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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Experimental study of high-k turbulence during an energy confinement degradation phase in EAST ohmic plasmas

In this paper, we present experimental studies of both high-k(r) ( cm(-1), and , respectively; ) and high- ( cm(-1), and , respectively; ) turbulence behavior during an ohmic energy confinement degradation phase in experimental advanced superconducting tokamak (EAST). High-k(r) turbulence from density fluctuation at and high- turbulence from density fluctuation at -0.97 were measured by tangential and poloidal CO2 laser collective scattering diagnostics, respectively. Note that k(r), , and are radial wavenumber, poloidal wavenumber, perpendicular wavenumber and ion gyroradius at electron temperature, respectively. Both high-k(r)/ turbulence power and energy confinement time are found to be temporally correlated to line-averaged electron density n(e) in the plasma current flat-top phase (I-p = 0.4 MA): when the n(e) shows continuous increase/decrease, the high-k(r)/ turbulence power increases/decreases correspondingly and the shows corresponding decrease/increase; the stable n(e) is related to stable both and high-k(r)/ turbulence power. Statistical results of high-k(r)/ turbulence power versus further imply that high-k(r)/ turbulence shows a strong correlation with plasma energy confinement degradation in high line-averaged n(e) condition, but high-k(r) and high- turbulence have relatively weak and no dependence on the transition between linear range in low-n(e) condition and energy confinement degradation in the high-n(e) condition, respectively. Moreover, profiles of electron temperature T-e and n(e) as well as their normalized gradients in a part of high- density fluctuation measurement region also have been given to qualitatively explain the enhancement of turbulence power with the increase of line-averaged n(e).

EAST tokamak↗
DOE OSTI2019

Learning Temporal and Spatial Correlations Jointly: A Unified Framework for Wind Speed Prediction

Leveraging both temporal and spatial correlations to predict wind speed remains one of the most challenging and less studied areas of wind speed prediction. In this paper, the problem of predicting wind speeds for multiple sites is investigated by using the spatio-temporal correlation. We proposed a deep architecture termed predictive spatio-temporal network (PSTN), which is a unified framework integrating a convolutional neural network (CNN) and a long short-term memory (LSTM). Initially, the spatial features are extracted from the spatial wind speed matrices (SWSMs) by the CNN at the bottom of the model. Then, the LSTM captures the temporal dependencies among the spatial features extracted from contiguous time points. Lastly, the predicted wind speeds are given by the last state of the top layer of the LSTM, which are generated by using the spatial features and temporal dependencies. Though composed of two kinds of architectures, PSTN is trained with one loss function in an end-to-end (E2E) manner, which can learn temporal and spatial correlations jointly. Experiments for short-term predictions are conducted on real-world data, whose results demonstrate that PSTN outperforms prior methods.

42 ENGINEERING↗
NASA NTRS1995

A serach for moderate- and high-energy neturino emission correlated with gamma-ray bursts

A temporal correlation analysis between moderate- (60 Mev less than or equal to E(sub nu)greater than or equal to 2500 MeV) and high-energy (E(sub nu) greater than or equal to 2000 MeV) neutrino interactions consist of two types: the moderate-energy interactions that are contained within the volume of IMB-3 and the upward-going muons produced by high-energy nu(sub mu) interactions in the rock around the detector. No evidence is found for moderate- or high-energy neutrino emission from GRBs nor for any neutrino/neutrino correlation. The nonobservation of nu/GRB correlations allows upper limits to be placed on the neutrino flux associated with GRBs.

Becker-Szendy, R.↗
DOE OSTI2024

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗
DOE OSTI2018

Modeling the effects of molecular disorder on the properties of Frenkel excitons in organic molecular semiconductors

