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DOE OSTI2019

Effect of electrolyte composition on rock salt surface degradation in NMC cathodes during high-voltage potentiostatic holds

Surface degradation of lithium-ion cathodes at high voltages represents a significant barrier to increasing the useable energy of conventional cathodes. Though much work has been focused on mitigating the detrimental effects of such phenomena, the complex and correlated mechanisms involved have made progress difficult. Herein, the effect of electrolyte identity on surface degradation is examined. LiNi0.5Mn0.3Co0.2O2 (NMC532)/Li4Ti5O12 (LTO) full cells were constructed using three different electrolytes: a baseline organic carbonate electrolyte, a baseline organic carbonate electrolyte with an oxidizable additive, and a fluorinated carbonate electrolyte. Each system was subjected to a 60 h potentiostatic hold at 3.05 V (4.6 V vs. Li+/Li) and subsequently deconstructed for characterization via transmission electron microscopy (TEM) and electron energy loss spectroscopy (EELS). Molecular simulations were carried out on each distinct component of the three electrolytes in contact with crystal surfaces of an NMC532 particle. Results indicate an affinity for the additive-containing electrolyte to extract atomic oxygen from the cathode surface, whereas the fluorinated electrolyte components have negligible interactions. Hydrogen abstraction from the baseline electrolyte is facilitated by the NMC532 surface. TEM analysis of cathode surfaces, after the potentiostatic holds, revealed that the NMC532 particles cycled with the additive-containing electrolyte underwent significant surface degradation, including changes to local crystal structure in a region penetrating 20-40 nm from the surface; consistent with oxygen and lithium loss from the cathode material. However, the NMC532 in contact with the fluorinated electrolyte showed a disordered layer of just a few nm in thickness, similar to the depth of crystal disorder observed in pristine NMC532 primary particles. EELS data of the oxygen K-edge also indicated transition metal (TM) reduction, consistent with oxygen loss and changes in crystal structure extending into the cathode surface for each of the electrolytes surveyed. These surface reactions, including oxygen loss, are shown to correlate well with elevated oxidation currents and surface reconstructions of cathode particles.

cathode/electrolyte interface↗

DOE OSTI2013

TIDAL TURBULENCE SPECTRA FROM A COMPLIANT MOORING

A compliant mooring to collect high frequency turbulence data at a tidal energy site is evaluated in a series of short demon- stration deployments. The Tidal Turbulence Mooring (TTM) improves upon recent bottom-mounted approaches by suspend- ing Acoustic Doppler Velocimeters (ADVs) at mid-water depths (which are more relevant to tidal turbines). The ADV turbulence data are superior to Acoustic Doppler Current Profiler (ADCP) data, but are subject to motion contamination when suspended on a mooring in strong currents. In this demonstration, passive stabilization is shown to be sufficient for acquiring bulk statistics of the turbulence, without motion correction. With motion cor- rection (post-processing), data quality is further improved; the relative merits of direct and spectral motion correction are dis- cussed.

ADCP↗

DOE OSTI2025

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗

DOE OSTI2025

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Bridging the length scales on mechanical property evaluation (Final Report)

