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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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Quantitative imaging of the magnetic field distribution in an artificial spin ice studied by off-axis electron holography
Not Available
A Brillouin light scattering study of the spin-wave magnetic field dependence in a magnetic hybrid system made of an artificial spin-ice structure and a film underlayer
We present a combined Brillouin light scattering (BLS) and micromagnetic simulation investigation of the magnetic-field-dependent spin-wave spectra in a hybrid structure made of permalloy (NiFe) artificial spin-ice (ASI) systems, composed of stadium-shaped nanoislands, deposited on the top of an unpatterned permalloy film with a nonmagnetic spacer layer. The thermal spin-wave spectra were recorded by BLS as a function of the magnetic field applied along the symmetry direction of the ASI sample. Magneto-optic Kerr effect magnetometry was used to measure the hysteresis loops in the same orientation as the BLS measurements. Here, the frequency and the intensity of several spin-wave modes detected by BLS were measured as a function of the applied magnetic field. Micromagnetic simulations enabled us to identify the modes in terms of their frequency and spatial symmetry and to extract information about the existence and strength of the dynamic coupling, relevant only to a few modes of a given hybrid system. Using this approach, we suggest a way to understand if the dynamic coupling between ASI and film modes is present or not, with interesting implications for the development of future three-dimensional magnonic applications and devices.
Study of the behaviour of the light field orbital angular momentum upon astigmatic mode conversion
We consider the behaviour of the orbital angular momentum of the light field as a superposition of Hermite – Gaussian beams upon astigmatic mode conversion. An analytical expression is obtained for the orbital angular momentum of such fields. Expressions are found for various linear combinations of Hermite – Gaussian beams. The astigmatic mode conversion of the initial light fields that are equivalent from the point of view of the orbital angular momentum is shown to lead to significantly different final results. (paper)
Dedicated cold-climate field laboratory for photovoltaic system and component studies: the Michigan Regional Test Center as a case study.
Abstract not provided.
Deep Learning-Based Failure Prognostic Model for PV Inverter Using Field Measurements
Here, this study presents a novel approach for the precise monitoring and prognosis of photovoltaic (PV) inverter status, which is crucial for the proactive maintenance of PV systems. It addresses the gaps in traditional model-based methods, which tend to neglect the overall reliability of inverters, and the limitations of data-driven approaches that largely depend on simulated data. This research presents a robust solution applicable to real-world scenarios. The proposed data-driven model for PV inverter failure prognosis employs actual inverter measurements, integrating various operational and weather-related factors based on domain knowledge. This approach effectively represents inverter stressors and operational status. Utilizing an Enhanced Siamese Convolutional Neural Network (ESCNN), the model merges operational data with domain knowledge features, redefining the prognosis challenge as a classification task. Furthermore, the paper discusses an ESCNN-based real-time inverter failure monitoring method developed on the well-trained model. The proposed models are rigorously trained and tested with real inverter data and a novel filtering method is included to address accidental failures in practical scenarios. The results validate the model's efficacy, and the directions for future research are also outlined.
Estimating Latent Fields in Stochastic Dynamical Systems - A Case Study of COVID-19 in New Mexico
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Monitoring Offshore CO 2 Sequestration Using Marine CSEM Methods; Constraints Inferred from Field- and Laboratory-Based Gas Hydrate Studies
Offshore geological sequestration of CO 2 offers a viable approach for reducing greenhouse gas emissions into the atmosphere. Strategies include injection of CO 2 into the deep-ocean or ocean-floor sediments, whereby depending on pressure–temperature conditions, CO 2 can be trapped physically, gravitationally, or converted to CO 2 hydrate. Energy-driven research continues to also advance CO 2 -for-CH 4 replacement strategies in the gas hydrate stability zone (GHSZ), producing methane for natural gas needs while sequestering CO 2 . In all cases, safe storage of CO 2 requires reliable monitoring of the targeted CO 2 injection sites and the integrity of the repository over time, including possible leakage. Electromagnetic technologies used for oil and gas exploration, sensitive to electrical conductivity, have long been considered an optimal monitoring method, as CO 2 , similar to hydrocarbons, typically exhibits lower conductivity than the surrounding medium. We apply 3D controlled-source electromagnetic (CSEM) forward modeling code to simulate an evolving CO 2 reservoir in deep-ocean sediments, demonstrating sufficient sensitivity and resolution of CSEM data to detect reservoir changes even before sophisticated inversion of data. Laboratory measurements place further constraints on evaluating certain systems within the GHSZ; notably, CO 2 hydrate is measurably weaker than methane hydrate, and >1 order of magnitude more conductive, properties that may affect site selection, stability, and modeling considerations.
