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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Freezing Behavior of Stratospheric Sulfate Aerosols Inferred from Trajectory Studies

Temperature histories based on 10-day back growth trajectories for six ER-2 flights during AASE I (1989) and AAOE (1987) are presented. These trajectories along with the properties of the observed PSC (polar stratospheric cloud) particles are used here to infer the physical state of the pre-existing sulfuric acid aerosols. Of all the ER-2 flights described here, only the PSCs observed on the flights of January 24 and 25, 1989 are consistent with the thermodynamics of liquid ternary solutions of H2SO4/HNO3/H2O Ib PSCs). For these two days, back trajectories indicate that the air mass was exposed to SAT (sulfuric acid tetrahydrate) melting temperatures about 24 hours prior to being sampled by the ER-2. For the remaining ER-2 flights (January, 16, 19, and 20 for the AASE I campaign and August 17 for the AAOE campaign), the observed PSCs were probably composed of amorphous solid solutions of HNO3 and H2O (Type Ic PSCs). Formation of such Type Ic PSCs requires the presence of solid H2SO4 aerosols since liquid aerosols yield ternary solutions. The 10-day back trajectories of these flights indicate that the air mass was not exposed to SAT melting temperatures during the past week and had experienced cooling/warming cycles prior to being sampled by the ER-2. These temperature histories, recent laboratory measurements and the properties of glassy solids suggest that stratospheric H2SO4 aerosols may undergo a phase transition to SAT upon warming at approximately 198 K after going through a cooling cycle to about 194 K or lower.

Tabazadeh, A.↗
NASA NTRS1998

Approximation Of Multi-Valued Inverse Functions Using Clustering And Sugeno Fuzzy Inference

Finding the inverse of a continuous function can be challenging and computationally expensive when the inverse function is multi-valued. Difficulties may be compounded when the function itself is difficult to evaluate. We show that we can use fuzzy-logic approximators such as Sugeno inference systems to compute the inverse on-line. To do so, a fuzzy clustering algorithm can be used in conjunction with a discriminating function to split the function data into branches for the different values of the forward function. These data sets are then fed into a recursive least-squares learning algorithm that finds the proper coefficients of the Sugeno approximators; each Sugeno approximator finds one value of the inverse function. Discussions about the accuracy of the approximation will be included.

Walden, Maria A.↗
NASA NTRS2000

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data

We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays. The essential steps are (I) clustering many genes by their expression time-course data into a minimal set of clusters of co-expressed genes, (2) theoretically modeling the various conditions under which the time-courses are measured using a continuous-time analog recurrent neural network for the cluster mean time-courses, (3) fitting such a regulatory model to the cluster mean time courses by simulated annealing with weight decay, and (4) analysing several such fits for commonalities in the circuit parameter sets including the connection matrices. This procedure can be used to assess the adequacy of existing and future gene expression time-course data sets for determining transcriptional regulatory relationships such as coregulation.

Mjolsness, Eric↗
NASA NTRS2000

Measured Correlation Between Roll-Vortex Signatures and Radar-Inferred Sea Surface Roughness

This paper presents aircraft measurements of near-surface atmospheric boundary layer roll signatures and radar-derived sea surface roughness. These data are completely coincident in space and time and this unique feature supports attempts to definitively link SAR backscatter signatures to boundary layer roll impacts. The open-ocean data were collected at an altitude of 20 in from NOAA's Long-EZ aircraft using its turbulence probe and down-looking Ka-band radar scatterometer, Several flight legs of 20-30 km were flown with a heading across the wind direction, which is also roughly perpendicular to the roll vortices. We find remarkable correlation between measured modulations in the along-wind component of wind speed and radar backscatter for the spatial scale of I to 1.5 kin. Close agreement between normalized modulation amplitudes suggests the radar-inferred surface slope variance is changing linearly with wind speed. These data were collected within 30 minutes of a RADARSAT SAR overpass where apparent boundary layer impacts of the same orientation and spatial dimension are prevalent in the SAR backscatter image. Quantitative comparison between modulations in the aircraft and satellite radar data will be discussed.

Vandemark, Douglas↗
NASA NTRS1999

Climate Change on Mars Inferred from Erosion Rates at the Mars Pathfinder Landing Site

The observation that the Mars Pathfinder landing site probably looks very similar to when it was deposited by catastrophic floods some 1.8-3.5 Ga allows quantitative constraints to be placed on the rate of change at the landing site since that time. When combined with interpretations of data recently returned by the Mars Pathfinder and Global Surveyor missions and perspectives drawn from 20 years of analysis and interpretation of Viking data, these observations and inferences suggest an early warmer and wetter environment with vastly different erosion rates and a major climatic change on Mars. Additional information is contained in the original extended abstract.

