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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Development of a Short-Duration Drive Cycle to Represent Long-Term Measured Drive Cycle Data: Evaluation of Truck Efficiency Technologies in Class 8 Tractor Trailers

Quantifying the fuel savings and emissions reductions that can be achieved from truck fuel efficiency technologies for a fleet's specific usage allows the fleet to select a combination of technologies that will yield the greatest operational efficiency and profitability. An accurate characterization of usage for the fleet is critical for such an evaluation; however, short-term measured drive cycle data do not generally reflect overall usage very effectively. This study presents a detailed analysis of vehicle usage in a commercial vehicle fleet and demonstrates the development of a short-duration synthetic drive cycle with measured drive cycle data collected over an extended period of time. The approach matched statistical measures of the vehicle speed with acceleration history and integrated measured grade data to develop a compressed drive cycle that accurately represents total usage. Drive cycle measurements obtained during a full year from six tractor trailers in normal operations in a less-than-truckload carrier were analyzed to develop a synthetic drive cycle. The vehicle mass was also estimated to account for the variation of loads that the fleet experienced. These drive cycle and mass data were analyzed with a tractive energy analysis to quantify the benefits in terms of fuel efficiency and reduced carbon dioxide emissions that can be achieved on Class 8 tractor trailers by using advanced efficiency technologies, either individually or in combination. Although differences exist between Class 8 tractor trailer fleets, this study provides valuable insight into the energy and emissions reduction potential that various technologies can bring in this important trucking application. Finally, the methodology employed for generating the synthetic drive cycle serves as a rigorous approach to develop an accurate usage characterization that can be used to effectively compress large quantities of drive cycle data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Temperature and precipitation signal in two Alpine ice cores over the period 1961–2001

Water stable isotope ratios and net snow accumulation in ice cores are commonly interpreted as temperature or precipitation proxies. However, only in a few cases has a direct calibration with instrumental data been attempted. In this study we took advantage of the dense network of observations in the European Alpine region to rigorously test the relationship of the annual and seasonal resolved proxy data from two highly resolved ice cores with local temperature and precipitation. We focused on the time period 1961–2001 with the highest amount and quality of meteorological data and the minimal uncertainty in ice core dating (±1 year). The two ice cores were retrieved from the Fiescherhorn glacier (northern Alps, 3900 m a.s.l.), and Grenzgletscher (southern Alps, 4200 m a.s.l.). A parallel core from the Fiescherhorn glacier allowed assessing the reproducibility of the ice core proxy data. Due to the orographic barrier, the two flanks of the Alpine chain are affected by distinct patterns of precipitation. The different location of the two glaciers therefore offers a unique opportunity to test whether such a specific setting is reflected in the proxy data. On a seasonal scale a high fraction of δ 18 O variability was explained by the seasonal cycle of temperature (~60% for the ice cores, ~70% for the nearby stations of the Global Network of Isotopes in Precipitation – GNIP). When the seasonality is removed, the correlations decrease for all sites, indicating that factors other than temperature such as changing moisture sources and/or precipitation regimes affect the isotopic signal on this timescale. Post-depositional phenomena may additionally modify the ice core data. On an annual scale, the δ 18 O/temperature relationship was significant at the Fiescherhorn, whereas for Grenzgletscher this was the case only when weighting the temperature with precipitation. In both cases the fraction of interannual temperature variability explained was ~20%, comparable to the values obtained from the GNIP stations data. Consistently with previous studies, we found an altitude effect for the δ 18 O of -0.17‰/100 m for an extended elevation range combining data of the two ice core sites and four GNIP stations. Significant correlations between net accumulation and precipitation were observed for Grenzgletscher during the entire period of investigation, whereas for Fiescherhorn this was the case only for the less recent period (1961–1977). Local phenomena, probably related to wind, seem to partly disturb the Fiescherhorn accumulation record. Spatial correlation analysis shows the two glaciers to be influenced by different precipitation regimes, with the Grenzgletscher reflecting the characteristic precipitation regime south of the Alps and the Fiescherhorn accumulation showing a pattern more closely linked to northern Alpine stations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Hybrid Modeling of Three-Phase Grid-Supporting Inverters for Dynamic Studies