Applying the Velocity Gradient Technique in NGC 1333: Comparison with Dust Polarization Observations
Magnetic fields (B-fields) are ubiquitous in the interstellar medium (ISM), and they play an essential role in the formation of molecular clouds and subsequent star formation. However, B-fields in interstellar environments remain challenging to measure, and their properties typically need to be inferred from dust polarization observations over multiple physical scales. In this work, we seek to use a recently proposed approach called the velocity gradient technique (VGT) to study B-fields in star-forming regions and compare the results with dust polarization observations in different wavelengths. The VGT is based on the anisotropic properties of eddies in magnetized turbulence to derive B-field properties in the ISM. We investigate that this technique is synergistic with dust polarimetry when applied to a turbulent diffused medium for the purpose of measuring its magnetization. Specifically, we use the VGT on molecular line data toward the NGC 1333 star-forming region ( 12 CO, 13 CO, C 18 O, and N 2 H + ), and we compare the derived B-field properties with those inferred from 214 and 850 μm dust polarization observations of the region using Stratospheric Observatory for Infrared Astronomy/High-Resolution Airborne Wide-band Camera Plus and James Clerk Maxwell Telescope/POL-2, respectively. We estimate both the inclination angle and the 3D Alfvénic Mach number M A from the molecular line gradients. Crucially, testing this technique on gravitationally bound, dynamic, and turbulent regions, and comparing the results with those obtained from polarization observations at different wavelengths, such as the plane-of-sky field orientation, is an important test on the applicability of the VGT in various density regimes of the ISM. We in general do not find a close correlation between the velocity gradient inferred orientations and the dust inferred magnetic field orientations.
Modeling the role of lateral surface flow in low‐relief polygonal tundra
Abstract Ice‐wedge polygon troughs play an important role in controlling the hydrology of low‐relief polygonal tundra regions. Lateral surface flow is confined to troughs only, but it is often neglected in model projections of permafrost thermal hydrology. Recent field and modeling studies have shown that, after rain events, increases in trough water levels are significantly more than the observed precipitation, highlighting the role of lateral surface flow in the polygonal tundra. Therefore, understanding how trough lateral surface flow can influence polygonal tundra thermal hydrology is important, especially under projected changes in temperatures and rainfall in the Arctic regions. Using an integrated cryohydrology model, this study presents plot‐scale end‐of‐century projections of ice‐wedge polygon water budget components and active layer thickness with and without trough lateral surface flow under the Representative Concentration Pathway 8.5 scenario. Trough lateral surface flow is incorporated through a newly developed empirical model, evaluated against field measurements. The numerical scenario that includes trough lateral surface flow simulates discharge (outflow from a polygon) and recharge (rain‐induced inflow to a polygon trough from upslope areas), while the scenario that does not include trough lateral surface flow ignores recharge. The results show considerable reduction (about 100–150%) in evapotranspiration and discharge in rainy years in the scenarios ignoring trough lateral surface flow, but less effect on soil water storage, in comparison with the scenario with trough lateral surface flow. In addition, the results demonstrate long‐term changes (~10–15 cm increase) in active layer thickness when trough lateral surface flow is modeled. This study highlights the importance of including lateral surface flow processes to better understand the long‐term thermal and hydrological changes in low‐relief polygonal tundra regions under a changing climate.
