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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Depth-dependent links between microbial taxa and nitrous oxide emissions in a long-term cotton cropping system employing soil health practices

Long-term management practices can shape soil microbial communities in ways that influence nitrogen (N) dynamics and nitrous oxide (N 2 O) emissions. We leverage a 41-year continuous cotton cropping experiment with contrasting tillage, cover cropping, and N fertilization regimes to investigate how these long-term strategies influence soil microbial communities and their associations with N 2 O fluxes during the cotton growing season. Using 16S rRNA gene metabarcoding, we assessed microbial composition in surface and subsurface soils and evaluated its relationship with temporal N 2 O emissions. Among the management practices, N fertilization – a known driver of N 2 O emissions – had the strongest effect on microbial community composition and was linked to a greater number of taxa correlated to N 2 O emissions, particularly in surface soils. Soil pH emerged as a key variable influencing microbial structure across depth and was negatively associated with both N 2 O emissions and microbial composition in the surface layers of fertilized soils. In total, 57 archaeal/bacterial taxa were correlated with N 2 O fluxes, but only seven were shared across depths, suggesting distinct microbial contributors in surface and subsurface soils. Several of these taxa have been previously reported to be associated with N and C cycling processes such as nitrate respiration or carbon turnover, indicating functional context to their correlation with N 2 O fluxes. Temporal shifts in the abundance of key taxa aligned with seasonal peaks in N 2 O emissions, notably in early and late August, and were most pronounced under conventional tillage, hairy vetch cover cropping, and N fertilization. While 16S-based associations cannot confirm functional gene presence or activity, these findings demonstrate that long-term fertilization and associated soil acidification are dominant drivers of microbial shifts linked to N 2 O emissions and highlight the importance of accounting for depth-specific and seasonal microbial dynamics when evaluating management impacts on greenhouse gas emissions.

16S rRNA gene sequencing↗
NASA NTRS2003

On the Computation of Space-Time Correlations by Large-Eddy Simulation

Numerical comparisons in decaying isotropic turbulence suggest that there exist discrepancies in time correlations evaluated by DNS and LES using eddy-viscosity-type SGS models. This is consistent with the previous observations in forced isotropic turbulence. Therefore, forcing is not the main cause of the discrepancies. Comparisons among different SGS models in the LES also indicate that the model choice affects the time correlations in the LES. The multi-scale LES method using the dynamic Smagorinsky model on the small scale equation is the most accurate of the all models, the classic Smagorinsky model is the least accurate and the dynamic Smagorinsky model and spectral eddy viscosity model give intermediate results with small differences. The generalized sweeping hypothesis implies that time correlations in decaying isotropic turbulence are mainly determined by the instantaneous energy spectra and sweeping velocities. The analysis based on the sweeping hypothesis explains the discrepancies in our numerical simulations: the LES overpredicts the decorrelation time scales because the sweeping velocities are smaller than the DNS values, and underpredicts the magnitudes of time correlations because the energy spectrum levels are lower than the DNS ones. Since the sweeping velocity is determined by the energy spectra, one concludes that an accurate prediction of the instantaneous energy spectra guarantees the accuracy of time correlations. An analytical expression of sound power spectra based on Lighthill's theory and the quasi-normal closure assumption suggests that the sound power spectra are sensitive to errors in time correlations. Small errors in time correlations can cause significant errors in the sound power spectra, which exhibit a sizable drop at moderate to high frequencies accompanied by a shift of the peaks to lower frequencies. Based on the above analysis, two possible ways to improve the acoustic power spectrum predictions can be considered. The first is to construct better SGS models to improve the LES accuracy for time correlations. The second is to remedy the temporal statistics of the Lighthill stress tensor in order to "recover" the contribution from the unresolved scales in LES to time correlations.