Grid technologies connected by power electronic converter (PEC) interfaces continually implement grid support functions mandated by grid codes and standards. The transition to converter-based generation demands precise PEC models to assess system dynamics, which have been previously overlooked in conventional power systems. This study proposes a hybrid method for analyzing grid-connected three-phase PEC dynamics with the IEEE standard 1547-2018 Volt-VAr mode that combines physics and data-driven techniques. The physics model reflects the PEC’s internal behavior, whereas the data-driven modeling technique evaluates the grid-supporting capabilities of the smart PEC. The system identification approach is used to generate dynamic PEC models based on changing grid voltage and measured current injected into the grid by the PEC. In the Volt-VAr support mode, a detailed topological model including switches is utilized to compare the goodness-of-fit of the extracted hybrid dynamic model. The results demonstrate that the hybrid PEC model in the Volt-VAr mode accurately matches the dynamics with the topological model.

Subedi, Sunil↗
DOE OSTI2022

Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)

This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Order priors for Bayesian network discovery with an application to malware phylogeny

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges) in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Synergistic ground and orbital observations of iron oxides on Mt. Sharp and Vera Rubin ridge

Visible/short-wave infrared spectral data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) show absorptions attributed to hematite at Vera Rubin ridge (VRR), a topographic feature on northwest Mt. Sharp. The goals of this study are to determine why absorptions caused by ferric iron are strongly visible from orbit at VRR, and to improve interpretation of CRISM data throughout lower Mt. Sharp. These goals are achieved by analyzing coordinated CRISM and in situ spectral data along the Curiosity Mars rover’s traverse. VRR bedrock within areas that have the deepest ferric absorptions in CRISM data also have the deepest ferric absorptions measured in situ. This suggests strong ferric absorptions are visible from orbit at VRR because of the unique spectral properties of VRR bedrock. Dust and mixing with basaltic sand additionally inhibit the ability to measure ferric absorptions in bedrock stratigraphically below VRR from orbit. There are two implications of these findings: (1) Ferric absorptions in CRISM data initially dismissed as noise could be real, and ferric phases are more widespread in lower Mt. Sharp than previously reported, (2) Patches with the deepest ferric absorptions in CRISM data are, like VRR, reflective of deeper absorptions in the bedrock. One model to explain this spectral variability is late-stage diagenetic fluids that changed the grain size of ferric phases, deepening absorptions. Curiosity’s experience highlights the strengths of using CRISM data for spectral absorptions and associated mineral detections, and the caveats in using these data for geologic interpretations and strategic path planning tools.

58 GEOSCIENCES↗
DOE OSTI2022

An Analysis of PNM's Renewable Reserve Requirements to Meet New Mexico's Decarbonization Goals

Over the next three years, the Public Service Company of New Mexico (PNM) plans to increase utility-scale solar photovoltaic (PV) capacity from today’s roughly 330MW to about 1600MW. This massive increase in variable generation—from about 15% to 75% of peak load—will require changes in how PNM operates their system. We characterize the 5 and 30-minute solar and wind forecast errors that the system is likely to experience in order to determine the level of reserves needed to counteract such events. Our focus in this study is on negative forecast error (in other words, shortfalls relative to forecast) – whereas excess variable generation can be curtailed if needed, a shortfall must be compensated for to avoid loss of load. Calculating forecast error requires the use of the same forecasting methods that PNM uses or a reasonable approximation thereof. For wind, we use a persistence forecast on actual 5-minute 2019 wind output data (scaled up to reflect the amount of wind capacity planned for 2025). For solar, we use a formula incorporating the clear sky index (CSI) for the forecast. As the solar on the grid now is a small fraction of what is planned for 2025, we generated 5-minute solar data using 2019 weather inputs. We find that to handle 99.9% of the 5-minute negative forecast errors, a maximum of 275MW of variable generation reserve during daylight hours, and a maximum of 75MW during non-daylight hours, should be sufficient. Note that this variable generation reserve is an additional reserve category that specifies reserves over and above what are currently carried for contingency reserve. This would require a significant increase in reserve relative to what PNM currently carries or can call upon from other utilities per reserve sharing agreements. This variable generation reserve specification may overestimate the actual level needed to deal with PNM’s planned variable generation in 2025. The forecasting methodologies used in this study likely underperform PNM’s forecasting – and better forecasting allows for less reserve. To obtain more precise estimates, it is necessary to consider load and use the same forecasting inputs and methods used by PNM.