Modeling Terrestrial Dissolved Organic Carbon Loading to Western Arctic Rivers
The mobilization and land-to-ocean transfer of dissolved organic carbon (DOC) in Arctic watersheds is intricately linked with the region's climate and water cycle, and furthermore at risk of changes from climate warming and associated impacts. This study quantifies model-simulated estimates of runoff, surface and active layer leachate DOC concentrations and loadings to western Arctic rivers, specifically for basins that drain into coastal waters between and including the Yukon and Mackenzie Rivers. Model validation leverages data from other field measurements, synthesis studies, and modeling efforts. The simulations effectively quantify DOC leaching in surface and subsurface runoff and broadly capture the seasonal cycle in DOC concentration and mass loadings reported from other studies that use river-based measurements. A marked east-west gradient in simulated spring and summer DOC concentrations of 24 drainage basins on the North Slope of Alaska is captured by the modeling, consistent with independent data derived from river sampling. Simulated loadings for the Mackenzie and Yukon show reasonable agreement with estimates of DOC export for annual totals and four of the six seasonal comparisons. Nearly equivalent loading occurs to rivers which drain north to the Beaufort Sea and west to the Bering and Chukchi Seas. The modeling framework provides a basis for understanding carbon export to coastal waters and for assessing impacts of hydrological cycle intensification and permafrost thaw with ongoing warming in the Arctic.
Investigation of near-field jet stability of a single-hole injector based on fast X-ray phase contrast imaging and image feature matching
Fuel spray is very effective in controlling the combustion process to improve engine performance and reduce emissions. Understanding the spray unstability during the injection process is of importance to improve the control of spray characteristics and engine operation. In this study, near-field biodiesel jets were recorded using fast X-ray phase contrast imaging and the flow features inside the jet were extracted using Speeded Up Robust Features (SURF) method. Here, the image similarity by feature matching was successfully used to represent the near-field jet stability. Based on the jet stability, an injection process can be divided into five stages: an unstable stage at needle opening, a partially stable transition stage at needle opening, a stable stage, a stable transition stage at needle closing and an unstable stage at needle closing. The ranges of needle lift for five stages were also determined. The jet unstability is highly related to the cavitation formation and gas purging process during needle opening. The variation of stable jet feature is dependent on the needle lift at needle closing. Higher needle lift for the similar jet feature at needle opening indicates a hydraulic delay compared to needle closing. Finally, the possible reasons of jet feature formation and feature detection used on the multi-hole injector are discussed.
Interstellar Extinction, Polarization, and Grain Alignment in the Sh 2-185 (IC 59 and IC 63) Region
Optical and infrared continuum polarization from the interstellar medium is driven by radiative processes aligning the grains with the magnetic field. While a quantitative, predictive theory of radiative alignment torques (RATs) exists and has been extensively tested, several parameters of the theory remain to be fully constrained. In a recent paper, Medan & Andersson showed that the polarization efficiency (and therefore grain alignment efficiency) at different locations in the wall of the Local Bubble (LB) could be modeled as proportional to the integrated light intensity from the surrounding stars and OB associations. Here we probe that relationship at high radiation field intensities by studying the extinction and polarization in the two reflection nebulae IC 59 and IC 63 in the Sh 2-185 H ii region, illuminated by the B0 IV star γ Cassiopeia. We combine archival visual polarimetry with new seven-band photometry in the Vilnius system, to derive the polarization efficiency from the material. We find that the same linear relationship seen in the LB wall also applies to the Sh 2-185 region, strengthening the conclusion from the earlier study.