The development of small-scale mechanical testing in combination with microstructural investigation is of great interest to the nuclear materials community for both materials development and monitoring applications. Dramatically reducing the sample sizes to reduce radioactivity and obtaining mechanical properties of irradiated samples is truly intriguing. Moreover, such studies promise a range of benefits including cost reduction, fundamental insight in structure-property relationships, increased statistics on less sample material, and reinvestigation of prior irradiated and tested reactor samples while simultaneously enabling the generation of mechanical test data on ion beam irradiated materials with limited penetration depths. Small scale materials testing on sub-sized samples has been studied for several decades, though it has only been after the development of micro-testing based on Focused Ion Beam (FIB) sample manufacturing in that orders of magnitude smaller samples could really be investigated in a quantitative manner. In recent years, small scale mechanical testing techniques at a number of length scales has been developed for both unirradiated and irradiated (ion and neutron) materials. Technological advances made in this field have enabled ex-situ and in-situ transmission electron microscopy (TEM) and scanning electron microscopy (SEM) examination, thus leading to more accurate measurements as well as additional mechanistic information. A recent review of the benefits of these techniques show that these techniques are at a stage to tackle multi-scale ranges of materials investigations and can be utilized to obtain fundamental science-based understanding of nuclear materials. Considering the tremendous advances made, one can see how small-scale mechanical testing techniques combined with modeling can enable true small scale to bulk scale mechanical property correlations. However, for the engineering community to adapt this approach fully, one needs to demonstrate that a) that these techniques can produce results with high fidelity and reproducibility, b) generate engineering stress-strain data that one can utilize to understand bulk behavior, and c) generate new insight into relevant phenomena fostering the true understanding of radiation damage and microstructure in materials for nuclear applications. It is the objective of this proposal to bridge the length scale between macro- and micro- scale mechanical testing of unirradiated and irradiated materials. This involves the development and demonstration of procedures for multi-scale mechanical testing that enable high fidelity reproducibility of data and the generation bulk property data from small-scale mechanical tests. Through this, the proposal aims to enhance the confidence in the obtained data at the smaller length scales and enhance the insight provided from these techniques for bulk scale applications on both unirradiated and irradiated materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Magnetohydrodynamic simulations of hot jupiter upper atmospheres

Two-dimensional simulations of hot Jupiter upper atmospheres including the planet's magnetic field are presented. The goal is to explore magnetic effects on the layer of the atmosphere that is ionized and heated by stellar EUV radiation, and the imprint of these effects on the Lyα transmission spectrum. The simulations are axisymmetric, isothermal, and include both rotation and azimuth-averaged stellar tides. Mass density is converted to atomic hydrogen density through the assumption of ionization equilibrium. The three-zone structure—polar dead zone (DZ), mid-latitude wind zone (WZ), and equatorial DZ—found in previous analytic calculations is confirmed. For a magnetic field comparable to that of Jupiter, the equatorial DZ, which is confined by the magnetic field and corotates with the planet, contributes at least half of the transit signal. For even stronger fields, the gas escaping in the mid-latitude WZ is found to have a smaller contribution to the transit depth than the equatorial DZ. Transmission spectra computed from the simulations are compared to Hubble Space Telescope Space Telescope Imaging Spectrograph and Advanced Camera for Surveys data for HD 209458b and HD 189733b, and the range of model parameters consistent with the data is found. The central result of this paper is that the transit depth increases strongly with magnetic field strength when the hydrogen ionization layer is magnetically dominated, for dipole magnetic field B {sub 0} ≳ 10 G. Hence transit depth is sensitive to magnetic field strength, in addition to standard quantities such as the ratio of thermal to gravitational binding energies. Another effect of the magnetic field is that the planet loses angular momentum orders of magnitude faster than in the non-magnetic case, because the magnetic field greatly increases the lever arm for wind braking of the planet's rotation. Spin-down timescales for magnetized models of HD 209458b that agree with the observed transit depth can be as short as ≅ 30 Myr, which is much shorter than the age of the system.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Enhancing trap and fault seal analyses by integrating observations from HR3D seismic data with well logs and conventional 3D seismic data, Texas inner shelf

