Search NASA⌕ Search

SEARCH · Search NASA

Results for “Temporal Study”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Climate-Driven Legacies in Simulated Microbial Communities Alter Litter Decomposition Rates

The mechanisms underlying diversity-functioning relationships have been a consistent area of inquiry in biogeochemistry since the 1950s. Though these mechanisms remain unresolved in soil microbiomes, many approaches at varying scales have pointed to the same notion—composition matters. Confronting the methodological challenge arising from the complexity of microbiomes, this study used the model DEMENTpy, a trait-based modeling framework, to explore trait-based drivers of microbiome-dependent litter decomposition. We parameterized DEMENTpy for five sites along a climate gradient in Southern California, United States, and conducted reciprocal transplant simulations analogous to a prior empirical study. The simulations demonstrated climate-dependent legacy effects of microbial communities on plant litter decomposition across the gradient. This result is consistent with the previous empirical study across the same gradient. An analysis of community-level traits further suggests that a 3-way tradeoff among resource acquisition, stress tolerance, and yield strategies influences community assembly. Simulated litter decomposition was predictable with two community traits (indicative of two of the three strategies) plus local environment, regardless of the system state (transient vs. equilibrium). Although more empirical confirmation is still needed, community traits plus local environmental factors (e.g., environment and litter chemistry) may robustly predict litter decomposition across spatial-temporal scales. In conclusion, this study offers a potential trait-based explanation for climate-dependent community effects on litter decomposition with implications for improved understanding of whole-ecosystem functioning across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Spatial and temporal baseline of perfluorooctanesulfonic acid retained in sediment core samples from Puget Sound, Washington, USA

Per- and poly-fluorinated alkyl substances (PFAS) are a group of highly persistent synthetic chemicals utilized in many industrial and consumer products, and — most significantly toward introduction to the marine environment — in fire-fighting foams. Recently, PFAS have been linked to adverse health effects, prompting the need to understand transport and fate. Puget Sound’s main basin, hosting densely populated urban and industrial areas, is known to be contaminated with various persistent organic pollutants and provides a central focus for ecosystem monitoring. Perfluorooctanesulfonic acid, a manufactured PFAS and biodegradation product, partitions to marine sediments and thus can be used as a primary indicator toward regulatory efforts. The current study offers a spatial and temporal analysis of the Puget Sound from cores collected adjacent, Tacoma and Seattle, WA, as well as cores from central Hood Canal and Carr Inlet.

Per- and poly-fluorinated alkyl substances (PFAS),↗
NASA NTRS1987

Simulation and analysis of a geopotential research mission

Methods for the determination of the initial conditions for the two satellites that will satisfy Geopotential Research Mission (GRM) requirements are investigated. For certain gravitational recovery techniques, the satellites must remain close to a specified separation distance and their groundtracks must repeat after a specified interval of time. Since the objective of the GRM mission is to improve the gravity model, any pre-mission orbit predicted using existing gravity models will be in error. A technique has been developed to eliminate the drift between the two satellites caused by gravitational modeling errors and return them to repeating groundtracks. The concept of frozen orbits, which minimize altitude variations over given latitudes, was investigated. Finally, the effects of temporal perturbations on the relative range-rate signal were studied. At the proposed altitude of 160 km, the range-rate signal produced by perturbations other than the static geopotential field are dominated by the luni-solar effect. This study demonstrates that the combined effects of all the temporal perturbations does not prevent the orbit from being frozen or the satellites from obtaining a repeating groundtrack to within a specified closure distance.

White, Lisa K.↗
DOE OSTI2024

Reviews and syntheses: Opportunities for robust use of peak intensities from high-resolution mass spectrometry in organic matter studies

