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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dynamic response of nanosecond repetitively pulsed discharges to combustion dynamics: regime transitions driven by flame oscillations

Abstract When using nanosecond repetitively pulsed discharges to actuate on dynamic combustion instabilities, the environment the discharge is created in is unsteady and changing on the timescale of the combustion processes. As a result, individual discharge pulses are triggered in a background gas that evolves at the timescale of combustion dynamics, and pulse-to-pulse variations may be observed during the instability cycle. Prior work has studied nanosecond pulsed discharges in pin-to-ring configurations used to control instabilities in lean-operating swirl-stabilized combustors, and observed variable discharge behavior. The focus of this work is on characterizing how the pulse-to-pulse discharge morphology, energy deposition, and actuation authority, evolve during the combustion instability cycle. This has important implications for designing effective plasma-assisted combustion control schemes. The discharge is observed in two distinct modes, a streamer corona and a nanosecond spark, with the occurrence of each regime directly linked to the phase of the combustor instability. Variation of pulse repetition frequency affects the total fraction of pulses in each mode, while variation of voltage affects the onset of the nanosecond spark mode. The transitions are described in terms of ratios of the relevant combustion and plasma timescales and the implications of this coupled interaction on the design of an effective control scheme is discussed.

Physics↗
DOE OSTI2022

Investigating the origin of observed central dips in radial metallicity profiles

ABSTRACT Radial metallicity trends provide a key indicator of physical processes such as star formation and radial gas migration within a galaxy. Large integral field unit surveys allow for detailed studies of these radial variations, with recent observations detecting central dips in the metallicity, which may trace the impact of various evolutionary processes. However, the origin of these dips has not been conclusively determined, with suggestions that they may be diagnostic dependent. In this paper, we use the Sloan Digital Sky Survey IV Mapping Nearby Galaxies at Apache Point Observatory survey to investigate whether the observed dips represent genuine decreases in the central metallicity, or whether they could be an artefact of the diagnostic used. Using a sub-sample of 758 local star-forming galaxies at low inclinations, we investigate in detail the impact of using different strong line diagnostics on the shapes of the returned profiles, and the prevalence of dips. We find no clear evidence of the dips being caused by changing values of the ionization parameter within galaxies. To investigate physical causes, we explore both global and spatially resolved parameters, finding that galaxies exhibiting central dips in the O3N2 metallicity profile have on average lower H α equivalent width values out to $R/R_{\rm {e}} \sim 1.5$, and higher values of DN(4000) in the central regions. We additionally find a higher prevalence of dips in galaxies with high stellar mass, and lower values of global specific star formation rate, suggesting a possible link to central quenching. Nevertheless, these results are dependent on the diagnostic used, suggesting caution should be taken when interpreting observed features in galaxy metallicity gradients.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Tidally Modulated Glacial Slip and Tremor at Helheim Glacier, Greenland

Numerical modeling of ice sheet motion and hence projections of global sea level rise require information about the evolving subglacial environment, which unfortunately remains largely unknown due to its difficulty of access. Here we advance such subglacial observations by reporting multi–year observations of seismic tremor likely associated with glacier sliding at Helheim Glacier. This association is confirmed by correlation analysis between tremor power and multiple environmental forcings on different timescales. Variations of the observed tremor power indicate that different factors affect glacial sliding on different timescales. Effective pressure may control glacial sliding on long (seasonal/annual) timescales, while tidal forcing modulates the sliding rate and tremor power on short (hourly/daily) timescales. Polarization results suggest that the tremor source comes from an upstream subglacial ridge. This observation provides insights on how different factors should be included in ice sheet modeling and how their timescales of variability play an essential role.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Resolving surface potential variation in Ge/MoS 2 heterostructures with Kelvin probe force microscopy

