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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g., ELM filaments) in the scrape-off layer and at the plasma edge with 2.5 μs temporal and 10 mm optical resolution. A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics and then extended to a database of 159 ELM events. Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average, an ELM crash consists of a filament with a circular cross section, which is propelled outward with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100 μs until the radial propulsion settles back to the pre-ELM level. Furthermore, the experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current–filament interaction model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Fermionic matrix product states and one-dimensional short-range entangled phases with antiunitary symmetries

We extend the formalism of matrix product states (MPS) to describe one-dimensional gapped systems of fermions with both unitary and antiunitary symmetries. Additionally, systems with orientation-reversing spatial symmetries are considered. The short-ranged entangled phases of such systems are classified by three invariants, which characterize the projective action of the symmetry on edge states. We give interpretations of these invariants as properties of states on the closed chain. The relationship between fermionic MPS systems at a renormalization group fixed point and equivariant algebras is exploited to derive a group law for the stacking of fermionic phases. Furthermore, the result generalizes known classifications to symmetry groups that are nontrivial extensions of fermion parity and time-reversal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Polariton Condensation in Gap-Confined States of Photonic Crystal Waveguides

Here, the development of patterned multiquantum well heterostructures in GaAs/AlGaAs waveguides has recently made it possible to achieve exciton-polariton condensation in a topologically protected bound state in the continuum (BIC). Polariton condensation was shown to occur above a saddle point of the two-dimensional polariton dispersion in a one-dimensional photonic crystal waveguide. A rigorous analysis of the condensation phenomenon in these systems, as well as the role of the BIC, is still missing. In the present Letter, we theoretically and experimentally fill this gap by showing that polariton confinement resulting from the negative effective mass and the photonic energy gap in the dispersion play a key role in enhancing the relaxation toward the condensed state. In fact, our results show that low-threshold polariton condensation is achieved within the effective trap created by the exciting laser spot, regardless of whether the resulting confined mode is long-lived (polariton BIC) or short-lived (lossy mode). In both cases, the spatial quantization of the polariton condensate and the threshold differences associated to the corresponding state lifetime are measured and characterized. For a given negative mass, a slightly lower condensation threshold from the polariton BIC mode is found and associated to its reduced radiative losses, as compared to the lossy one.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Data-centric framework for crystal structure identification in atomistic simulations using machine learning

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

X-ray scattering based scanning tomography for imaging and structural characterization of cellulose in plants

X-ray and neutron scattering have long been used for structural characterization of cellulose in plants. Due to averaging over the illuminated sample volume, these measurements traditionally overlooked the compositional and morphological heterogeneity within the sample. Here, a scanning tomographic imaging method is described, using contrast derived from the X-ray scattering intensity, for virtually sectioning the sample to reveal its internal structure at a resolution of a few micrometres. This method provides a means for retrieving the local scattering signal that corresponds to any voxel within the virtual section, enabling characterization of the local structure using traditional data-analysis methods. This is accomplished through tomographic reconstruction of the spatial distribution of a handful of mathematical components identified by non-negative matrix factorization from the large dataset of X-ray scattering intensity. Joint analysis of multiple datasets, to find similarity between voxels by clustering of the decomposed data, could help elucidate systematic differences between samples, such as those expected from genetic modifications, chemical treatments or fungal decay. The spatial distribution of the microfibril angle can also be analyzed, based on the tomographically reconstructed scattering intensity as a function of the azimuthal angle.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging (GPI) at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g. ELM filaments) in the scrape-off layer and the at the plasma edge with 2.5 us temporal and 10 mm optical resolution.A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics, and then extended to a database of 169 ELM events.Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average an ELM crash consists of a filament with a circular cross-section which is propelled outwards with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100us until the radial propulsion settles back to the pre-ELM level. The experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current-filament interaction model.

correlation↗
DOE OSTI2023

Data-Driven Transition Path Analysis Yields a Statistical Understanding of Sudden Stratospheric Warming Events in an Idealized Model

Abstract Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current . The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Evaluation of Potential DAS Array Geometries for the Source Physics Experiment, Phase III

