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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations

Satellite quantification of aerosol effects on clouds relies on aerosol optical depth (AOD) as a proxy for aerosol concentration or cloud condensation nuclei (CCN). However, the lack of error characterization of satellite-based results hampers their use for the evaluation and improvement of global climate models. We show that the use of AOD for assessing aerosol–cloud interactions (ACIs) is inadequate over vast oceanic areas in the subtropics. Instead, we postulate that a more physical approach that consists of matching vertically resolved aerosol data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite at the cloud-layer height with Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud retrievals reduces uncertainties in satellite-based ACI estimates. Combined aerosol extinction coefficients (σ) below cloud top (σBC) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (N d ) from MODIS Aqua yield high correlations across a broad range of σBC values, with σBC quartile correlations ≥0.78. In contrast, CALIOP-based AOD yields correlations with MODIS Nd of 0.54–0.62 for the two lower AOD quartiles. Moreover, σBC explains 41% of the spatial variance in MODIS N d , whereas AOD only explains 17%, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with σBC, near-surface σ weakly correlates in space with MODIS N d , accounting for a 16% variance. It is concluded that the linear regression calculated from ln(N d )–ln(σBC) (the standard method for quantifying ACIs) is more physically meaningful than that derived from the Nd–AOD pair.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Nonthermal X-ray Spectral Flattening toward Low Energies in Early Impulsive Flares

The determination of the low-energy cutoff to nonthermal electron distributions is critical to the calculation of the nonthermal energy in solar flares. The most direct evidence for low-energy cutoffs is flattening of the power-law, nontherma1 X-ray spectra at low energies. However, because of the plasma preheating often seen in flares, the thermal emissions at low energies may hide such spectral flattening of the nonthermal component. We select a category of flares, which we call "early impulsive flares", in which the > 25 keV hard X-ray (HXR) flux increase is delayed by less than 30 s after the flux increase at lower energies. Thus, the plasma preheating in these flares is minimal, so the nonthermal spectrum can be determined to lower energies than in flares with significant preheating. Out of a sample of 33 early impulsive flares observed by the Ramaty High Energy Solar Spectroscopy Imager (RHESSI), 9 showed spectral flattening toward low energies. In these events, the break energy of the double power-law fit to the HXR spectra lies in the range of 10-50 keV, significantly lower than the value we have seen for other flares that do not show such early impulsive emissions. In particular, it correlates with the HXR flux. After correcting the spatially-integrated spectra for albedo from isotropically emitted X-rays and using RHESSI imaging spectroscopy to exclude the extended albedo halo, we find that albedo associated with isotropic or nearly isotropic electrons can only account for the spectral flattening in 3 flares near Sun center. The spectral flattening in the remaining 6 flares is found to be consistent with the existence of a low-energy cutoff in the electron spectrum, falling in the range of 15-50 keV, which also correlates with the HXR flux.

Holman, Gordon D.↗
DOE OSTI2024

MemFriend: Understanding Memory Performance with Spatial-Temporal Affinity

In HPC applications, memory access behavior is one of the main factors affecting performance. Improving an application’s memory access behavior involves optimizing data layout and/or restructuring code, and requires studying spatial-temporal data locality. Existing data locality analyses focus on single-location metrics and are restricted to evaluating temporal locality. We introduce spatial-temporal affinity metrics that quantify temporal access proximity, forward access correlation, and nearby access correlation between pairs of memory locations. We describe methods for distinguishing between potential vs. realized affinity and for reasoning about affinity at multiple resolutions (3D, 2D, 1D). Finally, we construct spatial-temporal affinity signatures that classify memory behavior and that be used to reason about changes in software (data relayout, code refactoring) or hardware (caching, prefetching). We describe methods for signature visualization, interpretation, and quantitative comparison of signatures. We evaluate our methodology using applications with variants that contrast data structures, data layouts and algorithms. We show that spatial-temporal affinity analysis provides novel insights and enables predictive reasoning about application performance when contrasted with reuse distance analysis.

