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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

On the multi-temporal correlation between photosynthesis and soil CO2 efflux: reconciling lags and observations.

Although there is increasing evidence of the temporal correlation between photosynthesis and soil CO{sub 2} efflux, no study has so far tested its generality across the growing season at multiple study sites and across several time scales. Here, we used continuous (hourly) data and applied time series analysis (wavelet coherence analysis) to identify temporal correlations and time lags between photosynthesis and soil CO{sub 2} efflux for three forests from different climates and a grassland. Results showed the existence of multi-temporal correlations at time periods that varied between 1 and 16 d during the growing seasons at all study sites. Temporal correlations were strongest at the 1 d time period, with longer time lags for forests relative to the grassland. The multi-temporal correlations were not continuous throughout the growing season, and were weakened when the effect of variations in soil temperature and CO{sub 2} diffusivity on soil CO{sub 2} efflux was taken into account. Multi-temporal correlations between photosynthesis and soil CO{sub 2} efflux exist, and suggest that multiple biophysical drivers (i.e. photosynthesis, soil CO{sub 2} diffusion, temperature) are likely to coexist for the regulation of allocation and transport speed of carbon during a growing season. Future studies should consider the multi-temporal influence of these biophysical drivers to investigate their effect on the transport of carbon through the soil-plant-atmosphere continuum.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes

Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disruption of operation, financial losses, and equipment damage. In particular, false data attacks initiated during power systems transients caused due to abrupt changes in load and generation can fool the conventional model-based detection methods relying on thresholds comparison to trigger an anomaly. In this paper, we propose a Koopman mode decomposition (KMD) based algorithm to detect and identify false data attacks in real-time. The Koopman modes (KMs) are capable of capturing the nonlinear modes of oscillation in the transient dynamics of the power networks and reveal the spatial embedding of both natural and anomalous modes of oscillations in the sensor measurements. The Koopman-based spatio-temporal nonlinear modal analysis is used to filter out the false data injected by an attacker. The performance of the algorithm is illustrated on the IEEE 68-bus test system using synthetic attack scenarios generated on GridSTAGE, a recently developed multivariate spatio-temporal data generation framework for simulation of adversarial scenarios in cyber-physical power systems.

Nandanoori, Sai Pushpak↗
DOE OSTI2015

A priori and a posteriori investigations for developing large eddy simulations of multi-species turbulent mixing under high-pressure conditions

A Direct Numerical Simulation (DNS) database was created representing mixing of species under high-pressure conditions. The configuration considered is that of a temporally evolving mixing layer. The database was examined and analyzed for the purpose of modeling some of the unclosed terms that appear in the Large Eddy Simulation (LES) equations. Several metrics are used to understand the LES modeling requirements. First, a statistical analysis of the DNS-database large-scale flow structures was performed to provide a metric for probing the accuracy of the proposed LES models as the flow fields obtained from accurate LESs should contain structures of morphology statistically similar to those observed in the filtered-and-coarsened DNS (FC-DNS) fields. To characterize the morphology of the large-scales structures, the Minkowski functionals of the iso-surfaces were evaluated for two different fields: the second-invariant of the rate of deformation tensor and the irreversible entropy production rate. To remove the presence of the small flow scales, both of these fields were computed using the FC-DNS solutions. It was found that the large-scale structures of the irreversible entropy production rate exhibit higher morphological complexity than those of the second invariant of the rate of deformation tensor, indicating that the burden of modeling will be on recovering the thermodynamic fields. Second, to evaluate the physical effects which must be modeled at the subfilter scale, an a priori analysis was conducted. This a priori analysis, conducted in the coarse-grid LES regime, revealed that standard closures for the filtered pressure, the filtered heat flux, and the filtered species mass fluxes, in which a filtered function of a variable is equal to the function of the filtered variable, may no longer be valid for the high-pressure flows considered in this study. The terms requiring modeling are the filtered pressure, the filtered heat flux, the filtered pressure work, and the filtered species mass fluxes. Improved models were developed based on a scale-similarity approach and were found to perform considerably better than the classical ones. These improved models were also assessed in an a posteriori study. Different combinations of the standard models and the improved ones were tested. At the relatively small Reynolds numbers achievable in DNS and at the relatively small filter widths used here, the standard models for the filtered pressure, the filtered heat flux, and the filtered species fluxes were found to yield accurate results for the morphology of the large-scale structures present in the flow. Analysis of the temporal evolution of several volume-averaged quantities representative of the mixing layer growth, and of the cross-stream variation of homogeneous-plane averages and second-order correlations, as well as of visualizations, indicated that the models performed equivalently for the conditions of the simulations. The expectation is that at the much larger Reynolds numbers and much larger filter widths used in practical applications, the improved models will have much more accurate performance than the standard one.