Golombek, M. P.↗
NASA NTRS2001

A Comparison of Seasonal and Interannual Variability of Soil Dust Aerosols Over the Atlantic Ocean as Inferred by the Toms AI and AVHRR AOT Retrievals

The seasonal cycle and interannual variability of two estimates of soil (or 'mineral') dust aerosols are compared: Advanced Very High Resolution Radiometer (AVHRR) aerosol optical thickness (AOT) and Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI), Both data sets, comprising more than a decade of global, daily images, are commonly used to evaluate aerosol transport models. The present comparison is based upon monthly averages, constructed from daily images of each data set for the period between 1984 and 1990, a period that excludes contamination from volcanic eruptions. The comparison focuses upon the Northern Hemisphere subtropical Atlantic Ocean, where soil dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set. While each retrieval is sensitive to a different aerosol radiative property - absorption for the TOMS AI versus reflectance for the AVHRR AOT - the seasonal cycles of dust loading implied by each retrieval are consistent, if seasonal variations in the height of the aerosol layer are taken into account when interpreting the TOMS AI. On interannual time scales, the correlation is low at most locations. It is suggested that the poor interannual correlation is at least partly a consequence of data availability. When the monthly averages are constructed using only days common to both data sets, the correlation is substantially increased: this consistency suggests that both TOMS and AVHRR accurately measure the aerosol load in any given scene. However, the two retrievals have only a few days in common per month so that these restricted monthly averages have a large uncertainty. Calculations suggest that at least 7 to 10 daily images are needed to estimate reliably the average dust load during any particular month, a threshold that is rarely satisfied by the AVHRR AOT due to the presence of clouds in the domain. By rebinning each data set onto a coarser grid, the availability of the AVHRR AOT is increased during any particular month, along with its interannual correlation with the TOMS AI The latter easily exceeds the sampling threshold due to its greater ability to infer the aerosol load in the presence of clouds. Whether the TOMS AI should be regarded as a more reliable indicator of interannual variability depends upon the extent of contamination by sub-pixel clouds.

Cakmur, R. V.↗
NASA NTRS2000

Comparison of Global Distributions of Zonal-Mean Gravity Wave Variance Inferred from Different Satellite Instruments

Gravity wave temperature fluctuations acquired by the CRISTA instrument are compared to previous estimates of zonal-mean gravity wave temperature variance inferred from the LIMS, MLS and GPS/MET satellite instruments during northern winter. Careful attention is paid to the range of vertical wavelengths resolved by each instrument. Good agreement between CRISTA data and previously published results from LIMS, MLS and GPS/MET are found. Key latitudinal features in these variances are consistent with previous findings from ground-based measurements and some simple models. We conclude that all four satellite instruments provide reliable global data on zonal-mean gravity wave temperature fluctuations throughout the middle atmosphere.

Preusse, Peter↗
NASA NTRS2002

Visual Inference Programming

The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

Wheeler, Kevin↗
NASA NTRS2003

Questions Revisited: A Close Examination of Calculus of Inference and Inquiry

In this paper I examine more closely the way in which probability theory, the calculus of inference, is derived from the Boolean lattice structure of logical assertions ordered by implication. I demonstrate how the duality between the logical conjunction and disjunction in Boolean algebra is lost when deriving the probability calculus. In addition, I look more closely at the other lattice identities to verify that they are satisfied by the probability calculus. Last, I look towards developing the calculus of inquiry demonstrating that there is a sum and product rule for the relevance measure as well as a Bayes theorem. Current difficulties in deriving the complete inquiry calculus will also be discussed.

Knuth, Kevin H.↗
NASA NTRS2004

Multivariate Statistical Inference of Lightning Occurrence, and Using Lightning Observations

Two classes of multivariate statistical inference using TRMM Lightning Imaging Sensor, Precipitation Radar, and Microwave Imager observation are studied, using nonlinear classification neural networks as inferential tools. The very large and globally representative data sample provided by TRMM allows both training and validation (without overfitting) of neural networks with many degrees of freedom. In the first study, the flashing / or flashing condition of storm complexes is diagnosed using radar, passive microwave and/or environmental observations as neural network inputs. The diagnostic skill of these simple lightning/no-lightning classifiers can be quite high, over land (above 80% Probability of Detection; below 20% False Alarm Rate). In the second, passive microwave and lightning observations are used to diagnose radar reflectivity vertical structure. A priori diagnosis of hydrometeor vertical structure is highly important for improved rainfall retrieval from either orbital radars (e.g., the future Global Precipitation Mission "mothership") or radiometers (e.g., operational SSM/I and future Global Precipitation Mission passive microwave constellation platforms), we explore the incremental benefit to such diagnosis provided by lightning observations.

Boccippio, Dennis↗
NASA NTRS1999

Molecular evolution inferred from small subunit rRNA sequences: what does it tell us about phylogenetic relationships and taxonomy of the parabasalids?