Abstract. Earth's biogeochemical cycles are intimately tied to the biotic and abiotic processing of organic matter (OM). Spatial and temporal variations in OM chemistry are often studied using direct infusion, high-resolution Fourier transform mass spectrometry (FTMS). An increasingly common approach is to use ecological metrics (e.g., within-sample diversity) to summarize high-dimensional FTMS data, notably Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). However, problems can arise when FTMS peak-intensity data are used in a way that is analogous to abundances in ecological analyses (e.g., species abundance distributions). Using peak-intensity data in this way requires the assumption that intensities act as direct proxies for concentrations. Here, we show that comparisons of the same peak across samples (within-peak) may carry information regarding variations in relative concentration, but comparing different peaks (between-peak) within or between samples does not. We further developed a simulation model to study the quantitative implications of using peak intensities to compute ecological metrics (e.g., intensity-weighted mean properties and diversity) that rely on information about both within-peak and between-peak shifts in relative abundance. We found that, despite analytical limitations in linking concentration to intensity, ecological metrics often perform well in terms of providing robust qualitative inferences and sometimes quantitatively accurate estimates of diversity and mean molecular characteristics. We conclude with recommendations for the robust use of peak intensities for natural organic matter studies. A primary recommendation is the use and extension of the simulation model to provide objective guidance on the degree to which conceptual and quantitative inferences can be made for a given analysis of a given dataset. Broad use of this approach can help ensure rigorous scientific outcomes from the use of FTMS peak intensities in environmental applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Impact of Clean Grid Transition on Wastewater Sector Greenhouse Gas Emissions

This study examines the spatial and temporal impacts of the U.S. clean energy grid transition on related greenhouse gas (GHG) emissions from the wastewater treatment industry. By analyzing data from 17,156 water resource recovery facilities (WRRFs) and state-specific grid decarbonization scenarios, the results project a 60% reduction in Scope 2 emissions by 2050, driven by the national shift to renewable energy. However, regional disparities are prominent, with northeastern and western states achieving the most significant reductions, while the Ohio Valley and Rockies are likely to experience higher emissions due to the reliance on fossil fuels. This study offers the first assessment of clean grid impacts on the WRRFs and highlights the need for targeted, region-specific strategies across different emission scopes. This research provides insights for policymakers and stakeholders in the wastewater sector, emphasizing the critical role of grid decarbonization in achieving GHG reduction goals.

Li, Xiatong↗
DOE OSTI2025

Diverging drivers of fungal diversity: seasonal effects shape aboveground communities, while geographical patterns govern belowground communities in rubber tree ecosystems

Understanding the spatiotemporal dynamics of microbial communities is essential for predicting their ecological roles and interactions with host plants. In a recent study, Wei and colleagues (Microbiol Spectr 13:e02097-24, 2024) investigated fungal diversity across multiple plant and soil compartments in rubber trees over two seasons and two geographically distinct regions in China. Their findings revealed that alpha diversity was primarily influenced by seasonal changes and physicochemical factors, while beta diversity exhibited a strong geographical pattern, shaped by leaf phosphorus and soil available potassium. These results highlight the role of environmental drivers in shaping within-community diversity, while other factors contribute to the differences between fungal communities across the soil–plant continuum. By distinguishing the effects of temporal and spatial factors, this study provides detailed insights into plant-associated microbiomes and emphasizes the need for further research on the functional implications of microbial diversity in the context of changing environmental and agricultural conditions.

fungal diversity↗
NASA NTRS2019

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

Dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extends from the interior to the corona and from fast turbulent motions to the global-Sun magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across the different layers, which contribute to the corona heating and eruptive dynamics, as well as interlinks between different layers of the solar interior and atmosphere. For modeling the global-scale activity we use the data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitation on the prediction accuracy. We present the EnKF predictions of the upcoming Solar Cycle 25 based on both the sunspot number series and observed magnetic fields, and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting the solar activity.

Kitiashvili, I. N.↗
DOE OSTI2025

Forecasting Multi-Step-Ahead Street-Scale Nuisance Flooding using a seq2seq LSTM Surrogate Model for Real-Time Application in a Coastal-Urban City