42 ENGINEERING↗
NASA NTRS2001

Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

NASA Discipline Cardiopulmonary↗
NASA NTRS1984

Analysis of some acoustics-jet flow interaction problems

Analytical problems in the interactions between the mean-shear flows and the acoustic field in the planar and circular jets are examined. These problems are basic in understanding the effects of coherent large structure on the generation and complications of sound in a sub-sonic jet. Three problems were investigated: (1) spatial (vs. temporal) normal mode analysis in a planar jets; (2) a slightly divergent, planar jet; and (3) acoustic waves in an axisymmetrical jet.

Chow, P. L.↗
DOE OSTI2025

Profiles of Radiative Fluxes at ENA

Profiles of radiative fluxes observed at the Atmospheric Radiation Measurement (ARM)’s Eastern North Atlantic (ENA) observatory along with the ancillary measurements are reported. The below-cloud drizzle properties were derived by combining the data from the ceilometer and Ka-band ARM Zenith Radar (KAZR) following the technique explained by Ghate et al. (2021 JAMC). The cloud and drizzle water path values were derived from the brightness temperatures reported by the microwave radiometer following the technique of Cadeddu et al. (2020 AMT). The cloud water path was then scaled to the KAZR-reported radar reflectivity to calculate profiles of liquid water content (LWC). Following the analysis from Ghate et al. (2023 JGR), cloud droplet effective radius was calculated using the number concentration value of 100 cm-3. The cloud properties, along with the thermodynamic properties, served as an input to the Rapid Radiative Transfer Model (RRTM) to yield profiles of radiative fluxes at a 1-minute temporal and 50-m vertical resolution. The fluxes were then averaged to hourly temporal resolution for analysis. In Mitra et al. (2025 JClim), the calculated profiles were compared against those derived from the satellite measurements (SYN1deg). Flux profiles from the SYN1deg and the thermodynamic and cloud properties used for deriving them are also reported here. Both all-sky and clear-sky radiative flux profiles were calculated. Due to the large data volume, the surface and top-of-atmosphere (TOA) radiative fluxes for the six-year period, and the hourly profiles of the radiative fluxes for January 2018, are submitted here. Full profiles of radiative fluxes calculated from the thermodynamic and cloud properties measured at the ENA site at 1-minute temporal and 50-m vertical resolution for a six-year period are available from the authors. Six files here correspond to the following data: 1_ENARAD_CERES_with_cld_amount_timeseries.nc: Time-series of hourly values of RRTM-simulated values of upwelling and downwelling fluxes at the surface and TOA, observed boundary-layer cloud fractions, and upwelling and downwelling fluxes from the SYN1deg from July 2015 to January 2022. 2_CERES_2018_at_CERES_levels.nc: SYN1deg radiative fluxes at six levels for the year 2018. 3_ENARad_2018_at_CERES_levels.nc: RRTM calculated fluxes at the SYN1deg vertical levels for the year 2018. 4_ENARad_rrtminputs_hourly_201801.nc: Thermodynamic and cloud properties used as an input to the RRTM for January 2018. 5_CERES_inputs_hourly_201801.nc: Thermodynamic and cloud properties utilized by SYN1deg algorithm for January 2018. 6_ENARAD_hourly_201801.nc: Full profiles of hourly averaged radiative fluxes from the RRTM simulations for January 2018.

Atmosphere↗
NASA NTRS1999

Utilizing Multiple Datasets for Snow Cover Mapping

Snow-cover maps generated from surface data are based on direct measurements, however they are prone to interpolation errors where climate stations are sparsely distributed. Snow cover is clearly discernable using satellite-attained optical data because of the high albedo of snow, yet the surface is often obscured by cloud cover. Passive microwave (PM) data is unaffected by clouds, however, the snow-cover signature is significantly affected by melting snow and the microwaves may be transparent to thin snow (less than 3cm). Both optical and microwave sensors have problems discerning snow beneath forest canopies. This paper describes a method that combines ground and satellite data to produce a Multiple-Dataset Snow-Cover Product (MDSCP). Comparisons with current snow-cover products show that the MDSCP draws together the advantages of each of its component products while minimizing their potential errors. Improved estimates of the snow-covered area are derived through the addition of two snow-cover classes ("thin or patchy" and "high elevation" snow cover) and from the analysis of the climate station data within each class. The compatibility of this method for use with Moderate Resolution Imaging Spectroradiometer (MODIS) data, which will be available in 2000, is also discussed. With the assimilation of these data, the resolution of the MDSCP would be improved both spatially and temporally and the analysis would become completely automated.