He, Guo-Wei↗
NASA NTRS1985

Subseasonal and interannual variations of tropical convection and the El Nino/Southern Oscillation

It was found that during the northern winter, fluctuation in tropical convection is dominated by eastware propagating cloud clusters from the Indian Ocean. Most of these clusters reach as far as the central Pacific. Longitude time sections of outgoing longwave radiation (OLR) anomaly along the equator show that there are about 3 to 4 such episodes each winter. Also, simultaneous OLR anomalies over the equatorial central Pacific (ECP) and the maritime continent (MC) are negatively correlated and their variations are dominated by a 40 to 60 day period, suggesting the presence of a standing wave phenomenon. Such combination of propagating and standing phenomena can be captured by the extended empirical orthogonal function (EEOF) analysis. The EEOF method combines the temporal as well as the spatial correlation information to produce eigenmodes which have space time dependence. A 5 day and a 10 day lag in addition to the simultaneous spatial correlation is used.

Lau, K. M.↗
DOE OSTI2021

Designing high-power, octave spanning entangled photon sources for quantum spectroscopy

Entangled photon spectroscopy is a nascent field that has important implications for measurement and imaging across chemical, biology, and materials fields. Entangled photon spectroscopy potentially offers improved spatial and temporal-frequency resolutions, increased cross sections for multiphoton and nonlinear measurements, and new abilities in inducing or measuring quantum correlations. A critical step in enabling entangled photon spectroscopies is the creation of high-flux entangled sources that can use conventional detectors as well as provide redundancy for the losses in realistic samples. Here, we report a periodically poled, chirped, lithium tantalate platform that generates entangled photon pairs with ~10 -7 efficiency. For a near watt level diode laser, this results in a near μW-level flux. The single photon per mode limit that is necessary to maintain non-classical photon behavior is still satisfied by distributing this power over up to an octave-spanning bandwidth. The spectral–temporal photon correlations are observed via a Michelson-type interferometer that measures the broadband Hong–Ou–Mandel two-photon interference. A coherence time of 245 fs for a 10 nm bandwidth in the collinear case and a coherence time of 62 fs for a 125 nm bandwidth in the non-collinear case are measured using a CW pump laser and, essentially, collecting the full photon cone. We outline in detail the numerical methods used for designing and tailoring the entangled photons source, such as changing center wavelength or bandwidth, with the ultimate aim of increasing the availability of high-flux UV–Vis entangled photon sources in the optical spectroscopy community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact

Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing body of new traffic speed prediction models have been designed that achieved high accuracy and large-scale prediction. However, existing studies have two major limitations. First, they predict aggregated traffic speed rather than lane-level traffic speed; second, most studies ignore the impact of other traffic flow parameters in speed prediction. To address these issues, the authors propose a two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact. In this model, the authors first introduce a new data conversion method that converts raw traffic speed data and volume data into spatial–temporal multi-channel matrices. Then the authors carefully design a two-stream deep neural network to effectively learn the features and correlations between individual lanes, in the spatial–temporal dimensions, and between speed and volume. Accordingly, a new loss function that considers the volume impact in speed prediction is developed. A case study using 1-year data validates the TM-CNN model and demonstrates its superiority. This paper contributes to two research areas: (1) traffic speed prediction, and (2) multi-lane traffic flow study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multitiered computational methodology for extracting three-dimensional rotational diffusion coefficients from x-ray photon correlation spectroscopy data without structural information

X-ray photon correlation spectroscopy (XPCS) is a powerful technique for analyzing particle systems by investigating their dynamics in suspensions across a broad range of temporal and spatial scales. This is done by illuminating samples with coherent x-ray beams and calculating the correlation function of the obtained x-ray scattering images. XPCS is uniquely suited for studying Brownian dynamics, consisting of translational and rotational diffusion. While traditional XPCS image analysis techniques can extract translational diffusion components, they are unable to estimate rotational diffusion coefficients. Here, we introduce a methodology that combines the angular-temporal cross-correlation analysis and a algorithmic framework called Multi-Tiered Estimation for Correlation Spectroscopy in 3D for estimating three-dimensional rotational diffusion coefficients from XPCS images of three-dimensional particle systems. We demonstrate our methodology for extracting rotational diffusion coefficients from XPCS data by applying it to simulated noisy x-ray images of systems of crossing nanotubes and proteins that evolve under translational and rotational Brownian motion for different diffusion rates. Furthermore, our results show that our approach determines rotational diffusion coefficients within a few percent error.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Using an Extended Kalman Filter Learning Algorithm for Feed-Forward Neural Networks to Describe Tracer Correlations

In this study a new extended Kalman filter (EKF) learning algorithm for feed-forward neural networks (FFN) is used. With the EKF approach, the training of the FFN can be seen as state estimation for a non-linear stationary process. The EKF method gives excellent convergence performances provided that there is enough computer core memory and that the machine precision is high. Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). The neural network was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9997. The neural network Fortran code used is available for download.