In this work, we employ an atomic force microscopy-based technique, Kelvin probe force microscopy, to analyze heterogeneities of four different 2D/3D Ge/MoS 2 heterostructures with Ge chemical vapor deposition (CVD) time. High-contrast spatially resolved contact potential difference (CPD) maps reveal the evolution of the samples by Ge deposition. The CPD map in an as-prepared sample does not display any heterogeneity, but CPD contrasts along the grain boundaries are obviously noticed as Ge is deposited on MoS 2 . With a sufficiently long Ge CVD deposition time, strong grain-to-grain CPD variations over the 2D/3D heterostructures are observed. The results show the variations of the work function from grain to grain that are attributed to the strain induced by the Ge island formation on the cracked MoS2 initiated by sulfur vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-Epoch Optical Spectroscopy Variability of the Changing-Look AGN Mrk 883

In this work, we present multi-epoch optical spectra of the Seyfert 1.9 galaxy Mrk 883. Data were obtained with the Gran Telescopio Canarias and the MEGARA Integral Field Unit mode, archival data from the SDSS-IV MaNGA Survey and the SDSS-I Legacy Survey, and new spectroscopic observations obtained at San Pedro Mártir Observatory. We report the appearance of the broad component of Hβ emission line, showing a maximum FWHM ∼ 5927 ± 481 km s−1 in the MaNGA spectra, finding evidence for a change from Seyfert 1.9 (23 June 2003) to Seyfert 1.8 (18 May 2018). The observed changing-look variation from Sy1.9 to Sy1.8 has a timescale Δt ∼15 y. In addition, we observe profile and flux broad emission line variability from 2018 to 2023, and a wind component in [OIII]5007 Å, with a maximum FWHM = 1758 ± 178 km s−1, detected on 15 April 2023. In all epochs, variability of the broad lines was found to be disconnected from the optical continuum emission, which shows little or no variations. These results suggest that an ionized-driven wind in the polar direction could be a possible scenario to explain the observed changing-look variations.

Benítez, Erika (ORCID:0000000310182613)↗
DOE OSTI2023

The battle of clean and dirty qubits in the era of partial error correction

When error correction becomes possible it will be necessary to dedicate a large number of physical qubits to each logical qubit. Error correction allows for deeper circuits to be run, but each additional physical qubit can potentially contribute an exponential increase in computational space, so there is a trade-off between using qubits for error correction or using them as noisy qubits. In this work, we look at the effects of using noisy qubits in conjunction with noiseless qubits (an idealized model for error-corrected qubits), which we call the “clean and dirty” setup. We employ analytical models and numerical simulations to characterize this setup. Numerically we show the appearance of Noise-Induced Barren Plateaus (NIBPs), i.e., an exponential concentration of observables caused by noise, in an Ising model Hamiltonian variational ansatz circuit. We observe this even if only a single qubit is noisy and given a deep enough circuit, suggesting that NIBPs cannot be fully overcome simply by error-correcting a subset of the qubits. On the positive side, we find that for every noiseless qubit in the circuit, there is an exponential suppression in the concentration of gradient observables, showing the benefit of partial error correction. Finally, our analytical models corroborate these findings by showing that observables concentrate with a scaling in the exponent related to the ratio of dirty-to-total qubits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The battle of clean and dirty qubits in the era of partial error correction

When error correction becomes possible it will be necessary to dedicate a large number of physical qubits to each logical qubit. Error correction allows for deeper circuits to be run, but each additional physical qubit can potentially contribute an exponential increase in computational space, so there is a trade-off between using qubits for error correction or using them as noisy qubits. In this work we look at the effects of using noisy qubits in conjunction with noiseless qubits (an idealized model for error-corrected qubits), which we call the "clean and dirty" setup. We employ analytical models and numerical simulations to characterize this setup. Numerically we show the appearance of Noise-Induced Barren Plateaus (NIBPs), i.e., an exponential concentration of observables caused by noise, in an Ising model Hamiltonian variational ansatz circuit. We observe this even if only a single qubit is noisy and given a deep enough circuit, suggesting that NIBPs cannot be fully overcome simply by error-correcting a subset of the qubits. On the positive side, we find that for every noiseless qubit in the circuit, there is an exponential suppression in concentration of gradient observables, showing the benefit of partial error correction. Finally, our analytical models corroborate these findings by showing that observables concentrate with a scaling in the exponent related to the ratio of dirty-to-total qubits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Two major chromosome evolution events with unrivaled conserved gene content in pomegranate