Suriyakumar, Yasodhadevi↗
DOE OSTI2013

Plasmon-Induced Optical Field Enhancement studied by Correlated Scanning and Photoemission Electron Microscopy

We use multi-photon photoemission electron microscopy (PEEM) to image the enhanced electric fields of silver nanoparticles supported on a silver thin film substrate. Electromagnetic field enhancement is measured by comparing the photoelectron yield of the nanoparticles with respect to the photoelectron yield of the surrounding silver thin film. We investigate the dependence of the photoelectron yield of the nanoparticle as a function of size and shape. Multi-photon PEEM results are presented for three average nanoparticle diameters: 122 ± 6, 75 ± 6, and 34 ± 2 nm. The enhancement in photoelectron yield of single nanoparticles illuminated with femtosecond laser pulses (400 nm, ~3.1 eV) is found to be a factor of 102 to 103 times greater than that produced by the flat silver thin film. High-resolution, multi-photon PEEM images of single silver nanoparticles reveal that the greatest enhancement in photoelectron yield is localized at distinct regions on the surface of the nanoparticle whose magnitude and spatial extent is dependent on the incident electric field polarization. In conjunction with correlated scanning electron microscopy (SEM), nanoparticles that deviate from nominally spherical shapes are found to exhibit irregular spatial distributions in the multi-photon PEEM images that are correlated with the unique shape and topology of the nanoparticle.

Environmental Molecular Sciences Laboratory↗
NASA NTRS1981

Computing aerodynamic sound using advanced statistical turbulence theories

It is noted that the calculation of turbulence-generated aerodynamic sound requires knowledge of the spatial and temporal variation of Q sub ij (xi sub k, tau), the two-point, two-time turbulent velocity correlations. A technique is presented to obtain an approximate form of these correlations based on closure of the Reynolds stress equations by modeling of higher order terms. The governing equations for Q sub ij are first developed for a general flow. The case of homogeneous, stationary turbulence in a unidirectional constant shear mean flow is then assumed. The required closure form for Q sub ij is selected which is capable of qualitatively reproducing experimentally observed behavior. This form contains separation time dependent scale factors as parameters and depends explicitly on spatial separation. The approximate forms of Q sub ij are used in the differential equations and integral moments are taken over the spatial domain. The velocity correlations are used in the Lighthill theory of aerodynamic sound by assuming normal joint probability.

Hecht, A. M.↗
DOE OSTI2026

Endophyte‐induced systemic spatial reprogramming of metabolism in Populus trichocarpa roots under drought

Beneficial, facultative endophytes help plants thrive in challenging environments by altering their host's metabolism, but how these cellular scale metabolic changes propagate to the systems biology scale is unknown. In this work, we employed a high-resolution chemical imaging approach to map metabolic changes at the Populus trichocarpa root-zone and cell-type levels combined with machine learning (ML) models to identify root metabolites and exudates that have predictive power over treatment class. We found that a nine-strain consortium of beneficial endophytes differentially altered the metabolome of droughted root tissues in a manner specific to cell type and root zone, with endophyte abundance showing a clear correlation to individual metabolites. Our study demonstrates that integrating spatial metabolomics with ML can reveal localized metabolic patterns linked to root–microbe interactions and generate novel hypotheses about underlying biological mechanisms.

Drought↗
NASA NTRS1986

Evaluation of 2 cognitive abilities tests in a dual-task environment

Most real world operators are required to perform multiple tasks simultaneously. In some cases, such as flying a high performance aircraft or trouble shooting a failing nuclear power plant, the operator's ability to time share or process in parallel" can be driven to extremes. This has created interest in selection tests of cognitive abilities. Two tests that have been suggested are the Dichotic Listening Task and the Cognitive Failures Questionnaire. Correlations between these test results and time sharing performance were obtained and the validity of these tests were examined. The primary task was a tracking task with dynamically varying bandwidth. This was performed either alone or concurrently with either another tracking task or a spatial transformation task. The results were: (1) An unexpected negative correlation was detected between the two tests; (2) The lack of correlation between either test and task performance made the predictive utility of the tests scores appear questionable; (3) Pilots made more errors on the Dichotic Listening Task than college students.