The Frenkel exciton model offers a convenient framework for simulating electronic excitations in organic conjugated systems that are too large to address with atomistic level electronic structure methods. Parameterization of this model is typically based on analytical expressions that incompletely describe the spatial and temporal correlations that are inherent to many condensed phase molecular systems. In this manuscript, we introduce a general procedure for including these correlations in the Frenkel exciton model, by mapping them directly from all-atom molecular configurations, for instance from classical molecular dynamics. Regardless of system morphology, this mapping automatically captures the spatial and temporal molecular correlations that are otherwise difficult or impossible to represent in terms of low-dimensional correlation functions. We apply this procedure to study the excited state properties of condensed phase materials made up of thiophene oligomers. We demonstrate that Frenkel model parameters can be mapped from a series of single molecule electronic structure calculations, and that for these materials efficient semi-empirical methods are sufficient to accurately reproduce experimental spectral measurements. By analyzing the statistics of model parameters derived from materials with different characteristic morphologies, we highlight failures in some assumptions that are commonly applied when generating model parameters. Finally, by simulating exciton dynamics on a mapped Frenekel exciton model, we demonstrate the ability to quantify the effect of material morphology on the dynamic properties of excitons.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Link Scheduling in Satellite Networks via Machine Learning Over Riemannian Manifolds

Low Earth Orbit (LEO) satellites play a crucial role in enhancing global connectivity, serving a complementary solution to existing terrestrial systems. In wireless networks, scheduling is a vital process that allocates time-frequency resources to users for interference management. However, LEO satellite networks face significant challenges in scheduling their links towards ground users due to the satellites’ mobility and overlapping coverage. This paper addresses the dynamic link scheduling problem in LEO satellite networks by considering spatio-temporal correlations introduced by the satellites’ movements. The first step in the proposed solution involves modeling the network over Riemannian manifolds, thanks to their representation as symmetric positive definite matrices. We introduce two machine learning (ML)-based link scheduling techniques that model the dynamic evolution of satellite positions and link conditions over time and space. To accurately predict satellite link states, we present a recurrent neural network (RNN) over Riemannian manifolds, which captures spatio-temporal characteristics over time. Furthermore, we introduce a separate model, the convolutional neural network (CNN) over Riemannian manifolds, which captures geometric relationships between satellites and users by extracting spatial features from the network topology across all links. Simulation results demonstrate that both RNN and CNN over Riemannian manifolds deliver comparable performance to the fractional programming-based link scheduling (FPLinQ) benchmark. Remarkably, unlike other ML-based models that require extensive training data, both models only need 30 training samples to achieve over 99% of the sum rate while maintaining similar computational complexity relative to the benchmark.

42 ENGINEERING↗
DOE OSTI2015

Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography

Images of pharmacokinetic parameters (also known as parametric images) in dynamic fluorescence molecular tomography (FMT) can provide three-dimensional metabolic information for biological studies and drug development. However, the ill-posed nature of FMT and the high temporal variation of fluorophore concentration together make it difficult to obtain accurate parametric images in small animals in vivo. In this letter, we present a method to directly reconstruct the parametric images from the boundary measurements based on hybrid FMT/X-ray computed tomography (XCT) system. This method can not only utilize structural priors obtained from the XCT system to mitigate the ill-posedness of FMT but also make full use of the temporal correlations of boundary measurements to model the high temporal variation of fluorophore concentration. The results of numerical simulation and mouse experiment demonstrate that the proposed method leads to significant improvements in the reconstruction quality of parametric images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Anisotropic stress correlations in two-dimensional liquids

In this paper we demonstrate the presence of anisotropic stress correlations in the simulated 2D liquids. Whereas the temporal correlation of macroscopic shear stress is known to contribute to viscosity via the Green-Kubo formula, the general question regarding angular dependence of the spatial correlation among atomic level stresses in liquids without external shear has not been explored. Besides the apparent anisotropicity with well-defined symmetry, we found that the characteristic length of shear stress correlation depends on temperature and follows the power law, suggesting divergence around the glass transition temperature. The anisotropy of the stress correlations can be explained in terms of the inclusion model by Eshelby, based upon which we suggest that the mismatch between the atom and its nearest neighbor cage produces the atomic level stress as well as the long-range stress fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Characterization of Structural Vibration and Acoustic Radiation with a Beam-Array Doppler Vibrometer