14 SOLAR ENERGY↗
DOE OSTI2014

The effect of birthrate granularity on the release-to-birth ratio for the AGR-1 in-core experiment

The AGR-1 Advanced Gas Reactor (AGR) tristructural-isotropic-particle fuel experiment underwent 13 irradiation intervals from December 2006 until November 2009 within the Idaho National Laboratory Advanced Test Reactor in support of the Next Generation Nuclear Power Plant program. During this multi-year experiment, release-to-birth rate ratios were computed at the end of each operating interval to provide information about fuel performance. Fission products released during irradiation were tracked daily by the Fission Product Monitoring System using 8-h measurements. Birth rate calculated by MCNP with ORIGEN for as-run conditions were computed at the end of each irradiation interval. Each time step in MCNP provided neutron flux, reaction rates and AGR-1 compact composition, which were used to determine birth rate using ORIGEN. The initial birth-rate data, consisting of four values for each irradiation interval at the beginning, end, and two intermediate times, were interpolated to obtain values for each 8-h activity. The problem with this method is that any daily changes in heat rates or perturbations, such as shim control movement or core/lobe power fluctuations, would not be reflected in the interpolated data and a true picture of the system would not be presented. At the conclusion of the AGR-1 experiment, great efforts were put forth to compute daily birthrates, which were reprocessed with the 8-h release activity. The results of this study are presented in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Development of a tomographic reconstruction method for axisymmetric D α emission profiles in the ITER plasma boundary

A tomographic method for reconstructing the axially symmetric D α emission profile in the ITER scrape-off layer and divertor from D α intensity measurements in the fields of view (FoV) of Vis/IR TV and Divertor Impurity Monitor diagnostics is under development. The method takes into account the strong background signal due to stray light from divertor produced by reflections from the metal wall of the vacuum chamber. The method allows to filter out the reflections in D α signals measured in the main chamber. Here, the accuracy of this method is tested within the framework of a synthetic diagnostic, which uses the Raysect and Cherab numerical codes for ray-tracing simulations. The D α emission profiles, simulated with the SOLPS and OEDGE codes, are used as synthetic experimental data. Uncertainty in light reflection properties of the first wall (FW) is the major factor affecting the accuracy of the D α emission reconstruction. The dependence on the uncertainty in the FW surface roughness and on the ratio of diffusive to specular reflection of the error in recovering useful D α signals (the direct light without reflections) in the FoV of the ITER main chamber H-alpha and Visible Spectroscopy Diagnostic is obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A Polycrystalline Pd Surface Studied by Two-Dimensional Surface Optical Reflectance during CO Oxidation: Bridging the Materials Gap