Vidulich, M. A.↗
DOE OSTI2024

Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model

Abstract Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold‐adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Predicting photovoltaic soiling losses using environmental parameters: An update

This study presents an investigation on the correlations between soiling losses and environmental parameters at 41 locations in the United States, with the aim of analyzing the possibility of predicting soiling losses at a site even when soiling data are not available. The results of this work, which considers the largest pool of soiling data points systematically investigated so far, confirm that a single-variable regression based on particulate matter concentration returns the best correlations with soiling, with adjusted coefficients of determination up to 70%, corresponding to RMSE as low as 0.9%. Among the various particulate matter datasets investigated, a gridded Environment Protection Agency dataset is for the first time found to return correlations similar to those obtained by interpolating particulate matter monitoring station data. We discuss in detail the different interpolation techniques used to process the particulate matter concentrations because they can greatly impact the correlations. Specifically, the correlation coefficients between soiling and particulate matter range between 70% and less than 20%, depending on the interpolation methods and monitoring distance. Spatial interpolation methods based on inverse distance weighting are found to return better correlations than a nearest neighbor or a simple average approach, especially when large distances are considered. Similarly, the effects of different rain thresholds used to calculate the length of the dry periods are examined. An enhanced two-variable regression is found to achieve higher-quality correlations, with adjusted R2 of 90% (RMSE = 0.55%), also suggesting that high and low soiling locations might be differentiated depending on fixed particulate matter or rainfall thresholds.

14 SOLAR ENERGY↗
NASA NTRS1978

The correlation function for density perturbations in an expanding universe. III The three-point and predictions of the four-point and higher order correlation functions

Higher-order correlation functions for the large-scale distribution of galaxies in space are investigated. It is demonstrated that the three-point correlation function observed by Peebles and Groth (1975) is not consistent with a distribution of perturbations that at present are randomly distributed in space. The two-point correlation function is shown to be independent of how the perturbations are distributed spatially, and a model of clustered perturbations is developed which incorporates a nonuniform perturbation distribution and which explains the three-point correlation function. A model with hierarchical perturbations incorporating the same nonuniform distribution is also constructed; it is found that this model also explains the three-point correlation function, but predicts different results for the four-point and higher-order correlation functions than does the model with clustered perturbations. It is suggested that the model of hierarchical perturbations might be explained by the single assumption of having density fluctuations or discrete objects all of the same mass randomly placed at some initial epoch.

Mcclelland, J.↗
DOE OSTI2015

Understanding and Exploiting Spatial Properties of System Failures on Extreme-Scale HPC Systems, In: 2015 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks

As we approach exascale, the scientific simulations are expected to experience more interruptions due to increased system failures. Designing better HPC resilience techniques requires understanding the key characteristics of system failures on these systems. While temporal properties of system failures on HPC systems have been well-investigated, there is limited understanding about the spatial characteristics of system failures and its impact on the resilience mechanisms. Therefore, we examine the spatial characteristics and behavior of system failures. We investigate the interaction between spatial and temporal characteristics of failures and its implications for system operations and resilience mechanisms on large-scale HPC systems. We show that system failures have "spatial locality" at different granularity in the system, study impact of different failure-types, and investigate the correlation among different failure-types. Finally, we propose a novel scheme that exploits the spatial locality in failures to improve application and system performance. Our evaluation shows that the proposed scheme significantly improves the system performance in a dynamic and production-level HPC system.