Tait, Andrew B.↗
NASA NTRS1976

Forest land management by satellite: LANDSAT-derived information as input to a forest inventory system

The author has identified the following significant results. Analysis of LANDSAT temporal data, specifically the digitally merged winter and summer scenes, provided the best overall classification results. Comparison of temporal classification results with available ground truth reveal a 94% agreement in the delineation of hardwood categories, a 96% agreement for the combined pine category, and a greater than 50% agreement for each individual pine subcategory. For nearly 1000 acres, compared clearcut acreage estimated with LANDSAT digital data differed from company inventory records by only 3%. Through analysis of summer data, pine stands were successfully classified into subcategories based upon the extent of crown closure. Maximum spectral separability of hardwood and pine stands was obtained from the analysis of winter data.

Williams, D. L.↗
NASA NTRS2011

Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation

This slide presentation reviews the systems engineering process designed to reduce the risk from debris during Space Shuttle Launching. This process begins the day of launch from the tanking to the vehicle tower clearance. Other debris risks (i.e., Ascent, and micrometeoroid orbital debit) are mentioned) but are not the subject of this presentation. The Liftoff debris systems engineering process and an example of how it works are reviewed (i.e.,STS-119 revealed a bolt liberation trend on the Fixed Service Structure (FSS) 275 level elevator room). The process includes preparation of a Certification of Flight Readiness (CoFR) that includes (1) Lift-off debris from previous mission dispositioned, (2) Flight acceptance rationale has been provided for Lift-off debris sources/causes (3) Lift-off debris mission support documentation, processes and tools are in place for the up-coming mission. The process includes a liftoff debris data collection that occurs after each launch. This includes a post launch walkdown, that records each liftoff debris, and the entry of the debris into a database, it also includes a review of the imagery from the launch, and a review of the instrumentation data. There is also a review of the debris transport analysis process, that includes temporal and spatial framework and a computational fluid dynamics (CFD) analysis. which incorporates a debris transport analyses (DTA), debris materials and impact tests, and impact analyses.

Mitchell, Michael↗
NASA NTRS2011

Coastal On-line Assessment and Synthesis Tool 2.0

COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.

Brown, Richard↗
NASA NTRS1995

A similarity hypothesis for the two-point correlation tensor in a temporally evolving plane wake

The analysis demonstrated that the governing equations for the two-point velocity correlation tensor in the temporally evolving wake admit similarity solutions, which include the similarity solutions for the single-point moment as a special case. The resulting equations for the similarity solutions include two constants, beta and Re(sub sigma), that are ratios of three characteristic time scales of processes in the flow: a viscous time scale, a time scale characteristic of the spread rate of the flow, and a characteristic time scale of the mean strain rate. The values of these ratios depend on the initial conditions of the flow and are most likely measures of the coherent structures in the initial conditions. The occurrences of these constants in the governing equations for the similarity solutions indicates that these solutions, in general, will only be the same for two flows if these two constants are equal (and hence the coherent structures in the flows are related). The comparisons between the predictions of the similarity hypothesis and the data presented here and elsewhere indicate that the similarity solutions for the two-point correlation tensors provide a good approximation of the measures of those motions that are not significantly affected by the boundary conditions caused by the finite extent of real flows. Thus, the two-point similarity hypothesis provides a useful tool for both numerical and physical experimentalist that can be used to examine how the finite extent of real flows affect the evolution of the different scales of motion in the flow.