In coastal-urban cities facing an elevated risk of nuisance flooding (by rain and tide) due to increased heavy rainfall, sea level rise, urbanization, and aging drainage systems, real-time flood forecasting at the street-scale can provide useful information to transportation decision-makers. Physics-Based Models (PBMs) that offer high accuracy come with high computational runtimes and costs that limit their application for real-time flood forecasting. To address this challenge, Machine Learning (ML) surrogate models trained from PBMs have been proposed to provide street-scale flood forecasts. Previous related studies have focused on using Long Short-Term Memory (LSTM) architectures to model hourly flood depth on streets. While LSTM models can capture input sequences effectively, they fall short in accurately preserving output sequences, limiting their suitability for multi-step-ahead forecasts. The seq2seq LSTM architecture offers a key advantage here by capturing the full sequence of input–output, making it potentially more suitable for multi-step-ahead flood forecasts compared to traditional LSTM models. However, seq2seq LSTM has not been tested for street-scale flood forecasting, particularly for rapidly fluctuating nuisance flooding events which require special attention to its temporal sequences. Hence, in this study, we applied the seq2seq LSTM model to explore multi-step-ahead street-scale nuisance flooding and compared its results to the traditional LSTM model as a benchmark model. LSTM and seq2seq LSTM surrogate models were applied to 22 flood-prone streets in Norfolk, Virginia, as a case study with a 4-hr (short-term) and 8-hr (long-term) lead time. The models were trained with environmental (rainfall and tide) and topographic (elevation, Topographic Wetness Index, and Depth-To-Water) features along with PBM-derived water depths for different storm events. The results demonstrated satisfactory performance of both LSTM and seq2seq LSTM surrogate models throughout the forecast period compared to the PBM. However, the seq2seq LSTM showed lower Mean Absolute Error (MAE)/ Root Mean Square Error (RMSE) and higher Nash–Sutcliffe Efficiency (NSE)/ correlation than the LSTM across most lead times, particularly for long-term forecasting due to its supremacy in handling both input–output sequences together, which is missing in the traditional LSTM. For example, in the long-term, the average RMSE ranges were 0.0268–0.0373 m for LSTM and 0.0226–0.0319 m for seq2seq LSTM, while in the short-term, they were 0.0263–0.0293 m and 0.0261–0.0283 m, respectively. Additionally, while both models exhibited similar performance in distinguishing flooded and non-flooded streets for flood depth ≥ 0.1 m, the seq2seq LSTM model demonstrated superior performance for higher flood depths (such as ≥ 0.2 m and ≥ 0.3 m). Once trained, inference took only 0.09 to 0.11 s (short-term) and 0.30 to 0.35 s (long-term) per storm event for the 22 streets, making the application highly suitable for real-time decision-making during nuisance flood events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Computational Study of Flow Establishment in a Ram Accelerator

The temporal evolution of the combustion process established during projectile transition from the launch tube into the ram accelerator section containing an explosive hydrogen-oxygen-argon gas mixture is studied. The Navier-Stokes equations for chemically reacting flow are solved in a fully coupled manner, using an implicit, time accurate algorithm. The solution procedure is based on a spatially second order total variation diminishing scheme and a temporally second order, variable-step, backward differentiation formula method. The hydrogen-oxygen chemistry is modeled with a 9-species, 19-step mechanism. The accuracy of the solution method is first demonstrated by several benchmark calculations. Numerical simulations of two ram accelerator configurations are then presented. In particular, the temporal developments of shock-induced combustion and thrust forces are followed. Positive thrust is established in both cases; however, in one of the ram accelerator configurations studied, combustion in the boundary layer enhances its separation, ultimately resulting in unstart.

Yungster, S.↗
NASA NTRS2020

100-kHz Interferometric Rayleigh Scattering Flow Diagnostics at 266 nm

Interferometric Rayleigh scattering (IRS) is a laser-based technique capable of spatially and temporally resolved measurement of gas velocity and temperature in unseeded gaseous flows. In the present embodiment of the technique, IRS is performed at 266 nm for the first time. IRS at 266 nm is potentially much less susceptible to interferences from particles and other stray light sources. A pulse-burst laser and high-speed camera provided image rates of 100 kHz, allowing simultaneous space- and time-resolved measurement in high speed flow at multiple points along a line. The use of 266 nm excitation and detection is compared with prior work that used 532 nm. New experimental interferogram modelling and fitting techniques for single and multi-velocity-component IRS were demonstrated in a study of the spatial and temporal variation of the flow along a line through a supersonic jet. Single component velocity and temperature measurements using 266 nm were successfully made and compared with prior 532 nm results. Two-component velocity measurements at 266 nm, using the reflected image method, were compared to single-component measurements.