Computer Science↗
NASA NTRS1993

Airborne eddy correlation gas flux measurements - Design criteria for optical techniques

Although several methods exist for the determination of the flux of an atmospheric species, the airborne eddy correlation method has the advantage of providing direct flux measurements that are representative of regional spatial domains. The design criteria pertinent to the construction of chemical instrumentation suitable for use in airborne eddy correlation flux measurements are discussed. A brief overview of the advantages and limitations of the current instrumentation used to obtain flux measurements for CO, CH4, O3, CO2, and water vapor are given. The intended height of the measurement within the convective boundary layer is also shown to be an important design criteria. The sensitivity, or resolution, which is required in the measurement of a scalar species to obtain an adequate species flux measurement is discussed. The relationship between the species flux resolution and the more commonly stated instrumental resolution is developed and it is shown that the standard error of the flux estimate is a complicated function of the atmospheric variability and the averaging time that is used. The use of the recently proposed intermittent sampling method to determine the species flux is examined. The application of this technique may provide an opportunity to expand the suite of trace gases for which direct flux measurements are possible.

Ritter, John A.↗
DOE OSTI2015

Understanding and Exploiting Spatial Properties of System Failures on Extreme-Scale HPC Systems

As we approach exascale, the scientific simulations are expected to experience more interruptions due to increased system failures. Designing better HPC resilience techniques requires understanding the key characteristics of system failures on these systems. While temporal properties of system failures on HPC systems have been well-investigated, there is limited understanding about the spatial characteristics of system failures and its impact on the resilience mechanisms. Therefore, we examine the spatial characteristics and behavior of system failures. We investigate the interaction between spatial and temporal characteristics of failures and its implications for system operations and resilience mechanisms on large-scale HPC systems. We show that system failures have spatial locality at different granularity in the system; study impact of different failure-types; and investigate the correlation among different failure-types. Finally, we propose a novel scheme that exploits the spatial locality in failures to improve application and system performance. Our evaluation shows that the proposed scheme significantly improves the system performance in a dynamic and production-level HPC system.

Rogers, James H↗
NASA NTRS2002

Phase Synchronization and Desynchronization of Structural Response Induced by Turbulent and External Sound

Acoustic and turbulent boundary layer flow loadings over a flexible structure are used to study the spatial-temporal dynamics of the response of the structure. The stability of the spatial synchronization and desynchronization by an active external force is investigated with an array of coupled transducers on the structure. In the synchronous state, the structural phase is locked, which leads to the formation of spatial patterns while the amplitude peaks exhibit chaotic behaviors. Large amplitude, spatially symmetric loading is superimposed on broadband, but in the desynchronized state, the spectrum broadens and the phase space is lost. The resulting pattern bears a striking resemblance to phase turbulence. The transition is achieved by using a low power external actuator to trigger broadband behaviors from the knowledge of the external acoustic load inducing synchronization. The changes are made favorably and efficiently to alter the frequency distribution of power, not the total power level. Before synchronization effects are seen, the panel response to the turbulent boundary layer loading is discontinuously spatio-temporally correlated. The stability develops from different competing wavelengths; the spatial scale is significantly shorter than when forced with the superimposed external sound. When the external sound level decreases and the synchronized phases are lost, changes in the character of the spectra can be linked to the occurrence of spatial phase transition. These changes can develop broadband response. Synchronized responses of fuselage structure panels have been observed in subsonic and supersonic aircraft; results from two flights tests are discussed.

Maestrello, Lucio↗
DOE OSTI2022

Organic matter distribution in the icy environments of Taylor Valley, Antarctica

Glaciers can accumulate and release organic matter affecting the structure and function of associated terrestrial and aquatic ecosystems. Here we analyzed 18 ice cores collected from six locations in Taylor Valley (McMurdo Dry Valleys), Antarctica to determine the spatial abundance and quality of organic matter, and the spatial distribution of bacterial density and community structure from the terminus of the Taylor Glacier to the coast (McMurdo Sound). Our results showed that dissolved and particulate organic carbon (DOC and POC) concentrations in the ice core samples increased from the Taylor Glacier to McMurdo Sound, a pattern also shown by bacterial cell density. Fluorescence Excitation Emission Matrices Spectroscopy (EEMs) and multivariate parallel factor (PARAFAC) modeling identified one humic-like (C1) and one protein-like (C2) component in ice cores whose fluorescent intensities all increased from the Polar Plateau to the coast. The fluorescence index showed that the bioavailability of dissolved organic matter (DOM) also decreased from the Polar Plateau to the coast. Partial least squares path modeling analysis revealed that bacterial abundance was the main positive biotic factor influencing both the quantity and quality of organic matter. Marine aerosol influenced the spatial distribution of DOC more than katabatic winds in the ice cores. Certain bacterial taxa showed significant correlations with DOC and POC concentrations. Collectively, our results show the tight connectivity among organic matter spatial distribution, bacterial abundance and meteorology in the McMurdo Dry Valley ecosystem.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Real-valued composite filters for correlation-based optical pattern recognition