An understanding of trap and fault seal quality is critical for assessing hydrocarbon prospectivity. To achieve this, modern analytical techniques leverage well data and conventional industry-standard 3D seismic data to evaluate the trap, and any faults displacing the reservoir and top seal intervals. Above all, geological interpretation provides the framework of trap and fault seal analyses, but can be hindered by the data resolution, quality and acquisition style of the conventional seismic data. Furthermore, limiting the analysis to only the petroleum system at depth may lead to erroneous perceptions because interpreting overburden features, such as shallow faults or gas chimneys, can provide valuable observations with respect to container performance, and can to help validate trap and fault seal predictions. Here, a supplement to conventional 3D data are high-resolution 3D seismic (HR3D) data, which provide detailed images of the overburden geology. This study utilizes an HR3D seismic volume in the San Luis Pass area of the Texas inner shelf, where shallow fault tips and a sizeable gas chimney are interpreted over an unsuccessful hydrocarbon prospect. Static post-drill fault seal and trap analyses suggest that the primary fault displacing the structural closure could have withheld columns of gas c. 100 m high, but disagree with our HR3D seismic interpretations and dry-well analyses. From our results, we hypothesize that tertiary gas migration through fault conduits reduced the hydrocarbon column in the prospective Early Miocene reservoir, and may have resulted from continued movement along the intersecting faults. Overall, this study reinforces the importance of understanding the overburden geology and geohistory of faulted prospects, and demonstrates the utility of pre-drill HR3D acquisition when conducting trap and fault seal analyses.

3D seismic↗

DOE OSTI2012

Supporting qualified database for uncertainty evaluation

Uncertainty evaluation constitutes a key feature of BEPU (Best Estimate Plus Uncertainty) process. The uncertainty can be the result of a Monte Carlo type analysis involving input uncertainty parameters or the outcome of a process involving the use of experimental data and connected code calculations. Those uncertainty methods are discussed in several papers and guidelines (IAEA-SRS-52, OECD/NEA BEMUSE reports). The present paper aims at discussing the role and the depth of the analysis required for merging from one side suitable experimental data and on the other side qualified code calculation results. This aspect is mostly connected with the second approach for uncertainty mentioned above, but it can be used also in the framework of the first approach. Namely, the paper discusses the features and structure of the database that includes the following kinds of documents: 1. The' RDS-facility' (Reference Data Set for the selected facility): this includes the description of the facility, the geometrical characterization of any component of the facility, the instrumentations, the data acquisition system, the evaluation of pressure losses, the physical properties of the material and the characterization of pumps, valves and heat losses; 2. The 'RDS-test' (Reference Data Set for the selected test of the facility): this includes the description of the main phenomena investigated during the test, the configuration of the facility for the selected test (possible new evaluation of pressure and heat losses if needed) and the specific boundary and initial conditions; 3. The 'QR' (Qualification Report) of the code calculation results: this includes the description of the nodalization developed following a set of homogeneous techniques, the achievement of the steady state conditions and the qualitative and quantitative analysis of the transient with the characterization of the Relevant Thermal-Hydraulics Aspects (RTA); 4. The EH (Engineering Handbook) of the input nodalization: this includes the rationale adopted for each part of the nodalization, the user choices, and the systematic derivation and justification of any value present in the code input respect to the values as indicated in the RDS-facility and in the RDS-test. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Composite Heat Shields in Intense Energy Fluxes with Diffusion

A method is proposed for bench testing of reusable composite samples under intense thermal and ionizing radiation. Tests are conducted under intense energy fluxes. As a result of the tests, the temperature field and the displacement field at the surface of heat-shielding composite and in its depth are determined at different times. The proposed mathematical model adequately determines describes the temperature distribution in the composite shield under the action of intense energy and radiation fluxes. The influence of diffusion and the temperature field on the displacement field in the composite is studied. The theoretical results are compared with experimental data.

42 ENGINEERING↗

DOE OSTI2017

Unveiling ν secrets with cosmological data: Neutrino masses and mass hierarchy

Using some of the latest cosmological datasets publicly available, we derive the strongest bounds in the literature on the sum of the three active neutrino masses, M ν , within the assumption of a background flat ΛCDM cosmology. In the most conservative scheme, combining Planck cosmic microwave background (CMB) temperature anisotropies and baryon acoustic oscillations (BAO) data, as well as the up-to-date constraint on the optical depth to reionization (τ), the tightest 95% confidence level (C.L.) upper bound we find is M ν <0.151~eV. The addition of Planck high-ℓ polarization data, which however might still be contaminated by systematics, further tightens the bound to M ν <0.118~eV. A proper model comparison treatment shows that the two aforementioned combinations disfavor the IH at ~64%~C.L. and ~71%~C.L. respectively. Furthermore, we compare the constraining power of measurements of the full-shape galaxy power spectrum versus the BAO signature, from the BOSS survey. Even though the latest BOSS full shape measurements cover a larger volume and benefit from smaller error bars compared to previous similar measurements, the analysis method commonly adopted results in their constraining power still being less powerful than that of the extracted BAO signal. Our research uses only cosmological data; imposing the constraint M ν >0.06eV from oscillations data would raise the quoted upper bounds by O(0.1σ) and would not affect our conclusions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