Andrew D Cutler↗
DOE OSTI2019

Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed

Changes in extreme precipitation events may require revisions of civil engineering standards to prevent water infrastructures from performing below the designated guidelines. Climate change may invalidate the intensity-duration-frequency (IDF) computation that is based on the assumption of data stationarity. Efforts in evaluating non-stationarity in the annual maxima series are inadequate, mostly due to the lack of long data records and convenient methods for detecting trends in the higher moments. In this study, using downscaled high resolution climate simulations of the historical and future periods under different carbon emission scenarios, we tested two solutions to obtain reliable IDFs under non-stationarity: (1) identify quasi-stationary time windows from the time series of interest to compute the IDF curves using data for the corresponding time windows; (2) introduce a parameter representing the trend in the means of the extreme value distributions. Focusing on a mountainous site, the Walker Watershed, the spatial heterogeneity and variability of IDFs or extremes are evaluated, particularly in terms of the terrain and elevation impacts. We compared observations-based IDFs that use the stationarity assumption with the two approaches that consider non-stationarity. The IDFs directly estimated based on the traditional stationarity assumption may underestimate the 100-year 24-h events by 10% to 60% towards the end of the century at most grids, resulting in significant under-designing of the engineering infrastructure at the study site. Strong spatial heterogeneity and variability in the IDF estimates suggest a preference for using high resolution simulation data for the reliable estimation of exceedance probability over data from sparsely distributed weather stations. Discrepancies among the three IDFs analyses due to non-stationarity are comparable to the spatial variability of the IDFs, underscoring a need to use an ensemble of non-stationary approaches to achieve unbiased and comprehensive IDF estimates.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Linear analysis of ion cyclotron interaction in a multicomponent plasma

The mechanism by which hot anisotropic protons generate electromagnetic ion cyclotron waves in a plasma containing cold H(+) and He(+) ions is quantitatively studied. Linear growth rates (both temporal and spatial) are computed for different plasma parameters: concentration, temperature,and anisotropy of cold He(+) ions and of hot protons. It is shown that: (1) for parameters typical of the geostationary altitude the maximum growth rates are not drastically changed when a small proportion (about 1 to 20 percent) of cold He(+) ions is present; (2) because of the important cyclotron absorption by thermal He(+) ions in the vicinity of the He(+) gyrofrequency, waves which could resonate with the bulk of the He(+) distribution cannot be generated. Therefore quasi-linear effects, in a homogeneous medium at least, cannot be responsible for the heating of He(+) ions which is often observed in conjunction with ion cyclotron waves. The variation of growth rate versus wave number is also studied for its importance in selecting suitable parameters in numerical simulation experiments.

Gendrin, R.↗
NASA NTRS1991

Potential vorticity index

Based on the European Center For Medium Range Weather Forecasting (ECMWF) First Global Atmospheric Research Program Global Experiment (FGGE) IIIb data set in the 1978 to 1979 winter, a potential vorticity (PV) index was defined as a measure of the zonally averaged, mid-latitude PV gradient on the 300 K isentropic surface in the Northern Hemisphere. The evolution of that index and its relation to teleconnection patterns of 500 mb geopotential height anomaly are studied. The results of the temporal and spatial variation of blocking and cyclogenesis in the 1978 to 1979 winter and its relation to global and local PV gradients were obtained. Complex empirical orthogonal function (EOF) analyses were performed, using the same FGGE data set for the 1978 to 1979 winter, for a representative high latitude band and mid latitude band geopotential height anomalies at 500 mb, phi sub h, phi sub m, and PV gradient at 300 K, delta(Q), at each longitude for the three month period. The focus of current research is the following: (1) to perform Fourier analyses for the first three EOF's of phi sub h, phi sub m, and delta(Q) at given latitude bands, and to find the dominant wavenumbers and frequencies which are responsible for these EOF's; (2) to compare the results from EOF and Fourier analyses which will be used to explore the relations of blocking and cyclogensis with local and global PV gradients; and (3) to study the time dependence of the local PV gradients and relate it to the PV index vacillation cycles observed in the PV index cycle.