Distributed Acoustic Sensing (DAS) is a rapidly developing technology that can record acoustic wavefields at high sampling rates and with dense spatial spacing difficult to achieve with seismometers. However, the geophysical community has not fully explored DAS survey parameters to characterize the ideal array design. A better quantitative understanding of DAS array behavior prior to SPE Phase III acquisition can help improve the quality of the data recorded by guiding the DAS array design. Here we use array response functions as well as beamforming and backprojection results from forward modelling calculations to assess the performance of varying DAS array geometries to record regional and local sources. A seven-sided polygon DAS array demonstrated improved capabilities for recording regional sources over segmented linear arrays, with potential improvements in recording and locating local sources. These results help reveal DAS array performance as a function of geometry.

58 GEOSCIENCES↗
DOE OSTI2022

Sustainability, Scalability and Resiliency of the Town of Innisfil Mobility-on-Demand Experiment: Preliminary Results, Analyses, and Lessons Learned: Preprint

In 2017, the Town of Innisfil, Ontario launched Innisfil Transit in partnership with Uber, a transportation network company, to provide a subsidized on-demand public mobility service as an alternative to investing in a new fixed-route bus service. The performance of Innisfil Transit is documented in a 2021 Ryerson University report which shows greater cost effectiveness of the mobility provided over the proposed bus alternative (Sweet, Mitra, and Benaroya 2021). This paper expands on those findings by assessing Innisfil Transit with respect to sustainability, scalability, and resiliency. First, we quantify the energy and emissions of this program relative to traditional transit and driving alone across varying powertrains. We then characterize a conservative first-order estimate of the percentage of US communities that fall within a similar spatial-demographic tier as Innisfil. Replicability also hinges on service cost and performance in comparison to average values for low-density transit in the US. Lastly, most transit agencies experienced a significant drop in demand (as much as 90%) with slowly rebounding ridership since the onset of the COVID-19 pandemic. The resiliency of the Innisfil program to the pressures induced by the pandemic is examined in comparison to other transit operations. The lessons learned across these three dimensions complement prior work to better understand the efficiency and sustainability of on-demand public mobility service for low-density communities like Innisfil.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident

In this paper, we quantify the temporal changes of air dose rates in the regional scale around the Fukushima Dai-ichi Nuclear Power Plant in Japan, and predict the spatial distribution of air dose rates in the future. We first apply the Bayesian geostatistical method developed by Wainwright et al. (2017) to integrate multiscale datasets including ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. We apply this method to the datasets from three years: 2014 to 2016. The temporal changes among the three integrated maps enables us to characterize the spatiotemporal dynamics of radiation air dose rates. The data-driven ecological decay model is then coupled with the integrated map to predict future dose rates. Results show that the air dose rates are decreasing consistently across the region. While slower in the forested region, the decrease is particularly significant in the town area. The decontamination has contributed to significant reduction of air dose rates. By 2026, the air dose rates will continue to decrease, and the area above 3.8 μSv/h will be almost fully contained within the non-residential forested zone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident

In this study, we quantify the temporal changes of air dose rates in the regional scale around the Fukushima Dai-ichi Nuclear Power Plant in Japan, and predict the spatial distribution of air dose rates in the future. We first apply the Bayesian geostatistical method developed by Wainwright et al. (2017) to integrate multiscale datasets including ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. We apply this method to the datasets from three years: 2014 to 2016. The temporal changes among the three integrated maps enables us to characterize the spatiotemporal dynamics of radiation air dose rates. The data-driven ecological decay model is then coupled with the integrated map to predict future dose rates. Results show that the air dose rates are decreasing consistently across the region. While slower in the forested region, the decrease is particularly significant in the town area. The decontamination has contributed to significant reduction of air dose rates. By 2026, the air dose rates will continue to decrease, and the area above 3.8 μSv/h will be almost fully contained within the non-residential forested zone.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Learning heterogeneous reaction kinetics from X-ray movies pixel-by-pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries 1 and electrocatalysts 2. Experimental characterizations of such materials by operando microscopy produce rich image datasets 3–6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation 7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Chueh, William↗
DOE OSTI2023

