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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Changes in the Temperature of Saturn's Stratosphere from 2002 to 2004 and Direct Evidence of a Mesopause

The state of a planetary stratosphere is intricately linked to the radiation it receives from its host star. The stellar flux impinging on the the planetary stratosphere affects the temperature and chemistry occurring there. The revolution of the planet about its orbit coupled to the planets axial tilt can cause variations in the amount of flux captured by the planet at a given latitude over the period of a year even if the flux output of the star is constant. This variation of stellar flux at a given latitude during the orbit of a planet is what causes seasons. Saturn, with its axial tilt of 27 degrees, experiences seasonal forcing much like the Earth, albeit with far less solar flux and a year equal to 30 Earth years. In an attempt to measure the effect seasonal forcing has on the temperature structure of Saturn's stratosphere, we have started a long term observing program. By observing Saturn with a high-resolution mid-infrared spectrograph in the v(sub 4) band of methane, we can infer the stratospheric temperature between the pressure levels of 10 and 0.01 mbar. We present latitudinally resolved observations of Saturn's southern hemisphere from 2002 and 2004. We have analyzed the data using a line-by-line radiative transfer model and inferred stratospheric temperatures and winds. We compare the temperatures from the two observing runs and the predictions of a stratospheric seasonal climate model. The zonal winds in the southern hemisphere, between the 10 and 0.01 mbar pressure levels, will be shown and discussed.

Greathouse, Thomas K.↗
DOE OSTI2013

PHIBSS: MOLECULAR GAS, EXTINCTION, STAR FORMATION, AND KINEMATICS IN THE z = 1.5 STAR-FORMING GALAXY EGS13011166

We report matched resolution imaging spectroscopy of the CO 3-2 line (with the IRAM Plateau de Bure millimeter interferometer) and of the H{alpha} line (with LUCI at the Large Binocular Telescope) in the massive z = 1.53 main-sequence galaxy EGS 13011166, as part of the ''Plateau de Bure high-z, blue-sequence survey'' (PHIBSS: Tacconi et al.). We combine these data with Hubble Space Telescope V-I-J-H-band maps to derive spatially resolved distributions of stellar surface density, star formation rate, molecular gas surface density, optical extinction, and gas kinematics. The spatial distribution and kinematics of the ionized and molecular gas are remarkably similar and are well modeled by a turbulent, globally Toomre unstable, rotating disk. The stellar surface density distribution is smoother than the clumpy rest-frame UV/optical light distribution and peaks in an obscured, star-forming massive bulge near the dynamical center. The molecular gas surface density and the effective optical screen extinction track each other and are well modeled by a ''mixed'' extinction model. The inferred slope of the spatially resolved molecular gas to star formation rate relation, N = dlog{Sigma}{sub starform}/dlog{Sigma}{sub molgas}, depends strongly on the adopted extinction model, and can vary from 0.8 to 1.7. For the preferred mixed dust-gas model, we find N = 1.14 {+-} 0.1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Multi-frequency Scatter Broadening Evolution of Pulsars. I

We present multi-wavelength scatter broadening observations of 47 pulsars made with the Giant Metre-wave Radio Telescope (GMRT), Ooty Radio Telescope (ORT), and Long Wavelength Array (LWA). The GMRT observations were made in the phased array mode at 148, 234, and 610 MHz and the ORT observations at 327 MHz. The LWA data sets were obtained from the LWA pulsar data archive. The broadening of each pulsar as a function of observing frequency provides the frequency scaling index, α. The estimations of α have been obtained for 39 pulsars and include entirely new estimates for 31 pulsars. This study increases the total sample of pulsars available with α estimates by ∼50%. The overall distribution of α with the dispersion measure (DM) of the pulsar shows interesting variations, which are consistent with earlier studies. However, for a given value of DM, a range of α values are observed, indicating the characteristic turbulence along each line of sight. For each pulsar, the estimated level of turbulence, C{sub n{sub e}{sup 2}}, has also been compared with α and DM. Additionally, we compare the distribution of α with the theoretically predicted model to infer the general characteristics of the ionized interstellar medium. Nearly 65% of the pulsars show a flatter index (i.e., α<4.4) than that expected from the Kolmogorov turbulence model. Moreover, the group of pulsars with flatter indices is typically associated with an enhanced value of C{sub n{sub e}{sup 2}} compared to those with steeper indices.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Constraining Hydrological and Cryospheric Mass Flux in Southeastern Alaska using Space-Based Gravity Measurements