Pomegranate has a unique evolutionary history given that different cultivars have eight or nine bivalent chromosomes with possible crossability between the two classes. Therefore, it is important to study chromosome evolution in pomegranate to understand the dynamics of its population. Here, we de novo assembled the Azerbaijani cultivar “Azerbaijan guloyshasi” (AG2017; 2n = 16) and re-sequenced six cultivars to track the evolution of pomegranate and to compare it with previously published de novo assembled and re-sequenced cultivars. High synteny was observed between AG2017, Bhagawa (2n = 16), Tunisia (2n = 16), and Dabenzi (2n = 18), but these four cultivars diverged from the cultivar Taishanhong (2n = 18) with several rearrangements indicating the presence of two major chromosome evolution events. Major presence/absence variations were not observed as >99% of the five genomes aligned across the cultivars, while >99% of the pan-genic content was represented by Tunisia and Taishanhong only. We also revisited the divergence between soft- and hard-seeded cultivars with less structured population genomic data, compared to previous studies, to refine the selected genomic regions and detect global migration routes for pomegranate. We reported a unique admixture between soft- and hard-seeded cultivars that can be exploited to improve the diversity, quality, and adaptability of local pomegranate varieties around the world. Our study adds body knowledge to understanding the evolution of the pomegranate genome and its implications for the population structure of global pomegranate diversity, as well as planning breeding programs aiming to develop improved cultivars.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Mesoscale structural gradients in human tooth enamel

The outstanding mechanical and chemical properties of dental enamel emerge from its complex hierarchical architecture. An accurate, detailed multiscale model of the structure and composition of enamel is important for understanding lesion formation in tooth decay (dental caries), enamel development (amelogenesis) and associated pathologies (e.g., amelogenesis imperfecta or molar hypomineralization), and minimally invasive dentistry. Although features at length scales smaller than 100 nm (individual crystallites) and greater than 50 µm (multiple rods) are well understood, competing field of view and sampling considerations have hindered exploration of mesoscale features, i.e., at the level of single enamel rods and the interrod enamel (1 to 10 µm). Here, we combine synchrotron X-ray diffraction at submicrometer resolution, analysis of crystallite orientation distribution, and unsupervised machine learning to show that crystallographic parameters differ between rod head and rod tail/interrod enamel. This variation strongly suggests that crystallites in different microarchitectural domains also differ in their composition. Thus, we use a dilute linear model to predict the concentrations of minority ions in hydroxylapatite (Mg 2+ and CO 3 2- /Na + ) that plausibly explain the observed lattice parameter variations. While differences within samples are highly significant and of similar magnitude, absolute values and the sign of the effect for some crystallographic parameters show interindividual variation that warrants further investigation. In conclusion, by revealing additional complexity at the rod/interrod level of human enamel and leaving open the possibility of modulation across larger length scales, these results inform future investigations into mechanisms governing amelogenesis and introduce another feature to consider when modeling the mechanical and chemical performance of enamel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Measurement of seasonal variations of the NSLS-II circumference and energy

Routine beam-based characterization of the NSLS-II storage ring indicated probable seasonal variations of the ring circumference and energy. We arranged regular direct measurements of the ring circumference during 2023 and compared the results with the archived data of the magnet and undulator settings. A clear correlation between the ring circumference and energy was observed. These seasonal variations of the ring energy are found to be the main reason for regular lattice corrections required to keep the machine performance stable for user operations. Finally, the measurement techniques and results are discussed in this article.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Direct Observation of the Pressure-Induced Structural Variation in Gold Nanoclusters and the Correlated Optical Response