Characterization of Methane Degradation and Methane-Degrading Microbes in Alaska Coastal Water

The net flux of methane from methane hydrates and other sources to the atmosphere depends on methane degradation as well as methane production and release from geological sources. The goal of this project was to examine methane-degrading archaea and organic carbon oxidizing bacteria in methane-rich and methane-poor sediments of the Beaufort Sea, Alaska. The Beaufort Sea system was sampled as part of a multi-disciplinary expedition (Methane in the Arctic Shelf or MIDAS) in September 2009. Microbial communities were examined by quantitative PCR analyses of 16S rRNA genes and key methane degradation genes (pmoA and mcrA involved in aerobic and anaerobic methane degradation, respectively), tag pyrosequencing of 16S rRNA genes to determine the taxonomic make up of microbes in these sediments, and sequencing of all microbial genes (metagenomes ). The taxonomic and functional make-up of the microbial communities varied with methane concentrations, with some data suggesting higher abundances of potential methane-oxidizing archaea in methane-rich sediments. Sequence analysis of PCR amplicons revealed that most of the mcrA genes were from the ANME-2 group of methane oxidizers. According to metagenomic data, genes involved in methane degradation and other degradation pathways changed with sediment depth along with sulfate and methane concentrations. Most importantly, sulfate reduction genes decreased with depth while the anaerobic methane degradation gene (mcrA) increased along with methane concentrations. The number of potential methane degradation genes (mcrA) was low and inconsistent with other data indicating the large impact of methane on these sediments. The data can be reconciled if a small number of potential methane-oxidizing archaea mediates a large flux of carbon in these sediments. Our study is the first to report metagenomic data from sediments dominated by ANME-2 archaea and is one of the few to examine the entire microbial assemblage potentially involved in anaerobic methane oxidation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

First Constraints on the Epoch of Reionization Using the Non-Gaussianity of the Kinematic Sunyaev-Zel’dovich Effect from the South Pole Telescope and Herschel-SPIRE Observations

We report results from an analysis aimed at detecting the trispectrum of the kinematic Sunyaev-Zel’dovich (kSZ) effect by combining data from the South Pole Telescope (SPT) and Herschel-SPIRE experiments over a 100 deg 2 field. The SPT observations combine data from the previous and current surveys, namely SPTpol and SPT-3G, to achieve depths of 4.5, 3, and 16 μ K - arcmin in bands centered at 95, 150, and 220 GHz. For SPIRE, we include data from the 600 and 857 GHz bands. We reconstruct the velocity-induced large-scale correlation of the small-scale kSZ signal with a quadratic estimator that uses two cosmic microwave background (CMB) temperature maps, constructed by optimally combining data from all the frequency bands. We reject the null hypothesis of a zero trispectrum at 10.3 σ level. However, the measured trispectrum contains contributions from both the kSZ and other undesired components, such as CMB lensing and astrophysical foregrounds, with kSZ being sub-dominant. We use the agora simulations to estimate the expected signal from CMB lensing and astrophysical foregrounds. After accounting for the contributions from CMB lensing and foreground signals, we do not detect an excess kSZ-only trispectrum and use this nondetection to set constraints on reionization. By applying a prior based on observations of the Gunn-Peterson trough, we obtain an upper limit on the duration of reionization of Δ z re , 50 < 4.5 (95% confidence level). We find these constraints are fairly robust to foregrounds assumptions. This trispectrum measurement is independent of, but consistent with, Planck’s optical depth measurement. This result is the first constraint on the epoch of reionization using the non-Gaussian nature of the kSZ signal.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Exponential Increase in Relative Biological Effectiveness Along Distal Edge of a Proton Bragg Peak as Measured by Deoxyribonucleic Acid Double-Strand Breaks