Lary, David J.↗
DOE OSTI2022

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗
DOE OSTI2026

Stochastic equilibrium Raman spectroscopy (STERS)

In this manuscript, we propose a new method for cavity- and surface-enhanced Raman spectroscopy (SERS) with improved temporal resolution in the measurement of stochastic Raman spectral fluctuations. Our approach combines Fourier spectroscopy and photon correlation to decouple the integration time from the temporal resolution. Using statistical optics Monte Carlo simulations, we establish the relationship between time resolution and Raman signal strength, revealing that typical Raman spectral fluctuations, commensurate with molecular conformational dynamics, can theoretically be resolved on micro- to millisecond timescales. The method can further extract average single-molecule dynamics from small sub-ensembles, thereby potentially mitigating challenges in achieving strictly single-molecule isolation on SERS substrates.

Cobb-Bruno, Colburn [University of California, Ber↗
NASA NTRS1989

Three dimensional simulation of spatial and temporal variability of stratospheric hydrogen chloride

Spatial and temporal variability of atmospheric HCl columns are calculated for January 1979 using a three-dimensional chemistry-transport model designed to provide the best possible representation of stratospheric transport. Large spatial and temporal variability of the HCl columns is shown to be correlated with lower stratospheric potential vorticity and thus to be of dynamical origin. Systematic longitudinal structure is correlated with planetary wave structure. These results can help place spatially and temporally isolated column and profile measurements in a regional and/or global perspective.

Kaye, Jack A.↗
NASA NTRS1994

Analysis of a 7 year tropospheric ozone vertical distribution at the Observatoire de Haute Provence

A seven year (1984-90) climatology of tropospheric vertical ozone soundings, performed by electrochemical sondes at the OHP (44 deg N, 6 deg E, 700 m ASL) in Southern France, is presented. Its seasonal variation shows a broad spring/summer maximum in the troposphere. The contribution of photochemical ozone production and transport from the stratosphere to this seasonal variation are studied by a correlative analysis of ozone concentrations and meteorological variables, with emphasis on potential vorticity. This analysis shows the impact of dynamical and photochemical processes on the spatial and temporal ozone variability. In particular, a positive correlation (r = 04.0, significance greater than 99.9 percent) of ozone with potential vorticity is observed in the middle troposphere, reflecting the impact of stratosphere-troposphere exchange on the vertical ozone distribution.

Beekmann, Matthias↗
DOE OSTI2015

Ostreopsis cf. ovata dynamics in the NW Mediterranean Sea in relation to biotic and abiotic factors

An expansion of the distribution of Ostreopsis cf. ovata, a dinoflagellate which produces palytoxin-like compounds, has been reported in recent years. Economical and social interests are affected by blooms, as they are responsible for respiratory and skin problems in humans and may cause damage to marine organisms. In order to identify the most influential environmental factors that trigger proliferations of O. cf. ovata in the area of the adjacent shallow rocky coast of the Ebro Delta (NW Mediterranean Sea) a three-year survey was performed on the metaphytic microalgae community growing on the macrophytes Jania rubens and Corallina elongata. Small-size diatoms were more abundant than dinoflagellates; O. cf. ovata was identified as the only species present from the genus. Seawater temperature was the primary driver defining the ecological niche of O. cf. ovata. Freshwater and groundwater fluxes were more pronounced in southern than in northern sites, which may have resulted in a distinct O. cf. ovata spatial distribution, with the highest records of abundance and more frequent blooms in the north. In consequence, negative correlations between the abundance of O. cf. ovata and nitrate concentrations and significant positive correlation with salinity were observed. The temporal pattern of O. cf. ovata dynamics from mid-July to early-November is probably due to the fact that this species is observed only above a certain threshold temperature of seawater. Metaphytic cells of O. cf. ovata were smaller in the northern site than in the south, possibly as a result of an increase in cell division, coinciding with higher abundance, and this could be an indicator of favorable conditions. Toxicity in planktonic cells was negatively correlated with cell abundance in the water column, achieving maximum concentrations of 25 pg. PLTX eq cell{sup −1}. - Highlights: • Presence of a single Ostreopsis genotype in confirmed through qPCR. • Temperature confirmed as the most important parameter affecting its distribution. • Salinity positively correlated with Ostreopsis cf. ovata abundance. • Ostreopsis cf. ovata has a restricted ecological niche. • Toxicity in Ostreopsis planktonic cells negatively correlated with cell abundance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Time-Resolved Hanbury Brown–Twiss Interferometry of On-Chip Biphoton Frequency Combs Using Vernier Phase Modulation

