Ogle, Kiona [School of Informatics, Computing, and↗

NASA NTRS1997

The Cretaceous-Tertiary Impact Crater and the Cosmic Projectile that Produced it

Evidence gathered to date from topographic data, geophysical data, well logs, and drill-core samples indicates that the buried Chicxulub basin, the source crater for the approximately 65 Ma Cretaceous-Tertiary (K/T) boundary deposits, is approximately 300 km in diameter. A prominent topographic ridge and a ring of gravity anomalies mark the position of the basin rim at approximately 150 km from the center. Wells in this region recovered thick sequences of impact-generated breccias at 200-300 m below present sea level. Inside the rim, which has been severely modified by erosion following impact, the subsurface basin continues to deepen until near the center it is approximately 1 km deep. The best planetary analog for this crater appears to be the 270 km-diameter Mead basin on Venus. Seismic reflection data indicate that the central zone of downward displacement and excavation (the transient crater is approximately 130 km in diameter, consistent with previous studies of gravity anomaly data). Our analysis of projectile characteristics utilizes this information, coupled with conventional scaling relationships, and geochemical constraints on the mass of extraterrestrial material deposited within the K/T boundary layer. Results indicate that the Chicxulub crater would most likely be formed by a long-period comet composed primarily of nonsilicate materials (ice, hydrocarbons, etc.) and subordinate amounts (less than or equal to 50 percent) primitive chondritic material. This collision would have released the energy equivalent to between 4 x 10(exp 8) and 4 x 10(exp 9) megatons of TNT. Studies of terrestrial impact rates suggest that such an event would have a mean production rate of approximately 1.25 x 10(exp -9) y(exp -1). This rate is considerably lower than that of the major mass extinctions over the last 250 million years (approximately 5 x 10(exp -7) y(exp -1). Consequently, while there is substantial circumstantial evidence establishing the cause-effect link between the Chicxulub basin forming event and the K/T biological extinctions, the results of our analysis do not support models of impact as a common or singular causative agent of mass extinctions on Earth.

Sharpton, Virgil L.↗

NASA NTRS2021

An Evaluation of Remotely Sensed and In-Situ Data Sufficiency for SGMA-Scale Groundwater Studies in the Central Valley, California

California’s Central Valley aquifer is a critical freshwater resource for the state, providing drinking water to 6.5 million residents and irrigation water for more than half of the nation’s produce. Increasing demands have led to a steady decline of aquifer water levels, leading to irreversible compaction and land subsidence. The Sustainable Groundwater Management Act of California (SGMA), instituted in 2014, requires high-priority regions to establish sustainability plans by 2020-2022 that mitigate groundwater depletion and land subsidence. Many regions within the Central Valley lack groundwater monitoring wells or continuous well data, rendering in-situ monitoring challenging. When combined with other data, NASA’s Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) missions provide valuable information about groundwater storage changes at a sub-basin scale. Interferometric Surface Aperture Radar (InSAR) measurements can map land subsidence, and Global Positioning System (GPS) can be used to estimate crustal uplift. Yet, all of these measurements have differences in resolution, coverage, discretization, and record length. Here we assess the various datasets that are potentially useful for Central Valley sub-basin groundwater monitoring and provide an analysis of gaps and other issues in regard to their suitability for SGMA-related analysis. Finally, we offer next steps and recommendations on data treatment and integration.

Kyra H Kim↗

NASA NTRS2004

Progressive Aerodynamic Model Identification From Dynamic Water Tunnel Test of the F-16XL Aircraft

Development of a general aerodynamic model that is adequate for predicting the forces and moments in the nonlinear and unsteady portions of the flight envelope has not been accomplished to a satisfactory degree. Predicting aerodynamic response during arbitrary motion of an aircraft over the complete flight envelope requires further development of the mathematical model and the associated methods for ground-based testing in order to allow identification of the model. In this study, a general nonlinear unsteady aerodynamic model is presented, followed by a summary of a linear modeling methodology that includes test and identification methods, and then a progressive series of steps suggesting a roadmap to develop a general nonlinear methodology that defines modeling, testing, and identification methods. Initial steps of the general methodology were applied to static and oscillatory test data to identify rolling-moment coefficient. Static measurements uncovered complicated dependencies of the aerodynamic coefficient on angle of attack and sideslip in the stall region making it difficult to find a simple analytical expression for the measurement data. In order to assess the effect of sideslip on the damping and unsteady terms, oscillatory tests in roll were conducted at different values of an initial offset in sideslip. Candidate runs for analyses were selected where higher order harmonics were required for the model and where in-phase and out-of-phase components varied with frequency. From these results it was found that only data in the angle-of-attack range of 35 degrees to 37.5 degrees met these requirements. From the limited results it was observed that the identified models fit the data well and both the damping-in-roll and the unsteady term gain are decreasing with increasing sideslip and motion amplitude. Limited similarity between parameter values in the nonlinear model and the linear model suggest that identifiability of parameters in both terms may be a problem. However, the proposed methodology can still be used with careful experiment design and carefully selected values of angle of attack, sideslip, amplitude, and frequency of the oscillatory data.

