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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Delineation of soil temperature regimes from HCMM data

Evaluation of LANDSAT and Heat Capacity Mapping Mission (HCMM) data as input into National Cooperative Soil Survey is discussed. Signature classification techniques were applied to 13 May 76 LANDSAT data. LANDSAT data was overlaid with HCMM data, revealing registration problems caused by a shortage of control points in LANDSAT data, and the WARP program developed to improve registration accuracy. Initial images for control point selection were produced using digital terrain elevation data. Statistical procedures for evaluating data classification and to describe spatial distribution of surface temperature and its correlation with soil surface conditions were investigated.

Day, R. L.↗
NASA NTRS1983

Crustal geomagnetic field - Two-dimensional intermediate-wavelength spatial power spectra

Two-dimensional Fourier spatial power spectra of equivalent magnetization values are presented for a region that includes a large portion of the western United States. The magnetization values were determined by inversion of POGO satellite data, assuming a magnetic crust 40 km thick, and were located on an 11 x 10 array with 300 km grid spacing. The spectra appear to be in good agreement with values of the crustal geomagnetic field spatial power spectra given by McLeod and Coleman (1980) and with the crustal field model given by Serson and Hannaford (1957). The spectra show evidence of noise at low frequencies in the direction along the satellite orbital track (N-S). indicating that for this particular data set additional filtering would probably be desirable. These findings illustrate the value of two-dimensional spatial power spectra both for describing the geomagnetic field statistically and as a guide for diagnosing possible noise sources.

Mcleod, M. G.↗
NASA NTRS1983

Statistical mechanics of neocortical interactions - Dynamics of synaptic modification

A recent study has demonstrated that several scales of neocortical interactions can be consistently analyzed with the use of methods of modern nonlinear nonequilibrium statistical mechanics. The formation, stability, and interaction of spatial-temporal patterns of columnar firings are explicitly calculated, to test hypothesized mechanisms relating to information processing. In this context, most probable patterns of columnar firings are associated with chemical and electrical synaptic modifications. It is stressed that synaptic modifications and shifts in most-probable firing patterns are highly nonlinear and interactive sets of phenomena. A detailed scenario of information processing is calculated of columnar coding of external stimuli, short-term storage via hysteresis, and long-term storage via synaptic modification.

Ingber, L.↗
NASA NTRS1984

Three-dimensional analysis of magnetometer array data

A technique is developed for mapping magnetic variation fields in three dimensions using data from an array of magnetometers, based on the theory of optimal linear estimation. The technique is applied to data from the Scandinavian Magnetometer Array. Estimates of the spatial power spectra for the internal and external magnetic variations are derived, which in turn provide estimates of the spatial autocorrelation functions of the three magnetic variation components. Statistical errors involved in mapping the external and internal fields are quantified and displayed over the mapping region. Examples of field mapping and of separation into external and internal components are presented. A comparison between the three-dimensional field separation and a two-dimensional separation from a single chain of stations shows that significant differences can arise in the inferred internal component.

Richmond, A. D.↗
NASA NTRS1986

The effect of the dynamic wet troposphere on VLBI measurements

Calculations using a statistical model of water vapor fluctuations yield the effect of the dynamic wet troposphere on Very Long Baseline Interferometry (VLBI) measurements. The statistical model arises from two primary assumptions: (1) the spatial structure of refractivity fluctuations can be closely approximated by elementary (Kolmogorov) turbulence theory, and (2) temporal fluctuations are caused by spatial patterns which are moved over a site by the wind. The consequences of these assumptions are outlined for the VLBI delay and delay rate observables. For example, wet troposphere induced rms delays for Deep Space Network (DSN) VLBI at 20-deg elevation are about 3 cm of delay per observation, which is smaller, on the average, than other known error sources in the current DSN VLBI data set. At 20-deg elevation for 200-s time intervals, water vapor induces approximately 1.5 x 10 to the minus 13th power s/s in the Allan standard deviation of interferometric delay, which is a measure of the delay rate observable error. In contrast to the delay error, the delay rate measurement error is dominated by water vapor fluctuations. Water vapor induced VLBI parameter errors and correlations are calculated. For the DSN, baseline length parameter errors due to water vapor fluctuations are in the range of 3 to 5 cm. The above physical assumptions also lead to a method for including the water vapor fluctuations in the parameter estimation procedure, which is used to extract baseline and source information from the VLBI observables.

Treuhaft, R. N.↗
NASA NTRS1987

Spectral characteristics and the extent of paleosols of the Palouse formation

Thematic mapping data was analyzed and verified by comparison to previously gathered transect samples and to aerial photographs. A bare-soil field with exposed paleosols characterized by slight enrichment of iron was investigated. Spectral relationships were first investigated statistically by creating a data set with DN values spatially matched as nearly as possible to field sample points. Chemical data for each point included organic carbon, free iron oxide, and amorphous iron content. The chemical data, DN values, and various band ratios were examined with the program package Statistix in order to find the combinations of reflectance data most likely to show a relationship which would dependably separate the exposed paleosols from the other soils. Cluster analysis and Fastclas classification procedures were applied to the most promising of the band ratio combinations.