Advances in the technology of optical devices such as spatial light modulators (SLMs) have influenced the research and growth of optical pattern recognition. In the research leading to this report, the design of real-valued composite filters that can be implemented using currently available SLMs for optical pattern recognition and classification was investigated. The design of real-valued minimum average correlation energy (RMACE) filter was investigated. Proper selection of the phase of the output response was shown to reduce the correlation energy. The performance of the filter was evaluated using computer simulations and compared with the complex filters. It was found that the performance degraded only slightly. Continuing the above investigation, the design of a real filter that minimizes the output correlation energy and the output variance due to noise was developed. Simulation studies showed that this filter had better tolerance to distortion and noise compared to that of the RMACE filter. Finally, the space domain design of RMACE filter was developed and implemented on the computer. It was found that the sharpness of the correlation peak was slightly reduced but the filter design was more computationally efficient than the complex filter.

Rajan, P. K.↗
DOE OSTI2022

Correlative SIP-FISH-Raman-SEM-NanoSIMS links identity, morphology, biochemistry, and physiology of environmental microbes

Microscopic and spectroscopic techniques are commonly applied to study microbial cells but are typically used on separate samples, resulting in population-level datasets that are integrated across different cells with little spatial resolution. To address this shortcoming, we developed a workflow that correlates several microscopic and spectroscopic techniques to generate an in depth analysis of individual cells. By combining stable isotope probing (SIP), fluorescence in situ hybridization (FISH), scanning electron microscopy (SEM), confocal Raman microspectroscopy (Raman), and nano-scale secondary ion mass spectrometry (NanoSIMS), we illustrate how individual cells can be thoroughly interrogated to obtain information about their taxonomic identity, structure, physiology, and metabolic activity. Analysis of an artificial community demonstrated that our correlative approach was able to resolve the activity of single cells using heavy water SIP in conjunction with Raman and/or NanoSIMS and establish their taxonomy and morphology using FISH and SEM. We then applied this workflow to a sample of yet uncultured multicellular magnetotactic bacteria. In addition to establishing their identity and activity, backscatter electron microscopy (BSE), NanoSIMS, and energy-dispersive X-ray spectroscopy (EDS) were employed to characterize the magnetosomes within the cells. By integrating these techniques, we demonstrate a cohesive approach to thoroughly study environmental microbes at single cell resolution.

Schaible, George↗
NASA NTRS1994

The rotation of photospheric magnetic fields: A random walk transport model

In an earlier study of solar differential rotation, we showed that the transport of magnetic flux across latitudes acts to establish quasi-stationary patterns, therby accounting for the observed rigid rotation of the large-scale photospheric field. In that paper, the effect of supergranular convection was represented by a continuum diffusion, limiting the applicability of the calculations to large spatial scales. Here we extend the model to scales comparable to that of the supergranulation itself by replacing the diffusive transport with a discrete random walk process. Rotation curves are derived by cross-correlating the simulated photospheric field maps for a variety of time lags and spatial resolutions. When the lag between maps is relatively short less than or approximately = 15 days), the midlatitude correlation functions show two distinct components: a broad feature associated with the large-scale unipolar patterns and a narrow feature originating from small magnetic structures encompossing from one to several supergranular cells. By fitting the broad component we obtain the rigid rotation profile of the patterns, whereas by fitting the narrow component, we recover the differential rate of the photospheric plasma itself. For time lags of 1 month or greater, only the broad feature associated with the long-lived patterns remains clearly identifiable in the simulations.

Wang, Y. -M.↗