Purpose: To quantify the relative biological effectiveness (RBE) of the distal edge of the proton Bragg peak, using an in vitro assay of DNA double-strand breaks (DSBs). Methods and Materials: U2OS cells were irradiated within the plateau of a spread-out Bragg peak and at each millimeter position along the distal edge using a custom slide holder, allowing for simultaneous measurement of physical dose. A reference radiation signal was generated using photons. The DNA DSBs at 3 hours (to assess for early damage) and at 24 hours (to assess for residual damage and repair) after irradiation were measured using the γH2AX assay and quantified via flow cytometry. Results were confirmed with clonogenic survival assays. A detailed map of the RBE as a function of depth along the Bragg peak was generated using γH2AX measurements as a biological endpoint. Results: At 3 hours after irradiation, DNA DSBs were higher with protons at every point along the distal edge compared with samples irradiated with photons to similar doses. This effect was even more pronounced after 24 hours, indicating that the impact of DNA repair is less after proton irradiation relative to photons. The RBE demonstrated an exponential increase as a function of depth and was measured to be as high as 4.0 after 3 hours and as high as 6.0 after 24 hours. When the RBE-corrected dose was plotted as a function of depth, the peak effective dose was extended 2-3 mm beyond what would be expected with physical measurement. Conclusions: We generated a highly comprehensive map of the RBE of the distal edge of the Bragg peak, using a direct assay of DNA DSBs in vitro. Our data show that the RBE of the distal edge increases with depth and is significantly higher than previously reported estimates.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

Understanding heat and groundwater flow through continental flood basalt provinces: insights gained from alternative models of permeability/depth relationships for the Columbia Plateau, USA

Heat-flow mapping of the western USA has identified an apparent low-heat-flow anomaly coincident with the Columbia Plateau Regional Aquifer System, a thick sequence of basalt aquifers within the Columbia River Basalt Group (CRBG). A heat and mass transport model (SUTRA) was used to evaluate the potential impact of groundwater flow on heat flow along two different regional groundwater flow paths. Limited in situ permeability (k) data from the CRBG are compatible with a steep permeability decrease (approximately 3.5 orders of magnitude) at 600–900 m depth and approximately 40°C. Numerical simulations incorporating this permeability decrease demonstrate that regional groundwater flow can explain lower-than-expected heat flow in these highly anisotropic (kx/kz ~ 104) continental flood basalts. Simulation results indicate that the abrupt reduction in permeability at approximately 600 m depth results in an equivalently abrupt transition from a shallow region where heat flow is affected by groundwater flow to a deeper region of conduction-dominated heat flow. Most existing heat-flow measurements within the CRBG are from shallower than 600 m depth or near regional groundwater discharge zones, so that heat-flow maps generated using these data are likely influenced by groundwater flow. Substantial k decreases at similar temperatures have also been observed in the volcanic rocks of the adjacent Cascade Range volcanic arc and at Kilauea Volcano, Hawaii, where they result from low-temperature hydrothermal alteration.