Biphoton frequency combs (BFCs) are promising quantum sources for large-scale and high-dimensional quantum information and networking systems. In this context, the spectral purity of individual frequency bins will be critical for realizing quantum networking protocols like teleportation and entanglement swapping. Measurement of the temporal autocorrelation function of the unheralded signal or idler photons comprising the BFC is a key tool for characterizing their spectral purity and in turn verifying the utility of the biphoton state for networking protocols. Yet the experimentally obtainable precision for measuring BFC correlation functions is often severely limited by detector jitter. The fine temporal features in the correlation function—not only of practical value in quantum information, but also of fundamental interest in the study of quantum optics—are lost as a result. We propose a scheme to circumvent this challenge through electro-optic phase modulation, experimentally demonstrating time-resolved Hanbury Brown–Twiss characterization of BFCs generated from an integrated 40.5-GHz Si 3 N 4 microring, up to a 3×3-dimensional two-qutrit Hilbert space. Through slight detuning of the electro-optic drive frequency from the comb’s free spectral range, our approach leverages Vernier principles to magnify temporal features, which would otherwise be averaged out by detector jitter. We demonstrate our approach under both continuous-wave and pulsed-pumping regimes, finding excellent agreement with theory. In conclusion, our method reveals not only the collective statistics of the contributing frequency bins but also their temporal shapes—features lost in standard fully integrated autocorrelation measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Regional correlations between [ 11 C]PIB PET and post-mortem burden of amyloid-beta pathology in a diverse neuropathological cohort

Imaging-pathological correlation studies show that in vivo amyloid-β (Aβ) positron emission tomography (PET) strongly predicts the presence of significant Aβ pathology at autopsy. We sought to determine whether regional PiB-PET uptake would improve sensitivity for amyloid detection in comparison with global measures (experiment 1), and to estimate the relative contributions of different Aβ aggregates to in vivo PET signal (experiment 2). In experiment 1, 54 subjects with [11C] PiB-PET during life and postmortem neuropathologic examination (85.2% with dementia, interval from PET to autopsy 3.1 ± 1.9 years) were included. We assessed Thal amyloid phase (N = 36) and CERAD score (N = 54) versus both global and regional PiB SUVRs. In experiment 2 (N = 42), PiB SUVR and post-mortem amyloid β burden was analyzed in five customized regions of interest matching regions sampled at autopsy. We assessed the relative contribution of neuritic plaques (NPs), diffuse plaques (DPs) and cerebral amyloid angiopathy (CAA) to regional PIB SUVR using multi-linear regression. In experiment 1, there were no differences in Area Under the Curve for amyloid phase ≥ A2 and CERAD score ≥ C2 between global and highest regional PiB SUVR (p = 0.186 and 0.230). In experiment 2, when NPs, DPs, and/or CAA were included in the same model, moderate to severe NPs were independently correlated with PiB SUVR in all regions except for the inferior temporal and calcarine ROI (β = 0.414–0.804, p < 0.05), whereas DPs were independently correlated with PiB SUVR in the angular gyrus ROI (β = 0.446, p = 0.010). CAA was also associated with PiB SUVR in the inferior temporal and calcarine ROI (β = 0.222–0.355, p < 0.05). In conclusion, global PiB-PET SUVR performed as well as regional values for amyloid detection in our cohort. The substrate-specific binding of PiB might differ among the brain specific regions.