Industrial catalysts are complex materials systems operating in harsh environments. The active parts of the catalysts are nanoparticles that expose different facets with different surface orientations at which the catalytic reactions occur. However, these facets are close to impossible to study in detail under industrially relevant operating conditions. Instead, simpler model systems, such as single crystals with a well-defined surface orientation, have been successfully used to study gas–surface interactions such as adsorption and desorption, surface oxidation, and oxidation/reduction reactions. To more closely mimic the many facets exhibited by nanoparticles and thereby close the so-called materials gap, there has also been a recent move toward using polycrystalline surfaces and curved crystals. However, these studies are limited either by the pressure or spatial resolution at realistic pressures or by the number of surfaces studied simultaneously. In this work, we demonstrate the use of reflectance microscopy to study a vast number of catalytically active surfaces simultaneously under realistic and identical reaction conditions. As a proof of concept, we have conducted an operando experiment to study CO oxidation over a Pd polycrystal, where the polycrystalline surface acts as a collection of many single-crystal surfaces. Finally, we visualized the resulting data by plotting the reflectivity as a function of surface orientation. We think the techniques and visualization methods introduced in this work will be key toward bridging the materials gap in catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Online Monitoring System for Concrete Structures Affected by Alkali-Silica Reaction

This report presents a comprehensive study of developing ultrasonic wave and acoustic emission (AE) techniques for long-term monitoring of alkali-silica reaction (ASR) development in concrete. Small, medium, and full-scale concrete specimens were cast, conditioned, and monitored for various periods, from at least one year to 2.4 years. The reactive concrete specimens contain coarse or fine reactive aggregates to study the effects of different types of reactive aggregates. Confinements were also designed to simulate the 2-dimensional confinement effects of reinforcement in the shield building of nuclear power plants. The concrete specimens were stored in a environmental chamber with high humidity and high temperature to accelerate the ASR development. The ultrasonic monitoring data shows high sensitivity to ASR development and could detect cracking initiation well before visible surface cracks occurred. However, the linear ultrasonic analysis based on wave velocity is strongly affected by temperature variation. Therefore, a nonlinear ultrasonic method was proposed to measure thermally induced nonlinear acoustic responses of concrete (thermal modulation of ultrasonic wave). The measured nonlinear acoustic parameter shows a high correlation with ASR expansion across specimens with different reactive aggregates and confinement conditions. The same conclusion was obtained from nonlinear resonance tests on small concrete prisms. Compared to the linear acoustic methods, the nonlinear tests show high sensitivities to ASR damage from internal microcracking initiation at the early stage to visible cracks at the late stage of ASR. The attributes of the thermal modulation of nonlinear ultrasonic method include high sensitivity, immunity to temperature effects, and strong correlation with ASR expansion, which demonstrate great potentials of the nonlinear ultrasonic method for diagnosis of ASR damage and prediction of concrete deterioration process. Acoustic emission is a passive sensing technique for damage assessment, and access to only one surface is needed even for thick and heavily reinforced elements such as the walls utilized for nuclear shield building. Additionally, relatively few sensors are required to monitor the progression of the damage process. Results indicate that the AE data can be related to the damage rating index, which is a petrography-based means of assessing damage due to ASR in reinforced concrete. Furthermore, AE is capable of detecting ASR damage long before surface cracking is visually noticeable. Boundary conditions play in important role in the progression of ASR damage and differences in boundary conditions are reflected in the AE data. Entropy based data assessment methods provide a means to assess the damage state, and convolutional neural network based data assessment provided a means to assess the damage state in real-time. Results indicate that artificial neural network models may be used as a means to predict volumetric expansion based on AE data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Retrospective Reconstructions of Active Bone Marrow Dose-Volume Histograms