Watersheds draining into the Gulf of Alaska (GoA) experience large seasonal and inter-annual variations of water in the form of rain, snow, and ice, but accurate constraints on these variations have been difficult to obtain. Over larger geographic regions, water variations can be inferred directly from the Gravity Recovery and Climate Experiment (GRACE) data. However, because GoA variations occur over such a small region, the inferred average value of water flux increases as the applied smoothing of the GRACE data decreases. We use this observed scaling together with scaling results obtained from forward models to infer a seasonal amplitude of 115 plus or minus 20 cubic kilometers of water and an average contribution to sea level rise over the two years of data of 0.31 plus or minus 0.09 millimeters per year. These results suggest that accelerated melting that began in the late 1990s, as inferred from altimetry, continues unabated.

Tamisiea, M. E.↗
DOE OSTI2014

Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bring out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.

Sanfilippo, Antonio P.↗
DOE OSTI2017

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Morton, April↗
DOE OSTI2015

Electric field and temperature dependence of dielectric permittivity in strontium titanate investigated by a photoemission study on Pt/SrTiO{sub 3}:Nb junctions

Schottky junctions made from platinum and niobium-doped strontium titanate (SrTiO{sub 3}:Nb) were investigated by hard X-ray photoemission (HXPES) and through a band bending behavior simulation using a phenomenological model, which assumes a decrease in dielectric constant due to an electric field. Thus, we confirmed that the observed HXPES spectra at relatively high temperatures, e.g., >250 K, were well simulated using this phenomenological model. In contrast, it was inferred that the model was not appropriate for junction behavior at lower temperatures, e.g., <150 K. Therefore, a reconstruction of the phenomenological model is necessary to adequately explain the dielectric properties of SrTiO{sub 3}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

QUASI-PERIODIC OSCILLATIONS AND BROADBAND VARIABILITY IN SHORT MAGNETAR BURSTS

The discovery of quasi-periodic oscillations (QPOs) in magnetar giant flares has opened up prospects for neutron star asteroseismology. However, with only three giant flares ever recorded, and only two with data of sufficient quality to search for QPOs, such analysis is seriously data limited. We set out a procedure for doing QPO searches in the far more numerous, short, less energetic magnetar bursts. The short, transient nature of these bursts requires the implementation of sophisticated statistical techniques to make reliable inferences. Using Bayesian statistics, we model the periodogram as a combination of red noise at low frequencies and white noise at high frequencies, which we show is a conservative approach to the problem. We use empirical models to make inferences about the potential signature of periodic and QPOs at these frequencies. We compare our method with previously used techniques and find that although it is on the whole more conservative, it is also more reliable in ruling out false positives. We illustrate our Bayesian method by applying it to a sample of 27 bursts from the magnetar SGR J0501+4516 observed by the Fermi Gamma-ray Burst Monitor, and we find no evidence for the presence of QPOs in any of the bursts in the unbinned spectra, but do find a candidate detection in the binned spectra of one burst. However, whether this signal is due to a genuine quasi-periodic process, or can be attributed to unmodeled effects in the noise is at this point a matter of interpretation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Modeling neutrino-induced scale-dependent galaxy clustering for photometric galaxy surveys

Abstract The increasing statistical precision of photometric redshift surveys requires improved accuracy of theoretical predictions for large-scale structure observables to obtain unbiased cosmological constraints. In ΛCDM cosmologies, massive neutrinos stream freely at small cosmological scales, suppressing the small-scale power spectrum. In massive neutrino cosmologies, galaxy bias modeling needs to accurately relate the scale-dependent growth of the underlying matter field to observed galaxy clustering statistics. In this work, we implement a computationally efficient approximation of the neutrino-induced scale-dependent bias (NISDB). Through simulated likelihood analyses of Dark Energy Survey Year 3 (DESY3) and Legacy Survey of Space and Time Year 1 (LSSTY1) synthetic data that contain an appreciable NISDB, we examine the impact of linear galaxy bias and neutrino mass modeling choices on cosmological parameter inference. We find model misspecification of the NISDB approximation and neutrino mass models to decrease the constraining power of photometric galaxy surveys and cause parameter biases in the cosmological interpretation of future surveys. We quantify these biases and devise mitigation strategies.