A practical method for modeling temporally-averaged ocean wave frequency-directional spectra for characterizing wave energy climates

Wave energy resource characterization investigations have been hindered because frequency-directional wave spectra are not broadly available for many coastal regions due to the insufficient spatial coverage of buoy observation networks and spectral wave model hindcast outputs. We address this problem by developing and validating a practical method for approximating temporally-averaged frequency-directional wave spectra averaged over periods of months or years from bulk wave parameters, which are available at a much greater coverage and resolution than frequency-directional wave spectra. While the temporally averaged frequency-directional wave spectrum over these periods cannot be used for analyzing a single sea state, it aggregates multiple sea states, identifies dominant wave energy systems representing wave climate, and resolves their spectral characteristics. Therefore, modelling temporally averaged frequency-directional wave spectra is of great value for planning and designing wave energy projects, e.g., resource characterization, site assessment, and conceptual design of wave energy converters. Temporally-averaged frequency-directional wave spectra and related important wave energy parameters approximated using this method are found to be more accurate than commonly used parametric wave spectrum models. This method can be applied to a wide range of wave climates given its universality and high accuracy. Also, the availability of bulk wave parameters from multi-decade high-resolution wave model hindcasts is increasing.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Modulation of North Atlantic Polar Low Activity and Associated Flow Patterns by Sudden Stratospheric Warmings

Abstract Polar lows (PLs) are intense maritime mesoscale cyclones that can pose hazards to coastal communities and marine operation in the Arctic. This study examines the impacts of sudden stratospheric warmings (SSWs) on PL activity in the subarctic North Atlantic. The 20 days following SSWs are characterized by tropospheric circulation anomalies resembling the negative phase of the North Atlantic Oscillation. PL activity decreases significantly over the Labrador Sea, which can be attributed to the infrequent occurrence of low static stability and strong environmental baroclinicity, as well as reduced surface turbulent heat fluxes. These results suggest that a skillful prediction of SSWs can improve the extended-range forecast of PL activity over the Labrador Sea. For the Nordic seas, the results imply that the spatial structure of an SSW event is important for the PL modulation through different tropospheric circulation patterns. Situations with increased PL frequency in the Nordic seas are characterized by SSWs centered close to northern Greenland occurring over a smaller area, and a tropospheric response featuring enhanced cold-air outbreaks over the Norwegian Sea. Conversely, PL activity is suppressed over the Nordic seas when the SSW favors the formation of a tropospheric anticyclone above Greenland and Scandinavia. Significance Statement This study investigates the relationships between polar lows (PLs) and sudden stratospheric warmings (SSWs) over the subarctic North Atlantic. A better understanding of the effect of SSWs on PL development has the potential to improve extended-range forecasts of PLs. It is shown that SSWs are responsible for the significantly suppressed regional PL activity over the Labrador Sea, suggesting that SSWs can serve as a predictor for the extended-range forecast of PLs over this region. Following SSW events, the thermodynamic state of atmosphere becomes more stable over the Labrador Sea and hinders the convective development of PLs. For the northern Nordic seas, the impacts of SSWs on PL activity are sensitive to the spatial structure of stratospheric warming.

Chang, Chuan-Chieh↗
DOE OSTI2021

Macroecological distributions of gene variants highlight the functional organization of soil microbial systems