Sources of Primary Electrons in Nanosecond Pulsed Breakdown in Water (Final Technical Report)
Electrical breakdown of liquid dielectrics under ns or sub-ns pulsed electric field has been studied extensively in the last decade. Summarized in [7], this relatively young research area makes significant contributions to the theories of liquid breakdown by introducing a new mechanism (electrostrictive cavitation) that is unique at the ns timescale. It is also fundamentally important to plasma sources for biomedical applications and insulation of pulsed power equipment. For water in particular, the understanding of the mechanisms and processes of ns/sub-ns breakdown also sheds new light on cavitation studies, one of the most exciting areas of modern fluid mechanics. The objective of this collaborative research with PCRF was to construct a complete picture of the physical mechanisms and processes at the initial phase of electrical breakdown in liquid dielectrics under nanosecond (ns) pulsed inhomogeneous fields. The research funded by the initial award DE‐ SC0021182 aimed to address the sources of primary electrons in ns breakdown in water, which led to one journal publication and multiple conference presentations. The PI also gave presentations to the PPPL/PCRF audience twice, one in October 2020 and the other during the 2021 PCRF Annual Meeting
Experimental investigation on thermal inertia characterization of commercial buildings for demand response
Characterizing the thermal inertia of commercial buildings is of great importance in quantifying demand flexibility. Experimental tests can be used to investigate the thermal inertia of commercial buildings. However, existing studies tend to be qualitative and have limited scope. In this study, a comprehensive field test has been performed to assess the thermal inertia of commercial buildings. In this field test, six buildings are selected with different sizes, vintages, and types of heating, ventilation, and air conditioning (HVAC) systems to represent the majority of the U.S. commercial building stock. We quantify the thermal inertia with building operation data collected under various thermostat excitation signals. We then studied the relationship between thermal inertia and intrinsic properties, such as floor area, HVAC system, etc., as well as the operation condition indicators such as outdoor air temperature, zone temperature, and occupancy. The testing results indicate that the median values of the normalized charge response time and the normalized discharge response time of the five buildings are 1~5 hr/ °C and -5~-1 hr/ °C, respectively. The results also show that the thermal inertia of commercial buildings may be sensitive to the HVAC system type but not the floor area or location of zones, i.e., core vs. perimeter. Finally, our results suggest that the relationships between the charging/discharging normalized response time and the zone/outdoor temperature may vary among zones and be highly nonlinear.
Machine learning opportunities for nucleosynthesis studies
Nuclear astrophysics is an interdisciplinary field focused on exploring the impact of nuclear physics on the evolution and explosions of stars and the cosmic creation of the elements. While researchers in astrophysics and in nuclear physics are separately using machine learning approaches to advance studies in their fields, there is currently little use of machine learning in nuclear astrophysics. We briefly describe the most common types of machine learning algorithms, and then detail their numerous possible uses to advance nuclear astrophysics, with a focus on simulation-based nucleosynthesis studies. We show that machine learning offers novel, complementary, creative approaches to address many important nucleosynthesis puzzles, with the potential to initiate a new frontier in nuclear astrophysics research.
Pairing correlations in the cuprates: A numerical study of the three-band Hubbard model
We study the three-band Hubbard model for the copper oxide plane of the high-temperature superconducting cuprates using determinant quantum Monte Carlo and the dynamical cluster approximation (DCA) and provide a comprehensive view of the pairing correlations in this model using these methods. Specifically, we compute the pair-field susceptibility and study its dependence on temperature, doping, interaction strength, and charge-transfer energy. Using the DCA, we also solve the Bethe-Salpeter equation for the two-particle Green's function in the particle-particle channel to determine the transition temperature to the superconducting phase on smaller clusters. Our calculations reproduce many aspects of the cuprate phase diagram and indicate that there is an “optimal” value of the charge-transfer energy for the model where T c is largest. Finally, these results have implications for our understanding of superconductivity in both the cuprates and other doped charge-transfer insulators.
Microseismic Monitoring at the Farnsworth CO 2 -EOR Field
The Farnsworth Unit in northern Texas is a field site for studying geologic carbon storage during enhanced oil recovery (EOR) using CO 2 . Microseismic monitoring is essential for risk assessment by detecting fluid leakage and fractures. We analyzed borehole microseismic data acquired during CO 2 injection and migration, including data denoising, event detection, event location, magnitude estimation, moment tensor inversion, and stress field inversion. We detected and located two shallow clusters, which occurred during increasing injection pressure. The two shallow clusters were also featured by large b values and tensile cracking moment tensors that are obtained based on a newly developed moment tensor inversion method using single-borehole data. The inverted stress fields at the two clusters showed large deviations from the regional stress field. The results provide evidence for microseismic responses to CO 2 /fluid injection and migration.