Ewing, D. W.↗
NASA NTRS2011

Calibrated Noise Measurements with Induced Receiver Gain Fluctuations

The lack of well-developed techniques for modeling changing statistical moments in our observations has stymied the application of stochastic process theory in science and engineering. These limitations were encountered when modeling the performance of radiometer calibration architectures and algorithms in the presence of non stationary receiver fluctuations. Analyses of measured signals have traditionally been limited to a single measurement series. Whereas in a radiometer that samples a set of noise references, the data collection can be treated as an ensemble set of measurements of the receiver state. Noise Assisted Data Analysis is a growing field of study with significant potential for aiding the understanding and modeling of non stationary processes. Typically, NADA entails adding noise to a signal to produce an ensemble set on which statistical analysis is performed. Alternatively as in radiometric measurements, mixing a signal with calibrated noise provides, through the calibration process, the means to detect deviations from the stationary assumption and thereby a measurement tool to characterize the signal's non stationary properties. Data sets comprised of calibrated noise measurements have been limited to those collected with naturally occurring fluctuations in the radiometer receiver. To examine the application of NADA using calibrated noise, a Receiver Gain Modulation Circuit (RGMC) was designed and built to modulate the gain of a radiometer receiver using an external signal. In 2010, an RGMC was installed and operated at the National Institute of Standards and Techniques (NIST) using their Noise Figure Radiometer (NFRad) and national standard noise references. The data collected is the first known set of calibrated noise measurements from a receiver with an externally modulated gain. As an initial step, sinusoidal and step-function signals were used to modulate the receiver gain, to evaluate the circuit characteristics and to study the performance of a variety of calibration algorithms. The receiver noise temperature and time-bandwidth product of the NFRad are calculated from the data. Statistical analysis using temporal-dependent calibration algorithms reveals that the natural occurring fluctuations in the receiver are stationary over long intervals (100s of seconds); however the receiver exhibits local non stationarity over the interval over which one set of reference measurements are collected. A variety of calibration algorithms have been applied to the data to assess algorithms' performance with the gain fluctuation signals. This presentation will describe the RGMC, experiment design and a comparative analysis of calibration algorithms.

Racette, Paul↗
NASA NTRS2001

Differential expression of neuroleukin in osseous tissues and its involvement in mineralization during osteoblast differentiation

Osteoblast differentiation is a multistep process that involves critical spatial and temporal regulation of cellular processes marked by the presence of a large number of differentially expressed molecules. To identify key functional molecules, we used differential messenger RNA (mRNA) display and compared RNA populations isolated from the defined transition phases (proliferation, matrix formation, and mineralization) of the MC3T3-E1 osteoblast-like cell line. Using this approach, a complementary DNA (cDNA) fragment was isolated and identified as neuroleukin (NLK), a multifunctional cytokine also known as autocrine motility factor (AMF), phosphoglucose isomerase (PGI; phosphohexose isomerase [PHI]), and maturation factor (MF). Northern analysis showed NLK temporal expression during MC3T3-E1 cell differentiation with a 3.5-fold increase during matrix formation and mineralization. Immunocytochemical studies revealed the presence of NLK in MC3T3-E1 cells as well as in the surrounding matrix, consistent with a secreted molecule. In contrast, the NLK receptor protein was detected primarily on the cell membrane. In subsequent studies, a high level of NLK expression was identified in osteoblasts and superficial articular chondrocytes in bone of 1-, 4-, and 8-month-old normal mice, as well as in fibroblasts, proliferating chondrocytes, and osteoblasts within a fracture callus. However, NLK was not evident in hypertrophic chondrocytes or osteocytes. In addition, treatment of MC3T3 cells with 6-phosphogluconic acid (6PGA; a NLK inhibitor) resulted in diminishing alkaline phosphatase (ALP) activity and mineralization in MC3T3-E1 cells, especially during the matrix formation stage of differentiating cells. Taken together, these data show specific expression of NLK in discrete populations of bone and cartilage cells and suggest a possible role for this secreted protein in bone development and regeneration.

NASA Discipline Musculoskeletal↗
DOE OSTI2017

Detecting population-environmental interactions with mismatched time series data

Time series analysis is an essential method for decomposing the influences of density and exogenous factors such as weather and climate on population regulation. However, there has not been much work focused on understanding how well commonly collected data can reconstruct the effects of environmental factors on population dynamics. We show that, analogous to similar scale issues in spatial data analysis, coarsely sampled temporal data can fail to detect covariate effects when interactions occur on timescales that are fast relative to the survey period. We propose a method for modeling mismatched time series data that couples high-resolution environmental data to low-resolution abundance data. We illustrate our approach with simulations and by applying it to Florida's southern Snail kite population. Our simulation results show that our method can reliably detect linear environmental effects and that detecting nonlinear effects requires high-resolution covariate data even when the population turnover rate is slow. In the Snail kite analysis, our approach performed among the best in a suite of previously used environmental covariates explaining Snail kite dynamics and was able to detect a potential phenological shift in the environmental dependence of Snail kites. Our work provides a statistical framework for reliably detecting population–environment interactions from coarsely surveyed time series. An important implication of this work is that the low predictability of animal population growth by weather variables found in previous studies may be due, in part, to how these data are utilized as covariates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Microbial Tracking-2, a metagenomics analysis of bacteria and fungi onboard the International Space Station