Abstract The recent application of macroecological tools and concepts has made it possible to identify consistent patterns in the distribution of microbial biodiversity, which greatly improved our understanding of the microbial world at large scales. However, the distribution of microbial functions remains largely uncharted from the macroecological point of view. Here, we used macroecological models to examine how the genes encoding the functional capabilities of microorganisms are distributed within and across soil systems. Models built using functional gene array data from 818 soil microbial communities showed that the occupancy-frequency distributions of genes were bimodal in every studied site, and that their rank-abundance distributions were best described by a lognormal model. In addition, the relationships between gene occupancy and abundance were positive in all sites. This allowed us to identify genes with high abundance and ubiquitous distribution (core) and genes with low abundance and limited spatial distribution (satellites), and to show that they encode different sets of microbial traits. Common genes encode microbial traits related to the main biogeochemical cycles (C, N, P and S) while rare genes encode traits related to adaptation to environmental stresses, such as nutrient limitation, resistance to heavy metals and degradation of xenobiotics. Overall, this study characterized for the first time the distribution of microbial functional genes within soil systems, and highlight the interest of macroecological models for understanding the functional organization of microbial systems across spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Wave Resource Characterization Using an Unstructured Grid Modeling Approach

This paper presents a modeling study conducted on the central Oregon coast for wave resource characterization using the unstructured-grid SWAN model coupled with a nested-grid WWIII model. The flexibility of models of various spatial resolutions and the effects of open- boundary conditions simulated by a nested-grid WWIII model with different physics packages were evaluated. The model results demonstrate the advantage of the unstructured-grid modeling approach for flexible model resolution and good model skills in simulating the six wave resource parameters recommended by the International Electrotechnical Commission in comparison to the observed data in Year 2009 at National Data Buoy Center Buoy 46050. Notably, spectral analysis indicates that the ST4 physics package improves upon the model skill of the ST2 physics package for predicting wave power density for large waves, which is important for wave resource assessment, device load calculation, and risk management. In addition, bivariate distributions show the simulated sea state of maximum occurrence with the ST4 physics package matched the observed data better than that with the ST2 physics package. This study demonstrated that the unstructured-grid wave modeling approach, driven by the nested-grid regional WWIII outputs with the ST4 physics package, can efficiently provide accurate wave hindcasts to support wave resource characterization. Our study also suggests that wind effects need to be considered if the dimension of the model domain is greater than approximately 100 km, or O (10^2 km).

Wu, Wei-Cheng↗
DOE OSTI2023

Biophotonic rogue waves in red blood cell suspensions

Rogue waves are ubiquitous in nature, appearing in a variety of physical systems ranging from acoustics, microwave cavities, optical fibers, and resonators to plasmas, superfluids, and Bose–Einstein condensates. Unlike nonlinear solitary waves, rogue waves are extreme events that can occur even without nonlinearity by, for example, spontaneous synchronization of waves with different spatial frequencies in a linear system. Here, we report the observation of rogue-wave-like events in human red blood cell (RBC) suspensions under weak light illumination, characterized by an abnormal L-shaped probability distribution. Such biophotonic extreme events arise mostly due to the constructive interference of Mie-scattered waves from the suspended RBCs, whose biconcave shape and mutable orientation give rise to a time-dependent random phase modulation to an incident laser beam. We numerically simulate the beam propagation through the colloidal suspensions with added disorder in both spatial and temporal domains to mimic random scattering due to Brownian motion. In addition, at high power levels, nonlinear beam self-focusing is also observed, leading to a dual-exponential probability distribution associated with the formation of multiple soliton-like spots. Such rogue wave events should also exist in environments with cells of other species such as swimming bacteria, and understanding of their underlying physics may lead to unexpected biophotonic applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Universal model of Floquet operator Krylov space

It is shown that the stroboscopic time evolution under a Floquet unitary, in any spatial dimension, and of any Hermitian operator, can be mapped to an operator Krylov space, which is identical to that generated by the edge operator of the noninteracting Floquet transverse-field Ising model (TFIM) in one-spatial dimension, and with inhomogeneous Ising and transverse field couplings. The latter has four topological phases reflected by the absence (topologically trivial) or presence (topologically nontrivial) of edge modes at 0 and/or π quasienergies. It is shown that the Floquet dynamics share certain universal features characterized by how the Krylov parameters vary in the topological phase diagram of the Floquet TFIM with homogeneous couplings. Furthermore, these results are highlighted through examples, all chosen for numerical convenience to be in one spatial dimension: nonintegrable Floquet spin 1/2 chains and Floquet Z 3 clock model where the latter hosts period-tripled edge modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