This paper discusses the operational principles of an assembly of two opto-electronic modules with their configurations based on a Laser-Array Doppler Vibrometer (LADV) and a Shack-Hartmann Wavefront Sensor (SHWFS). Both sensors can operate concurrently providing complementary data. While the SHWFS is a well-established system that enables low-bandwidth spatio-temporal characterization of aerodynamic turbulence, the LADV technology allows real-time detection of structural vibrations and associated acoustic radiation fields. Practical examples are shown of the instruments’ capabilities, focusing on the ability to simultaneously capture, visualize and quantitatively characterize full-field non-stationary structural dynamics and unsteady sound fields or transient flow fields around ground test facility airframe models or other structures of interest. The parallel multi-channel architecture of the LADV system enables synchronous detection and temporal correlation of indicators related to the spatio-temporal vibration of the structure under inspection. This unique feature is essential for real time detection and categorization of the structural and acoustic dynamics of transient events. For the present study, the LADV data have been successfully compared with measurements obtained with the SHWFS in the wake of a subsonic scale-model airfoil. The ability of the LADV-SHWFS coupled measurements to perform real time non-intrusive evaluation and characterization of dynamic processes at operationally relevant bandwidths should provide a deeper insight into the complex structural dynamics that contribute to radiated sound fields.

Vladimir B Markov↗
DOE OSTI2021

pnnl/grid_prediction

Two datadriven predictive approaches, namely, {\em Koopman Operator Theoretic (KOT)-based} model and {\em Graph Neural Network (GNN)-based model}, to enable effective power system state predictions. The KOT-based approaches (Robust DMD, deepDMD) capture the power system evolution as a linear dynamical system on an abstract space. The GNNs model the spatio-temporal correlations using graph convolutional network and are called Spatio-Temporal Graph Convolutional Network (STGCN). These predictive models are trained, tested and compared rigorously based on their predictions of frequencies in the IEEE 68 bus system when subjected to a disturbance. GridSTAGE framework developed at Pacific Northwest National Laboratory is leveraged to generate multiple datasets (in the form of PMU measurements) for training and testing by strategically creating load changes across the spatial locations of the network

Nandanoor, Sai Pushpak↗
DOE OSTI2016

WE-AB-207A-06: Progressive Dose Control for Cone Beam CT with Deformation Assisted Temporal Nonlocal Means Method

Purpose: To reduce cone beam CT (CBCT) imaging dose, we previously proposed a progressive dose control (PDC) scheme to employ temporal correlation between CBCT images at different fractions for image quality enhancement. A temporal non-local means (TNLM) method was developed to enhance quality of a new low-dose CBCT using existing high-quality CBCT. To enhance a voxel value, the TNLM method searches for similar voxels in a window. Due to patient deformation among the two CBCTs, a large searching window was required, reducing image quality and computational efficiency. This abstract proposes a deformation-assisted TNLM (DA-TNLM) method to solve this problem. Methods: For a low-dose CBCT to be enhanced using a high-quality CBCT, we first performed deformable image registration between the low-dose CBCT and the high-quality CBCT to approximately establish voxel correspondence between the two. A searching window for a voxel was then set based on the deformation vector field. Specifically, the search window for each voxel was shifted by the deformation vector. A TNLM step was then applied using only voxels within this determined window to correct image intensity at the low-dose CBCT. Results: We have tested the proposed scheme on simulated CIRS phantom data and real patient data. The CITS phantom was scanned on Varian onboard imaging CBCT system with coach shifting and dose reducing for each time. The real patient data was acquired in four fractions with dose reduced from standard CBCT dose to 12.5% of standard dose. It was found that the DA-TNLM method can reduce total dose by over 75% on average in the first four fractions. Conclusion: We have developed a PDC scheme which can enhance the quality of image scanned at low dose using a DA-TNLM method. Tests in phantom and patient studies demonstrated promising results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Electro-optic modulation for high-speed characterization of entangled photon pairs

In this study, we demonstrate a new biphoton manipulation and characterization technique based on electro-optic intensity modulation and time shifting. By applying fast modulation signals with a sharply peaked cross-correlation to each photon from an entangled pair, it is possible to measure temporal correlations with significantly higher precision than that attainable using standard single-photon detection. Low-duty-cycle pulses and maximal-length sequences are considered as modulation functions, reducing the time spread in our correlation measurement by a factor of five compared to our detector jitter. With state-of-the-art electro-optic components, we expect the potential to surpass the speed of any single-photon detectors currently available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2010