Frazier, B. E.↗
NASA NTRS1987

Contextual classification on the massively parallel processor

Classifiers are often used to produce land cover maps from multispectral Earth observation imagery. Conventionally, these classifiers have been designed to exploit the spectral information contained in the imagery. Very few classifiers exploit the spatial information content of the imagery, and the few that do rarely exploit spatial information content in conjunction with spectral and/or temporal information. A contextual classifier that exploits spatial and spectral information in combination through a general statistical approach was studied. Early test results obtained from an implementation of the classifier on a VAX-11/780 minicomputer were encouraging, but they are of limited meaning because they were produced from small data sets. An implementation of the contextual classifier is presented on the Massively Parallel Processor (MPP) at Goddard that for the first time makes feasible the testing of the classifier on large data sets.

Tilton, James C.↗
NASA NTRS1987

Time-cumulated visible and infrared histograms used as descriptor of cloud cover

To study the statistical behavior of clouds for different climate regimes, the spatial and temporal stability of VIS-IR bidimensional histograms is tested. Also, the effect of data sampling and averaging on the histogram shapes is considered; in particular the sampling strategy used by the International Satellite Cloud Climatology Project is tested.

Seze, G.↗
NASA NTRS1990

Asymptotic modal analysis and statistical energy analysis

The sound field of a structural-acoustic enclosure was subject to experimental analysis and theoretical description in order to develop an efficient and accurate method for predicting sound pressure levels in enclosures such as aircraft fuselages. Asymptotic Modal Analysis (AMA) is the method under investigation. AMA is derived from classical modal analysis (CMA) by considering the asymptotic limit of the sound pressure level as the number of acoustic and/or structural modes approaches infinity. Using AMA, results identical to those of Statistical Energy Analysis (SEA) were obtained for the spatially-averaged sound pressure levels in the interior. AMA is systematically derived from CMA and therefore the degree of generality of the end result can be adjusted through the choice of appropriate simplifying assumptions. For example, AMA can be used to obtain local sound pressure levels at particular points inside the enclosure, or to include the effects of varying the size and/or location of the sound source. AMA theoretical results were compared with CMA theory and also with experiment for the case where the structural-acoustic enclosure is a rectangular cavity with part of one wall flexible and vibrating, while the rest of the cavity is rigid.

Dowell, Earl H.↗
NASA NTRS1992

Pervasive variability in the quiet solar transition region

Extreme UV spectroheliograms from an experimental time series are employed to investigate the nature of the quiet solar transition region with respect to temporal variability. A statistical treatment is developed to analyze the fraction of spatial elements that yield intensity variations significantly higher than the signal noise. The EUV intensity in every spatial resolution varies on a time scale of minutes by about 10-30 percent, and the fractional amplitude of the temporal variations is found to be nearly independent of mean intensity. The paper concludes that the quiet solar transition region is probably generated and modulated by small-scale magnetic activity, since the temporal variability in the transition region is spatially uniform and rather pervasive.

Rabin, Douglas↗
NASA NTRS2010

Investigating the Performance of the Jason-2/OSTM Radar Altimeter Over Lakes and Reservoirs

Many inland water investigations utilize archival and near-real time radar altimetry data to enable observation of the variation in surface water level. A multi-altimeter approach allows a more global outlook with improved spatial resolution, and combined long-term observations improve statistical analyses. Central to all programs is a performance assessment of each instrument. Here, we focus on data quantity and quality pertaining to the Poseidon-3 radar altimeter onboard the Jason-2/OSTM satellite.Utilizing an interim data set (IGDR), studies show that the new on-board DIODE/median and DIODE/DEM tracking modes are performing well, acquiring and maintaining the majority of lake and reservoir surfaces in varying terrains. The 20-Hz along-track resolution of the data, and particularly the availability of the range output from the ice-retracker algorithm, also improves the number of valid height measurements. Based on test-case lakes and reservoirs, output from the ice-retracker algorithm is also seen to have a clear advantage over the ocean-retracker having better height stability across calm and icy surfaces, a greater ability to gain coastline waters, and less sensitivity to loss of water surface when there is island contamination in the radar echo. Such on-board tracking and postprocessing retracking enables the lake waters to be quickly gained after coastline crossing. Values can range from <0.1 s to 2.5 s, but the majority of measurements are obtained in less than 0.4 s or <2.3 km from the coast. Validation exercises reveal that targets of 150 km2 surface area and 0.8 km width are able to be monitored offering greater potential to acquire lakes in the 100 C300 km2 size-category. Time series of height variations are also found to be accurate to 3 to 33 cm rms depending on target size and the presence of winter ice. These findings are an improvement over the IGDR/GDR results from the predecessor Jason-1 and TOPEX/Poseidon missions and can satisfy the accuracy requirements of both the science-related and operational lake study programs.