The ability to gradually modify the atomic structures of nanomaterials and directly identify such structural variation is important in nanoscience research. Here, we present the first example of a high-pressure single-crystal X-ray diffraction analysis of atomically precise metal nanoclusters. The pressure-dependent, subangstrom structural evolution of an ultrasmall gold nanoparticle, Au 25 S 18 , has been directly identified. We found that a 0.1 Å decrease of the Au–Au bond length could induce a blue-shift of 30 nm in the photoluminescence spectra of gold nanoclusters. From theoretical calculations, the origins of the blue-shift and enhanced photoluminescence under pressure are investigated, which are ascribed to molecular orbital symmetry and conformational locking, respectively. Here, the combination of the high-pressure in situ X-ray results with both theoretical and experimental optical spectra provides a direct and generalizable avenue to unveil the underlying structure–property relations for nanoclusters and nanoparticles which cannot be obtained through traditional physical chemistry measurements.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Measurement report: Cloud condensation nuclei activity and its variation with organic oxidation level and volatility observed during an aerosol life cycle intensive operational period (ALC-IOP)

Abstract. Cloud condensation nuclei (CCN) spectrum and the CCN activated fraction of size-resolved aerosols (SR-CCN) were measured at a rural site on Long Island during the Department of Energy (DOE) aerosol life cycle intensive operational period (ALC-IOP) from 15 July to 15 August 2011. During the last week of the ALC-IOP, the dependence of the activated fraction on aerosol volatility was characterized by sampling downstream of a thermodenuder (TD) operated at temperatures up to 100 ∘C. Here we present aerosol properties, including aerosol total number concentration, CCN spectrum, and the CCN hygroscopicity, for air masses of representative origins during the ALC-IOP. The hygroscopicity of organic species in the aerosol is derived from CCN hygroscopicity and chemical composition. The dependence of organic hygroscopicity on the organic oxidation level (e.g., atomic O:C ratio) agrees well with theoretical predictions and results from previous laboratory and field studies. The derived κorg and O:C ratio first increase as TD temperature increases from 20 ∘C (i.e., ambient temperature) to 50 or 75 ∘C and then decrease as TD temperature further increases to 100 ∘C. The initial increases of O:C and κorg with TD temperature below 50 ∘C are likely due to evaporation of more volatile organics with relatively lower O:C and hygroscopicity such as primary organic aerosol. At the high TD temperatures, the decreases of O:C and κorg indicate that evaporated organics were more oxygenated and had lower molecular weights. These trends are different from previous laboratory experiments and field observations, which reported that organic O:C increased monotonically with increasing TD temperature, whereas κorg decreased with the TD temperature. One possible reason is that previous studies were either focused on laboratory-generated secondary organic aerosol (SOA) or based on field observations at locations more dominated by SOA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The impact of anisotropic redshift distributions on angular clustering

A leading way to constrain physical theories from cosmological observations is to test their predictions for the angular clustering statistics of matter tracers, a technique that is set to become ever more central with the next generation of large imaging surveys. Interpretation of this clustering requires knowledge of the projection kernel, or the redshift distribution of the sources, and the typical assumption is an isotropic redshift distribution for the objects. However, variations in the kernel are expected across the survey footprint due to photometric variations and residual observational systematic effects. Here, we develop the formalism for anisotropic projection and present several limiting cases that elucidate the key aspects. We quantify the impact of anisotropies in the redshift distribution on a general class of angular two-point statistics. In particular, we identify a mode-coupling effect that can add power to auto-correlations, including galaxy clustering and cosmic shear, and remove it from certain cross-correlations. If the projection anisotropy is primarily at large scales, the mode-coupling depends upon its variance as a function of redshift; furthermore, it is often of similar shape to the signal. In contrast, the cross-correlation of a field whose selection function is anisotropic with another one featuring no such variations — such as CMB lensing — is immune to these effects. We discuss explicitly several special cases of the general formalism including galaxy clustering, galaxy-galaxy lensing, cosmic shear and cross-correlations with CMB lensing, and publicly release a code to compute the biases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Exploring theoretical uncertainties in the hydrodynamic description of relativistic heavy-ion collisions