Optimization of Noise Performance of Low-Back Ground Detector Arrays

The performance of the 2k x 2k Teledyne H2RG detectors is key to the success of the JWST mission. For broadband imaging, where background limited sensitivity is quickly reached, the key parameter is the quantum efficiency of the detectors, which is, in general, very good. For near infrared spectroscopy and narrow band imaging, we cannot generally reach the back-round limit, so instrument sensitivity is directly dependent on the read noise of the detector. We have initiated a program to analyze the noise characteristics of the H2RG detectors, studying the correlations among the detector outputs and with the reference output, as well as the temporal correlations in a given detector section. Lasing the measured characteristics of the noise correlations, we can determine the optimal coefficients for the removal of correlated noise as a function of frequency. By using available reference sources and adding more frequent references, we have been able to reduce the noise by a factor of two. We find that the detectors have significantly lower noise that observed in prior tests, and can offer significant improvements in the performance of the JWST instruments. We will present the analysis and mitigation techniques, discuss prospects for further improvements with existing detectors, and describe considerations for improvements in next-generation detectors.

Rauscher, Bernard J.↗
NASA NTRS2018

Global-scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products Using Triple Collocation

Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. Considering the potential violation of TC error assumptions, the impact of active-passive and satellite-model error cross correlations on the TC-derived inter-comparison results is examined at in situ sites using quadruple collocation analysis. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. This study is the first to apply TC to obtain a robust global-scale cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy in terms of anomaly temporal correlation. Our results confirm the overall advantage of SMAP (with a global average anomaly correlation of 0.76) over SMOS (0.66) and ASCAT (0.63) that has been established in several recent regional, ground-based studies. SMAP is also the best-performing product over the majority of applicable land pixels (52%), although SMOS and ASCAT each shows advantage in distinct geographic regions.

global-scale↗
DOE OSTI2017

Quantifying drivers of wild pig movement across multiple spatial and temporal scales

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

The correlation of solar flare hard X-ray bursts with Doppler blueshifted soft X-ray flare emission

We have investigated the temporal correlation between hard X-ray bursts and the intensity of Doppler blueshifted soft X-ray spectral line emission. We find a strong correlation for many events that have intense blueshifted spectral signatures and some correlation in events with modest blueshifts. The onset of hard X-rays frequently coincides to within a few seconds with the onset of blueshifted emission. The peak intensity of blueshifted emission is frequently close in time to the peak of the hard X-ray emission. Decay rates of the blueshifted and hard X-ray emission are similar, with the decay of the blueshifted emission tending to lag behind the hard X-ray emission in some cases. There are, however, exceptions to these conclusions, and, therefore, the results should not be generalized to all flares. Most of the data for this work were obtained from instruments flown on the Japanese Yohkoh solar spacecraft.

Bentley, R. D.↗
DOE OSTI2020

Microscopic Theory of Long-Time Center-of-Mass Self-Diffusion and Anomalous Transport in Ring Polymer Liquids

We construct a microscopic theory at the level of segment-scale correlated space–time intermolecular forces for the long-time center-of-mass (CM) diffusion constant and intermediate-time non-Fickian transport in dense solutions and melts of ring polymers. The approach combines ideas of polymer, colloid, and liquid-state statistical mechanics to quantify how the multifractal intra-ring conformational structure and inter-ring packing correlations determine dynamic caging constraints and time-dependent friction. Breakdown of Rouse theory is predicted to occur due to length scale-dependent temporal correlation of forces exerted on pairs of tagged ring segments from surrounding polymers. At large enough degrees of polymerization (N), a stronger scaling of the CM diffusion constant (D ∝ N –2 ) is predicted, with a crossover N D proportional to the product of the system-specific macromolecular volume fraction and dimensionless compressibility. In analogy with caging effects in glass-forming fluids, the theory does appear to begin to fail at sufficiently high N/N D for the center-of-mass diffusivity, likely due to another crossover to an even slower activated transport regime. However, use of N/N D with the theoretically predicted N D , in conjunction with dynamic blob scaling ideas for local Rouse friction, collapses semidilute and concentrated solution simulation data onto a master curve. Based on the same physical ideas employed to predict the diffusion constant, a generalized Langevin equation description is formulated for intermediate-time CM transport. It predicts two subdiffusive regimes that emerge due to the self-similar nature of internal ring structure. Analytic and numerical predictions for the apparent non-Fickian exponent as a function of time, N/N D and dimensionless compressibility, the evolution of the maximum degree of subdiffusive motion with N/N D , and the time scale for recovering Fickian diffusion are made, all of which are in good accordance with melt simulations. Furthermore, the present work sets the stage to address activated dynamics and glass formation on the macromolecular scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