Birkett, C. M.↗
NASA NTRS1986

The role of high resolution observations in determining energy release and transport processes

With present observations from the Solar Maximum Mission, we are seeing a very selective sample of spatially large flares in the soft part (10 to 50 keV) of the hard X-ray spectrum. The spatial resolution is at best 5600 km with a corresponding time resolution of 4.5 s for adequate count statistics. This resolution gives rise to the following problems: We cannot resolve the minor radii of the loops involved or tell where and how the energy release occurs. The manner in which loops interact and the relationship between the soft and hard or approx 00 keV) parts of hard X-rays remains elusive. We cannot see how energy propagates in most cases. Thus it is desirable to determine the minimum increase in spatial and temporal resolution required to solve these problems. Spatially we need to resolve the minor radius of a small loop which is about 800 km or 1 arc s. Upper limits to observed speeds of conduction fronts and shocks are approx km/s with theoretical limits running about a factor of 2 higher. Thus, a compatible minimum time resolution is in the range of 0.2 to 0.4 s. With these spatial and temporal resolutions, sufficient count statistics are required to go up to approx 120 keV with a sufficient number of energy bands to obtain spectra.

Smith, D. F.↗
NASA NTRS1991

Intraseasonal oscillations in the global atmosphere. II - Southern Hemisphere

A systematic examination of oscillatory modes in the global atmosphere is completed by studying 12 years of 500 mb geopotential heights in the Southern Hemisphere. The data were band-pass filtered to focus on intraseasonal (IS) phenomena, and spatial empirical orthogonal functions (EOFs) were obtained. The leading principal components were subjected to singular spectrum analysis in order to identify nonlinear IS oscillations with high statistical confidence. In the Southern Hemisphere, the dominant mode has a period of 23 days, with spatial patterns carried by the second and third winter EOF of the IS band. It has a zonal wavenumber-four structure. The 40-day mode is second, and is dominated by wavenumbers three and four, while a 16-day mode is too weak to separate its spatial behavior from the previous two. The IS dynamics in the Southern Hemisphere is more complex and dominated by shorter wavenumbers than the Northern Hemisphere. No statistically significant correlations between the Southern Hemisphere and the tropics or the Northern Hemisphere are apparent in the IS band.

Ghil, Michael↗
NASA NTRS1987

Fine-scale motion in the central Orion nebula

The inner region of M42 has been mapped in the O III N1 forbidden line at an unprecedented combination of velocity and spatial resolution and photometric accuracy. Three separate velocity systems along the line of sight are identified. Differential mass flow is present in two of these systems. All three systems show random fluctuations in velocity well above their measurement errors. The point-by-point velocities are used to determine the diagnostic statistical parameter, the structure function. The random motions show correlation with spatial separation, as expected for turbulence; but comparison with the predictions of classical theory for nebular turbulence shows poor agreement. If Kolmogorov (1941, 1942) theory applies, then the energy must be input at many scales.

Castaneda, Hector O.↗
NASA NTRS1999

Statistical Quality Control of Moisture Data in GEOS DAS

A new statistical quality control algorithm was recently implemented in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The final step in the algorithm consists of an adaptive buddy check that either accepts or rejects outlier observations based on a local statistical analysis of nearby data. A basic assumption in any such test is that the observed field is spatially coherent, in the sense that nearby data can be expected to confirm each other. However, the buddy check resulted in excessive rejection of moisture data, especially during the Northern Hemisphere summer. The analysis moisture variable in GEOS DAS is water vapor mixing ratio. Observational evidence shows that the distribution of mixing ratio errors is far from normal. Furthermore, spatial correlations among mixing ratio errors are highly anisotropic and difficult to identify. Both factors contribute to the poor performance of the statistical quality control algorithm. To alleviate the problem, we applied the buddy check to relative humidity data instead. This variable explicitly depends on temperature and therefore exhibits a much greater spatial coherence. As a result, reject rates of moisture data are much more reasonable and homogeneous in time and space.

Dee, D. P.↗
DOE OSTI2025

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗
DOE OSTI2025

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗
NASA NTRS2017

Path Profiles of Cn2 Derived from Radiometer Temperature Measurements and Geometrical Ray Tracing

Atmospheric turbulence has significant impairments on the operation of Free-Space Optical (FSO) communication systems, in particular temporal and spatial intensity fluctuations at the receiving aperture resulting in power surges and fades, changes in angle of arrival, spatial coherence degradation, etc. The refractive index structure parameter Cn2 is a statistical measure of the strength of turbulence in the atmosphere and is highly dependent upon vertical height. Therefore to understand atmospheric turbulence effects on vertical FSO communication links such as space-to-ground links, it is necessary to specify Cn2 profiles along the atmospheric propagation path. To avoid the limitations on the applicability of classical approaches, propagation simulation through geometrical ray tracing is applied. This is achieved by considering the atmosphere along the optical propagation path as a spatial distribution of spherical bubbles with varying relative refractive index deviations representing turbulent eddies. The relative deviations of the refractive index are statistically determined from altitude-dependent and time-varying temperature fluctuations, as measured by a microwave profiling radiometer. For each representative atmosphere ray paths are analyzed using geometrical optics, which is particularly advantageous in situations of strong turbulence where there is severe wavefront distortion and discontinuity. The refractive index structure parameter is then determined as a function of height and time.

Atmospheric turbulence↗