Murphy, Patrick C.↗

NASA NTRS2012

Staring at 4U 1909+07 with Suzaku (Research Note)

We present an analysis of the neutron star High Mass X-ray Binary (HMXB) 4U 1909+07 mainly based on Suzaku data. We extend the pulse period evolution, which behaves in a random-walk like manner, indicative of direct wind accretion. Studying the spectral properties of 4U 1909+07 between 0.5 to 90keV we find that a power-law with an exponential cutoff can describe the data well, when additionally allowing for a blackbody or a partially covering absorber at low energies. We find no evidence for a cyclotron resonant scattering feature (CRSF), a feature seen in many other neutron star HMXBs sources. By performing pulse phase resolved spectroscopy we investigate the origin of the strong energy dependence of the pulse profile, which evolves from a broad two-peak profile at low energies to a profile with a single, narrow peak at energies above 20keV. Our data show that it is very likely that a higher folding energy in the high energy peak is responsible for this behavior. This in turn leads to the assumption that we observe the two magnetic poles and their respective accretion columns at different phases, and that these accretions column have slightly different physical conditions.

Fuerst, F.↗

DOE OSTI2019

Interpreting the Strain Tensor During Injection into a Reservoir

A suite of well tests was conducted to evaluate the feasibility of measuring and interpreting the strain tensor during injection. Water was injected at 1 liter/s for a few days to a few weeks into a well completed at a depth of 530 m in the Bartlesville sandstone in the North Avant Field in Oklahoma. The strain tensor was measured using strainmeters at a depth of 30m and a distance of 220m from the well. We used a Gladwin strainmeter, a state-of-the-art geodetic strainmeter, as well as novel borehole strainmeters developed for the project. After processing, the horizontal strains were tensile and the vertical strain was compressive during injection. The radial strain was less than the circumferential strain. Strain magnitudes increased during injection and recovered afterward. The strain rate was as fast as 100 nanostrain/d at the start of injection, and decreased to 10 nanostrain/d after a few days. The normal strain signals were approximately proportional to the log of time during the first few days of injection, and the semi-log slope was 50 to 75 nanostrain. Data from the Gladwin strainmeter were essentially identical to data from a strainmeter we developed using optical fiber sensors. Tilt was measured using two tiltmeters, but the tilts were erratic compared to the normal strain and were of limited value. Strain data were analyzed using a strain type-curve method, an analytical solution to a poroelastic inhomogeneity, and a stochastic inversion method. Poroelastic simulations explain the data well. Results from the interpretation methods are consistent with each other, and with independent information characterizing the area. The hydraulic diffusivity is approximately 0.5 m2/s and the permeability is between 100 and 500 mD, according to analysis of the strain signals. This is consistent with measurements of permeability from cores, and with analyses of pressure transients. The analyses indicate that Young’s modulus of the reservoir is between 2 and 6 GPa. Strain interpretations indicate the well intersects a permeable lens with a maximum dimension of 500 to 1,000 m. An isopach map of coarse-grained sand confirms a feature roughly 1,000 m in lateral extent. The results demonstrate that the strain signal measured at shallow (30m) depth can be used to infer properties and heterogeneities in an underlying reservoir or aquifer.

Murdoch, Larry↗

NASA NTRS1999

Time course of sleep inertia dissipation in human performance and alertness

Alertness and performance on a wide variety of tasks are impaired immediately upon waking from sleep due to sleep inertia, which has been found to dissipate in an asymptotic manner following waketime. It has been suggested that behavioural or environmental factors, as well as sleep stage at awakening, may affect the severity of sleep inertia. In order to determine the time course of sleep inertia dissipation under normal entrained conditions, subjective alertness and cognitive throughput were measured during the first 4 h after habitual waketime from a full 8-h sleep episode on 3 consecutive days. We investigated whether this time course was affected by either sleep stage at awakening or behavioural/environmental factors. Sleep inertia dissipated in an asymptotic manner and took 2-4 h to near the asymptote. Saturating exponential functions fitted the sleep inertia data well, with time constants of 0.67 h for subjective alertness and 1.17 h for cognitive performance. Most awakenings occurred out of stage rapid eye movement (REM), 2 or 1 sleep, and no effect of sleep stage at awakening on either the severity of sleep inertia or the time course of its dissipation could be detected. Subjective alertness and cognitive throughput were significantly impaired upon awakening regardless of whether subjects got out of bed, ate breakfast, showered and were exposed to ordinary indoor room light (approximately 150 lux) or whether subjects participated in a constant routine (CR) protocol in which they remained in bed, ate small hourly snacks and were exposed to very dim light (10-15 lux). These findings allow for the refinement of models of alertness and performance, and have important implications for the scheduling of work immediately upon awakening in many occupational settings.

Non-NASA Center↗