Purpose: To present a method for calculating dose-volume histograms (DVH's) to the active bone marrow (ABM) of patients who had undergone radiation therapy (RT) and subsequently developed leukemia. Methods and Materials: The study focuses on 15 patients treated between 1961 and 1996. Whole-body RT planning computed tomographic (CT) data were not available. We therefore generated representative whole-body CTs similar to patient anatomy. In addition, we developed a method enabling us to obtain information on the density distribution of ABM all over the skeleton. Dose could then be calculated in a series of points distributed all over the skeleton in such a way that their local density reflected age-specific data for ABM distribution. Dose to particular regions and dose-volume histograms of the entire ABM were estimated for all patients. Results: Depending on patient age, the total number of dose calculation points generated ranged from 1,190,970 to 4,108,524. The average dose to ABM ranged from 0.3 to 16.4 Gy. Dose-volume histograms analysis showed that the median doses (D{sub 50%}) ranged from 0.06 to 12.8 Gy. We also evaluated the inhomogeneity of individual patient ABM dose distribution according to clinical situation. It was evident that the coefficient of variation of the dose for the whole ABM ranged from 1.0 to 5.7, which means that the standard deviation could be more than 5 times higher than the mean. Conclusions: For patients with available long-term follow-up data, our method provides reconstruction of dose-volume data comparable to detailed dose calculations, which have become standard in modern CT-based 3-dimensional RT planning. Our strategy of using dose-volume histograms offers new perspectives to retrospective epidemiological studies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Determination of hot carrier energy distributions from inversion of ultrafast pump-probe reflectivity measurements

Developing a fundamental understanding of ultrafast non-thermal processes in metallic nanosys- tems will lead to applications in photodetection, photochemistry and photonic circuitry. Typically, non-thermal and thermal carrier populations in plasmonic systems are inferred either by making assumptions about the functional form of the initial energy distribution or using indirect sensors like localized plasmon frequency shifts. In this work we directly determine non-thermal and thermal distributions and dynamics in thin films by applying a double inversion procedure to optical pump- probe data that relates the reflectivity changes around Fermi energy to the changes in the dielectric function and in the single-electron energy band occupancies. When applied to normal incidence measurements our method uncovers the ultrafast excitation of a non-Fermi-Dirac distribution and its subsequent thermalization dynamics. Moreover, when applied to the Kretschmann configu- ration, we show that the excitation of propagating plasmons leads to a broader energy distribution of electrons due to the enhanced Landau damping.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Synthesis, crystal structure and photoluminescence of (Ba{sub 0.99}Eu{sub 0.01})Al{sub 3}Si{sub 4}N{sub 9}

Crystalline grains of (Ba{sub 0.99}Eu{sub 0.01})Al{sub 3}Si{sub 4}N{sub 9} were obtained from samples synthesized by heating mixtures of binary nitride powders at 2000 °C and 0.85 MPa of N{sub 2} gas. The fundamental reflections of electron diffraction (ED) and X-ray diffraction (XRD) measured for some grains could be indexed with orthorhombic cell parameters: a=10.028(2) Å, b=53.353(9) Å, and c=5.9215(11) Å. Streaks and diffuse lines along the b axis were observed in the ED and XRD photographs, indicating stacking faults. A statistical average structure was analyzed using the intensity data of the fundamental reflections with the space group Fdd2. Local structure models were presented based on the average structure. Similar streaks and diffuse lines with fundamental reflections indexed with monoclinic cell parameters: a=5.8376(4) Å, b=26.6895(12) Å, c=5.8393(3) Å, and β=118.8428(15)° were also observed in the XRD oscillation photographs of another grain. The mixture of the grains having the orthorhombic and monoclinic fundamental structures emitted blue–green light with a peak wavelength of 500 nm and a full width at half-maximum (FWHM) of 65 nm under 400 nm excitation. The emission intensity measured at 300 °C was 67.5% of the intensity measured at 25 °C. A broad excitation band ranged from about 260 nm to 475 nm with maximum intensity at around 290 nm, and 60% of the intensity was obtained by excitation at 400 nm. - Graphical abstract: Crystalline grains of (Ba{sub 0.99}Eu{sub 0.01})Al{sub 3}Si{sub 4}N{sub 9}, having orthorhombic and monoclinic fundamental structures and stacking faults, were obtained from samples synthesized at 2000 °C and 0.85 MPa of N{sub 2}. The grains emitted blue–green light with a peak wavelength of 500 nm and a full width at half-maximum (FWHM) of 65 nm under 400 nm excitation. The emission intensity measured at 300 °C was 67.5% of the intensity measured at 25 °C. - Highlights: • (Ba{sub 0.99}Eu{sub 0.01})Al{sub 3}Si{sub 4}N{sub 9} was synthesized at 2000 °C and 0.85 MPa of N{sub 2}. • Stacking faults of the crystal structure were shown by X-ray and electron diffraction. • Orthorhombic and monoclinic statistical average-structure models were presented. • Photoluminescence excitation and emission spectra were measured. • Thermal quenching of the emission intensities was characterized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Three-dimensional simulations of National Ignition Facility implosions: Insight into experimental observables