The Parabasala are a primitive group of protists divided into two classes: the trichomonads and the hypermastigids. Until recently, phylogeny and taxonomy of parabasalids were mainly based on the comparative analysis of morphological characters primarily linked to the development of their cytoskeleton. Recent use of molecular markers, such as small subunit (SSU) rRNA has led to now insights into the systematics of the Parabasala and other groups of prolists. An updated phylogeny based on SSU rRNA is provided and compared to that inferred from ultrastructural data. The SSU rRNA phylogeny contradicts the dogma equating simple characters with pumitive characters. Hypermastigids, possessing a hyperdeveloped cytoskeleton, exhibit the most basal emergence in the parabasalid lineage. Other observations emerge from the SSU rRNA analysis, such as the secondary loss of some cytoskeleton structures in all representatives of the Monocercomonadidae, the existence of secondarily free living taxa (reversibility of parasitism) and the evidence against the co-evolution of the endobiotic parabasalids and their animal hosts. According to phylogenies based on SSU rRNA, all the trichomonad families are not monophyletic groups, putting into question the validity of current taxonomic assignments. The precise branching order of some taxa remains unclear, but this issue can possibly be addressed by the molecular analysis of additional parabasalids. The goal of such additional analyses would be to propose, in a near future, a revision of the taxonomy of this group of protists that takes into account both molecular and morphological data.

NASA Discipline Exobiology↗
NASA NTRS2005

Seismic Study of the Solar Interior: Inferences from SOI/MDI Observations During Solar Activity

Work on the structure, asphericity and dynamics of the solar interior from p-mode frequencies and frequency splittings was carried out primarily in collaboration with Dr. Eff-Darwich (University of La Laguna, Tenerife). This ongoing collaboration produced new results for the inversion of the internal solar rotation rate and further development in inversion methodologies. It also resulted in inferences on the solar stratification. Substantial progress towards the characterization of high-degree p-modes has been achieved. In collaboration with Drs. Rabello-Soares and Schou (Stanford University), we have gained a clear conceptual understanding of the various elements that affect the leakage matrix of the SOI/MDI instrument. This work has precise implications on the properties and the characterization of the HMI instrument being developed for the SDO mission.

Korzennik, Sylvain G.↗
NASA NTRS2005

Bayesian Inference in Satellite Gravity Inversion

To solve a geophysical inverse problem means applying measurements to determine the parameters of the selected model. The inverse problem is formulated as the Bayesian inference. The Gaussian probability density functions are applied in the Bayes's equation. The CHAMP satellite gravity data are determined at the altitude of 400 kilometer altitude over the South part of the Pannonian basin. The model of interpretation is the right vertical cylinder. The parameters of the model are obtained from the minimum problem solved by the Simplex method.

Kis, K. I.↗
NASA NTRS2005

Zonal-Mean Temperature Variations Inferred from SABER Measurements on TIMED Compared with UARS Observations

In the Numerical Spectral Model (NSM, Mayr et al., 2003), small-scale gravity waves propagating in the north/south direction can generate zonal mean (m = 0) meridional wind oscillations with periods between 2 and 4 months. These oscillations tend to be confined to low latitudes and have been interpreted to be the meridional counterpart of the wave-driven Quasi Biennial Oscillation in the zonal circulation. Wave driven meridional winds across the equator should generate, due to dynamical heating and cooling, temperature oscillations with opposite phase in the two hemispheres. We have analyzed SABER temperature measurements in the altitude range between 55 and 95 km to investigate the existence such variations. Because there are also strong tidal signatures (up to approximately 20 K) in the data, our algorithm estimates both mean values and tides together from the data. Based on SABER temperature data, the intra-annual variations with periods between 2 and 4 months can have amplitudes up to 5 K or more, depending on the altitude. Their amplitudes are in qualitative agreement with those inferred Erom UARS data (from different years). The SABER temperature variations also reveal pronounced hemispherical asymmetries, which are qualitatively consistent with wave driven meridional wind oscillations across the equator. Oscillations with similar periods have been seen in the meridional winds based on UARS data (Huang and Reber, 2003).

Huang, Frank T.↗
NASA NTRS1993

Latitudinal Variation of Solar Wind Speed and Mass Flux in the Acceleration Region of the Solar Wind during Solar Minimum Inferred from Spectral Broadening measurements

In this paper, we use an aggregate of S-band 2.3 GHz (13 cm) spectral broadening observations conducted during solar minimum conditions by the Mariner 4, Pioneer 10, Mariner 10, Helios 1 & 2 and Viking spacecraft to infer the first measurements of the latitudinal variation of solar wind speed and mass flux in the acceleration region of the solar wind at 3-8 R(sub o).

latitudinal variation of solar wind mass flux in a↗
NASA NTRS2007

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Santanello, Joseph A.↗
NASA NTRS2005

Rheology of the Ronne Ice Shelf, Antarctica, Inferred from Satellite Radar Interferometry Data using an Inverse Control Method

The Antarctic Ice Sheet is surrounded by large floating ice shelves that spread under their own weight into the ocean. Ice shelf rigidity depends on ice temperature and fabrics, and is influenced by ice flow and the delicate balance between bottom and surface accumulation. Here, we use an inverse control method to infer the rigidity of the Ronne Ice Shelf that best matches observations of ice velocity from satellite radar interferometry. Ice rigidity, or flow law parameter B, is shown to vary between 300 and 900 kPa a(sup 1/3). Ice is softer along the side margins due to frictional heating, and harder along the outflow of large glaciers, which advect cold continental ice. Melting at the bottom surface of the ice shelf increases its rigidity, while freezing decreases it. Accurate numerical modelling of ice shelf flow must account for this spatial variability in mechanical characteristics.

ice velocity↗