Columbia Plateau Regional Aquifer System↗

DOE OSTI2015

CORONAL PROPERTIES OF THE SEYFERT 1.9 GALAXY MCG-05-23-016 DETERMINED FROM HARD X-RAY SPECTROSCOPY WITH NuSTAR

Measurements of the high-energy cut-off in the coronal continuum of active galactic nuclei have long been elusive for all but a small number of the brightest examples. We present a direct measurement of the cut-off energy in the nuclear continuum of the nearby Seyfert 1.9 galaxy MCG-05-23-016 with unprecedented precision. The high sensitivity of NuSTAR up to 79 keV allows us to clearly disentangle the spectral curvature of the primary continuum from that of its reflection component. Using a simple phenomenological model for the hard X-ray spectrum, we constrain the cut-off energy to 116{sub −5}{sup +6} keV with 90% confidence. Testing for more complex models and nuisance parameters that could potentially influence the measurement, we find that the cut-off is detected robustly. We further use simple Comptonized plasma models to provide independent constraints for both the kinetic temperature of the electrons in the corona and its optical depth. At the 90% confidence level, we find kT{sub e} = 29 ± 2 keV and τ {sub e} = 1.23 ± 0.08 assuming a slab (disk-like) geometry, and kT{sub e} = 25 ± 2 keV and τ {sub e} = 3.5 ± 0.2 assuming a spherical geometry. Both geometries are found to fit the data equally well and their two principal physical parameters are correlated in both cases. With the optical depth in the τ {sub e} ≳ 1 regime, the data are pushing the currently available theoretical models of the Comptonized plasma to the limits of their validity. Since the spectral features and variability arising from the inner accretion disk have been observed previously in MCG-05-23-016, the inferred high optical depth implies that a spherical or disk-like corona cannot be homogeneous.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Continental Scale Hydrostratigraphy: Basin‐Scale Testing of Alternative Data‐Driven Approaches

Abstract Integrated hydrological modeling is an effective method for understanding interactions between parts of the hydrologic cycle, quantifying water resources, and furthering knowledge of hydrologic processes. However, these models are dependent on robust and accurate datasets that physically represent spatial characteristics as model inputs. This study evaluates multiple data‐driven approaches for estimating hydraulic conductivity and subsurface properties at the continental‐scale, constructed from existing subsurface dataset components. Each subsurface configuration represents upper (unconfined) hydrogeology, lower (confined) hydrogeology, and the presence of a vertical flow barrier. Configurations are tested in two large‐scale U.S. watersheds using an integrated model. Model results are compared to observed streamflow and steady state water table depth (WTD). We provide model results for a range of configurations and show that both WTD and surface water partitioning are important indicators of performance. We also show that geology data source, total subsurface depth, anisotropy, and inclusion of a vertical flow barrier are the most important considerations for subsurface configurations. While a range of configurations proved viable, we provide a recommended Selected National Configuration 1 km resolution subsurface dataset for use in distributed large‐and continental‐scale hydrologic modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

A Multi-Stage Wear Model for Grid-to-Rod Fretting of Nuclear Fuel Rods

The wear of fuel rod cladding against the supporting structures in the cores of pressurized water nuclear reactors (PWRs) is an important and potentially costly tribological issue. Grid-to-rod fretting (GTRF), as it is known, involves not only time-varying contact conditions, but also elevated temperatures, flowing hot water, aqueous tribo-corrosion, and the embrittling effects of neutron fluences. The multi-stage, closed-form analytical model described in this paper relies on published out-of-reactor wear and corrosion data and a set of simplifying assumptions to portray the conversion of frictional work into wear depth. The cladding material of interest is a zirconium-based alloy called Zircaloy-4, and the grid support is made of a harder and more wear-resistant material. Focus is on the wear of the cladding. The model involves an incubation stage, a surface oxide wear stage, and a base alloy wear stage. The wear coefficient, which is a measure of the efficiency of conversion of frictional work into wear damage, can change to reflect the evolving metallurgical condition of the alloy. Wear coefficients for Zircaloy-4 and for a polyphase zirconia layer were back-calculated for a range of times required to wear to a critical depth. Inputs for the model, like the friction coefficient, are taken from the tribology literature in lieu of in-reactor tribological data. Concepts of classical fretting were used as a basis, but are modified to enable the model to accommodate the complexities of the PWR environment. Factors like grid spring relaxation, pre-oxidation of the cladding, multiple oxide phases, gap formation, impact, and hydrogen embrittlement are part of the problem definition but uncertainties in their relative roles limits the ability to validate the model. Sample calculations of wear depth versus time in the cladding illustrate how GTRF wear might occur in a discontinuous fashion during months-long reactor operating cycles. A means to account for grid/rod gaps and repetitive impact effects on GTRF wear is proposed

fretting↗