Neurosciences & Neurology↗
NASA NTRS2007

Correlations Between Sea-Surface Salinity Tendencies and Freshwater Fluxes in the Pacific Ocean

Temporal changes in sea-surface salinity (SSS) from 21 years of a high resolution model integration of the Pacific Ocean are correlated with the freshwater flux that was used to force the integration. The correlations are calculated on a 1 x10 grid, and on a monthly scale to assess the possibility of deducing evaporation minus precipitation (E-P) fields from the salinity measurements to be taken by the upcoming Aquarius/SAC-D mission. Correlations between the monthly mean E-P fields and monthly mean SSS temporal tendencies are mainly zonally-oriented, and are highest where the local precipitation is relatively high. Nonseasonal (deviations from the monthly mean) correlations are highest along mid-latitude storm tracks and are relatively small in the tropics. The response of the model's surface salinity to surface forcing is very complex, and retrievals of freshwater fluxes from SSS measurements alone will require consideration of other processes, including horizontal advection and vertical mixing, rather than a simple balance between the two.

Li, Zhen↗
DOE OSTI2019

Spatio‐temporally Resolved Methane Fluxes From the Los Angeles Megacity

Abstract We combine sustained observations from a network of atmospheric monitoring stations with inverse modeling to uniquely obtain spatiotemporal (3‐km, 4‐day) estimates of methane emissions from the Los Angeles megacity and the broader South Coast Air Basin for 2015–2016. Our inversions use customized and validated high‐fidelity meteorological output from Weather Research Forecasting and Stochastic Time‐Inverted Lagrangian model for South Coast Air Basin and innovatively employ a model resolution matrix‐based metric to disentangle the spatiotemporal information content of observations as manifested through estimated fluxes. We partially track and constrain fluxes from the Aliso Canyon natural gas leak and detect closure of the Puente Hills landfill, with no prior information. Our annually aggregated fluxes and their uncertainty excluding the Aliso Canyon leak period lie within the uncertainty bounds of the fluxes reported by the previous studies. Spatially, major sources of CH 4 emissions in the basin were correlated with CH 4 ‐emitting infrastructure. Temporally, our findings show large seasonal variations in CH 4 fluxes with significantly higher fluxes in winter in comparison to summer months, which is consistent with natural gas demand and anticorrelated with air temperature. Overall, this is the first study that utilizes inversions to detect both enhancement (Aliso Canyon leak) and reduction (Puente Hills) in CH 4 fluxes due to the unintended events and policy decisions and thereby demonstrates the utility of inverse modeling for identifying variations in fluxes at fine spatiotemporal resolution.

Yadav, Vineet↗
DOE OSTI2019

Dissipative and fast-timescale phenomena in superconductors

This project explored new effects and regimes that unfold in superconductors as they are pushed to ex treme and unprecedented conditions of electric field, power densities, vortex velocities, etc. Besides their own novelty, these phenomena yield fundamental in formation about the superconducting state and its parameters, as well as its practical limits for techno logical applications. Furthermore some of these ef fects (such as formation of phase slip processes and the acceleration of superfluid) are time dependent on time scales such as quasiparticle-phonon energy re laxation and gap relaxation. This project used fast low-duty-cycle pulsed signals to first of all access these regimes without excessive heating and secondly to observe directly in the time domain the temporal unfolding of these phenomena on nanosecond time scales. This project led to the discovery of new effects in the transport behavior in superconductors, provided new information on fundamental parameters, and helped establish intrinsic strengths and limitations of different superconducting materials for ap plications. The primary tools developed for extending the range of measurable dissipation densities and observation of short time-scale phenomena were fast pulsed-current and pulsed-voltage sources, and fast high-CM-rejection detection circuitry. This allowed conducting measurements at power densities in the 10 10 W/cm 3 range, and at E ~ 1 kV/cm and v Φ ~10 km/s. Also developed was the ability to simultaneously track current I(t) and voltage V (t) and cross correlate them with sub-nanosecond temporal resolution. A recent angle of this project was the exploration of subtle phenomena at low current densities, especially for the magnetic field orientation parallel to the plane of the films. Through modifications of the pulsed tube closed cycle cryostat, we developed methods for attaining low-noise and high temperature-stability conditions. This led to the observation of novel dimensional effects related to the mixed state and vortex matter, and to a new type of magnetoresistance oscillation.

36 MATERIALS SCIENCE↗