Barcilon, Albert↗
NASA NTRS2000

Full Field Scalar Measurements in a Pulsating Helium Jet using Rainbow Schlieren Deflectometry

The flow structure of a pulsating helium jet was investigated using quantitative rainbow schlieren deflectometry. The operating parameters included the tube inside diameter, the jet Reynolds number and the jet Richardson number. The jet structure was characterized by the frequency spectrum, temporal evolution of the oscillations and mean and root-mean-square profiles of the species mole fraction, which in this case, was helium. Experiments were conducted using a variable nozzle facility. Angular deflection data were obtained using rainbow schlieren deflectometry across full field of color images taken at a temporal resolution of 60Hz. The flicker cycle was analyzed by instantaneous rainbow schlieren images, contour plots of deflection angle and helium mole fraction placed sequentially in time. Two observe the flow downstream, the tube was lowered with respect to the optical setup and images were taken at different axial planes. In this way, the laminar, transition and turbulent regions of the jet flow were observed. Abel inversion algorithm was utilized to reconstruct the refractive index field from the measurements of the beam deflection angle. The concentration field was then generated from the refractive index field. The phenomenon of vortex initiation and propagation in the flicker cycle was described by correlating the ray deflection angle and concentration contour plots. Experiments in the flickering jet reveal global oscillation in the flow field. The effect of jet exit Reynolds number and jet Richardson number on the flickering frequency was analyzed. The effect of jet Richardson number was more pronounced than that of the jet exit Reynolds number. The flow field was studies quantitatively in terms of temporal evolution and statistical description of helium mole fraction.

Pasumarthi, Kasyap S.↗
NASA NTRSDate not supplied

Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow

Applications of satellite data in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on the trade-offs to spatial, spectral and temporal resolutions of observations. In weather tracking, high-frequency temporal observations are critical and used to improve forecasts, study severe events, and extract atmospheric motion, among others. However, while the current generation of geostationary satellites have hemispheric coverage at 10-15 minute intervals, higher temporal frequency observations are ideal for studying mesoscale severe weather events. In this work, we apply a task specific optical flow approach to temporal up-sampling using deep convolutional neural networks. We apply this technique to 16-bands of GOES-R/Advanced Baseline Imager mesoscale dataset to temporally enhance full disk hemispheric snapshots of different spatial resolutions from 15 minutes to 1 minute. Experiments show the effectiveness of task specific optical flow and multi-scale blocks for interpolating high-frequency severe weather events relative to bilinear and global optical flow baselines. Lastly, we demonstrate strong performance in capturing variability during convective precipitation events.

Optical flow, temporal interpolation, geostationar↗
NASA NTRS2002

Transients in Pacific/North American Plate Boundary Deformation: Synthesis and Modeling of GPS and Borehole Strain Observations

This is the Final Technical Report on research conducted between 1 June 1997 and 14 September 2001 entitled "Transients in Pacific/North American plate boundary deformation: Synthesis and modeling of GPS and borehole strain observations." As the project title implies, our effort involved a geodetic study of strain transients, i.e., temporal variations in deformation rates, that occur within plate boundary zones and their relationship to earthquakes and plate motions. Important transients occur during and following large earthquakes, and there are also strain transients not apparently associated with earthquakes. A particularly intriguing class of transients, for which there is a modest but growing list of examples, are preseismic anomalies. Such earthquake precursors, if further documented and understood, would have obvious importance for earthquake hazard mitigation. Because the timescales for these diverse transients range over at least 6 orders of magnitude (minutes to years), no single geodetic technique is optimum. We therefore undertook a systematic synthesis of Global Positioning Satellite (GPS) and borehole strainmeter data in three areas in California where there are adequate numbers of both types of instruments (or their equivalent): the San Francisco Bay region (within the Bay Area Regional Deformation network), southern California (within the Southern California Integrated GPS Network), and Parkfield (where a two-color laser system provides a proxy for continuous GPS measurements). An integral component of our study was the elucidation of the physical mechanisms by which such transients occur and propagate. We therefore initiated the development of multiple forward models, using two independent approaches. In the first, we explored the response to specified earthquake slip in viscoelastic models that incorporated failure criteria and the geometry of major faults in California. In the second approach, we examined the dynamical response of a complex rheological medium to the application of a far-field stress imposed by plate motions. The forward models were used both to gain insight into the range of strain transients to be expected under different assumed mechanical conditions and to develop representations for strain fields that allow GPS, borehole, and other strain data to be combined in a self-consistent, yet well-determined, manner. The models also provided a basis for hypothesis testing, by which data from a strain transient well characterized by GPS and borehole observations were utilized to distinguish among competing candidates for the causative physical mechanism and the governing physical characteristics. During the three years of this project, continued to a fourth year through a no-cost extension of the grant, we published 14 papers and presented or co-authored 37 papers at national scientific meetings.

Solomon, Sean C.↗