We explore theoretical uncertainties in the hydrodynamic description of relativistic heavy-ion collisions by examining the full nonlinear causality conditions and quantifying the second-order transport coefficients' role on flow observables. The causality conditions impose physical constraints on the maximum allowed values of inverse Reynolds numbers during the hydrodynamic evolution. Including additional second-order gradient terms in the Denicol-Niemi-Molnár-Rischke (DNMR) theory significantly shrinks the casual regions compared to those in the Israel-Stewart hydrodynamics. For Au + Au collisions, we find the variations of flow observables are small with and without imposing the necessary causality conditions, suggesting a robust extraction of the quark-gluon plasma's transport coefficients in previous model-to-data comparisons. However, sizable sensitivity is present in small p + Au collisions, which poses challenges to study the small systems' collectivity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Environmental controls on simulated deep moist convection initiation occurring during RELAMPAGO-CACTI

This study synthesizes the results of 13 high-resolution simulations of deep convective updrafts forming over idealized terrain using environments observed during the RELAMPAGO and CACTI field projects. Using composite soundings from multiple observed cases, and variations upon them, we explore the sensitivity of updraft properties (e.g., size, buoyancy, and vertical pressure gradient forces) to influences of environmental relative humidity, wind shear, and mesoscale orographic forcing that support or suppress deep convection initiation (CI). Emphasis is placed on differentiating physical processes affecting the development of updrafts (e.g., entrainment-driven dilution of updrafts) in environments typifying observed successful and null (i.e., no CI despite affirmative operational forecasts) CI events. Thermally-induced mesoscale orographic lift favors the production of deep updrafts originating from ~1–2-km-wide boundary layer thermals. Simulations without terrain forcing required much larger ( ~5-km-wide) thermals to yield precipitating convection. CI outcome was quite sensitive to environmental relative humidity; updrafts with increased buoyancy, depth, and intensity thrived in otherwise inhospitable environments by simply increasing the free tropospheric relative humidity. This implicates the entrainment of free-tropospheric air into updrafts as a prominent governor of CI, consistent with previous studies. Sensitivity of CI to the environmental wind is manifested by: 1) low-level flow affecting the strength and depth of mesoscale convergence along the terrain, and 2) clouds encountering updraft-suppressing pressure gradient forces while interacting with vertical wind shear in the free-troposphere. Among the ensemble of thermals occurring in each simulation, the widest deep updrafts in each simulation were the most sensitive to environmental influences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensor Distortion Effects in Photon Monte Carlo Simulations

We present a detailed method to simulating sensor distortions using a photon and electron Monte Carlo method. We use three-dimensional electrostatic simulations to parameterize the perturbed electric field profile for nonideal sensor details. We follow the conversion of simulated photons, and the subsequent response of the converted electrons to the electric field pattern. These nonideal sensor details can be implemented efficiently in a Monte Carlo approach. We demonstrate that the nonideal sensor distortions have a variety of observable consequence including the modification of the astrometric pattern; the distortion of the electron diffusion size and shape; and the distortion of flats. We show analytic validation of the diffusion physics, reproduce two kinds of edge distortion, and show qualitative validation of field-free regions, lithography errors, and fringing. We also demonstrate that there are two related effects of doping variation having different observable consequences. We show that field distortions from accumulated electrons lead to intensity-dependent point-spread functions and the sublinear variance in flats. The method is implemented in the Photon Simulator and the code is publicly available.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A High-resolution Regional Wave Resource Characterization For The U.S. West Coast

Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.

Wang, Taiping↗
DOE OSTI2022

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