The International Space Station (ISS) is a unique and complex built environment with the ISS surface microbiome originating from crew and cargo or from life support recirculation in an almost entirely closed system. The Microbial Tracking 1 (MT-1) project was the first ISS environmental surface study to report on the metagenome profiles without using whole-genome amplification. The study surveyed the microbial communities from eight surfaces over a 14-month period. The Microbial Tracking 2 (MT-2) project aimed to continue the work of MT-1, sampling an additional four flights from the same locations, over another 14 months. Eight surfaces across the ISS were sampled with sterile wipes and processed upon return to Earth. DNA extracted from the processed samples (and controls) were treated with propidium monoazide (PMA) to detect intact/viable cells or left untreated and to detect the total DNA population (free DNA/compromised cells/intact cells/viable cells). DNA extracted from PMA-treated and untreated samples were analyzed using shotgun metagenomics. Samples were cultured for bacteria and fungi to supplement the above results. Staphylococcus sp. and Malassezia sp. were the most represented bacterial and fungal species, respectively, on the ISS. Overall, the ISS surface microbiome was dominated by organisms associated with the human skin. Multi-dimensional scaling and differential abundance analysis showed significant temporal changes in the microbial population but no spatial differences. The ISS antimicrobial resistance gene profiles were however more stable over time, with no differences over the 5-year span of the MT-1 and MT-2 studies. Twenty-nine antimicrobial resistance genes were detected across all samples, with macrolide/lincosamide/streptogramin resistance being the most widespread. Metagenomic assembled genomes were reconstructed from the dataset, resulting in 82 MAGs. Functional assessment of the collective MAGs showed a propensity for amino acid utilization over carbohydrate metabolism. Co-occurrence analyses showed strong associations between bacterial and fungal genera. Culture analysis showed the microbial load to be on average 3.0 × 10 5 cfu/m 2 . Utilizing various metagenomics analyses and culture methods, we provided a comprehensive analysis of the ISS surface microbiome, showing microbial burden, bacterial and fungal species prevalence, changes in the microbiome, and resistome over time and space, as well as the functional capabilities and microbial interactions of this unique built microbiome. Data from this study may help to inform policies for future space missions to ensure an ISS surface microbiome that promotes astronaut health and spacecraft integrity.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

Evaluation Analysis of NASA SMAP L3 and L4 and SPoRT-LIS Soil Moisture Data in the United States

Soil moisture has a critical role in the development, frequency and persistence of climatic and hydrologic extremes such as drought, heat wave and flooding events. In situ soil moisture data are uneven and sparse in time and space. This highlights the need to utilize other soil moisture sources to fill this spatiotemporal gap. The goal of this study is to validate one satellite-based and two model-based soil moisture datasets with in situ data across the United States. Soil moisture information from the Soil Moisture Active Passive (SMAP) enhanced level 3 (L3) (SMAP L3) and modeled level 4 (L4) (SMAP L4) data at 9-km resolution and Short-term Prediction Research and Transition-Land Information System (SPoRT-LIS) modeled at 3-km resolution were selected for evaluation. SPoRT-LIS is a near real-time, high resolution operational land analysis data. Ground-based data were obtained from the North American Soil Moisture Database (NASMD) for 362 stations. Seven statistical indicators including anomaly, Spearman, and Pearson correlation coefficients, the systematic error (Bias), root mean square error (RMSE), unbiased root mean square error (ubRMSE), and normalized standard deviation (SDV) were used to evaluate the satellite- and model-derived soil moisture data. In addition, the triple collocation (TC) error model was used to measure the error among SMAP L4, SPoRT-LIS and ground-based data. This study assesses which satellite or modeled dataset is most appropriate for specific times and locations to use as a surrogate for in situ observations. Temporal and spatial analysis demonstrated that, overall, SMAP L4 performed better than SMAP L3 and SPoRT-LIS. Strong agreement was observed between SMAP L4 and in situ observations (ρ = 0.53, Bias = −0.006) in all seasons and most regions with various land covers, especially in winter and in the central regions of the United States. For croplands, SMAP L4 presented the best agreement with in situ data, analyzing all period (ρ = 0.60) and non-winter period (ρ = 0.61) separately.

Tavakol, Ameneh↗