We simulate in 3D both the hydrodynamics and, simultaneously, the X-ray and neutron diagnostic signatures of National Ignition Facility (NIF) implosions. We apply asymmetric radiation drive to study the impact of low mode asymmetry on diagnostic observables. We examine X-ray and neutron images as well as neutron spectra for these perturbed implosions. The X-ray images show hot spot evolution on small length scales and short time scales, reflecting the incomplete stagnation seen in the simulation. The neutron images show surprising differences from the X-ray images. The neutron spectra provide additional measures of implosion asymmetry. Flow in the hot spot alters the neutron spectral peak, namely, the peak location and width. The changes in the width lead to a variation in the apparent temperature with viewing angle that signals underlying hot spot asymmetry. We compare our new expectations based on the simulated data with NIF data. We find that some recent cryogenic layered experiments show appreciable temperature anisotropy indicating residual flow in the hot spot. We also find some trends in the data that do not reflect our simulation and theoretical understanding.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

The 2013–2014 outburst of XTE J1908+094 observed with Swift and NuSTAR: Spectral evolution and black hole spin constraint

We present a spectral study of the black hole candidate XTE J1908+094 during its 2013–2014 outburst. We analyzed 36 Swift/XRT observations together with a NuSTAR observation taken along this period. The outburst evolution is similar to what is previously observed in other black hole transients. The source transited from an initial low/hard state to a high/soft state and then went back to the low/hard state. The low/hard-state spectra are dominated by a hard component, while the high/soft-state spectra are dominated by a soft component. In the high/soft state, we find that the disk bolometric luminosity deviates weakly from the standard T{sub in}{sup 4} dependence, exhibiting a flatter dependence as L{sub disk}∝T{sub in}{sup 2}. The radial temperature profile is found to be flatter than that of the standard accretion disk. These results suggest an advection-dominated slim disk. During the NuSTAR observation, the source was in the high/soft state. A flare is seen in the NuSTAR light curves. During the flare, a spectral softening occurs with an increase in power-law flux. We suggest that the flare may be associated with the relativistic jets. A broad Fe Kα line and a disk reflection component are observed in the spectra, providing an opportunity to measure the black hole spin via the Fe-line method. We have fitted the NuSTAR spectra with different relativistically blurred disk reflection models. However, the data do not allow us to constrain the spin of the black hole.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Revealing complex subsurface dynamics with continuous seismic monitoring: Observations using distributed acoustic sensing and surface orbital vibrators during hydraulic fracturing

Understanding hydraulic fracturing is crucial to improving the stimulation of unconventional reservoirs and increasing fluid production. This study develops a novel seismic monitoring technology using distributed acoustic sensing (DAS) and surface orbital vibrators (SOV) to capture fracture seismic response and mechanical properties at high temporal intervals. We analyze continuous time-lapse vertical seismic profiling (VSP) data acquired every hour during the first nine days of treatment of an unconventional reservoir in the Austin Chalk/Eagle Field Laboratory. The VSP data contain clear seismic signals scattered from the activated fractures. The spatiotemporal changes of the fracture reflectivity revealed by the SOV/DAS data correlate well with the observations of fracture locations inferred from low-frequency DAS data. These results capture the fracture opening and closure processes, as well as highlight potential prestage activations of the fractures due to hydraulic connectivity with preexisting fracture systems. Therefore, analysis of the presented data set provides a unique opportunity to understand fracture initiation and subsequent evolution, not only in the context of unconventional resources but also in enhanced geothermal systems.

Correa, Julia↗