Astronomy & Astrophysics↗
NASA NTRS2011

Verification of Small Hole Theory for Application to Wire Chaffing Resulting in Shield Faults

Our work is focused upon developing methods for wire chafe fault detection through the use of reflectometry to assess shield integrity. When shielded electrical aircraft wiring first begins to chafe typically the resulting evidence is small hole(s) in the shielding. We are focused upon developing algorithms and the signal processing necessary to first detect these small holes prior to incurring damage to the inner conductors. Our approach has been to develop a first principles physics model combined with probabilistic inference, and to verify this model with laboratory experiments as well as through simulation. Previously we have presented the electromagnetic small-hole theory and how it might be applied to coaxial cable. In this presentation, we present our efforts to verify this theoretical approach with high-fidelity electromagnetic simulations (COMSOL). Laboratory observations are used to parameterize the computationally efficient theoretical model with probabilistic inference resulting in quantification of hole size and location. Our efforts in characterizing faults in coaxial cable are subsequently leading to fault detection in shielded twisted pair as well as analysis of intermittent faulty connectors using similar techniques.

Schuet, Stefan R.↗
DOE OSTI2018

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979–2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Marvel, Kate↗
DOE OSTI2014

Exploring the blazar zone in high-energy flares of FSRQs

The gamma-ray emission offers a powerful diagnostic tool to probe jets and their surroundings in flat-spectrum radio quasars (FSRQs). In particular, sources emitting at high energies (>10 GeV) give us the strongest constraints. This motivates us to start a systematic study of flares with bright emission above 10 GeV, examining archival data of the Fermi-LAT gamma-ray telescope. At the same time, we began to trigger Target of Opportunity observations to the Swift observatory at the occurrence of high-energy flares, obtaining a wide coverage of the spectral energy distributions (SEDs) for several FSRQs during flares. Among others, we investigate the SED of a peculiar flare of 3C 454.3, showing a remarkably hard gamma-ray spectrum, quite different from the brightest flares of this source, and a bright flare of CTA 102. We modeled the SED in the framework of the one-zone leptonic model, using also archival optical spectroscopic data to derive the luminosity of the broad lines and thus estimate the disk luminosity, from which the structural parameters of the FSRQ nucleus can be inferred. The model allowed us to evaluate the magnetic field intensity in the blazar zone and to locate the emitting region of gamma-rays in the particular case in which gamma-ray spectra show neither absorption from the broad-line region (BLR) nor the Klein-Nishina curvature expected in leptonic models assuming the BLR as the source of seed photons for the External Compton scenario. For FSRQs bright above 10 GeV, we were able to identify short periods lasting less than one day characterized by a high rate of high-energy gamma-rays and hard gamma-ray spectra. We discussed the observed spectra and variability timescales in terms of injection and cooling of energetic particles, arguing that these flares could be triggered by magnetic reconnection events or turbulence in the flow.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Computer Modeling and Simulation

Verification and validation of computer codes and models used in simulation are two aspects of the scientific practice of high importance and have recently been discussed by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to model’s relation to the real world and its intended use. It has been argued that because complex simulations are generally not transparent to a practitioner, the Duhem problem can arise for verification and validation due to their entanglement; such an entanglement makes it impossible to distinguish whether a coding error or model’s general inadequacy to its target should be blamed in the case of the model failure. I argue that in order to disentangle verification and validation, a clear distinction between computer modeling (construction of mathematical computer models of elementary processes) and simulation (construction of models of composite objects and processes by means of numerical experimenting with them) needs to be made. Holding on to that distinction, I propose to relate verification (based on theoretical strategies such as inferences) to modeling and validation, which shares the common epistemology with experimentation, to simulation. To explain reasons of their intermittent entanglement I propose a weberian ideal-typical model of modeling and simulation as roles in practice. I suggest an approach to alleviate the Duhem problem for verification and validation generally applicable in practice and based on differences in epistemic strategies and scopes

Pronskikh, V. S.↗
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.↗
DOE OSTI2015

Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

We construct a new framework for accelerating Markov chain Monte Carlo in posterior sampling problems where standard methods are limited by the computational cost of the likelihood, or of numerical models embedded therein. Our approach introduces local approximations of these models into the Metropolis–Hastings kernel, borrowing ideas from deterministic approximation theory, optimization, and experimental design. Previous efforts at integrating approximate models into inference typically sacrifice either the sampler’s exactness or efficiency; our work seeks to address these limitations by exploiting useful convergence characteristics of local approximations. We prove the ergodicity of our approximate Markov chain, showing that it samples asymptotically from the exact posterior distribution of interest. We describe variations of the algorithm that employ either local polynomial approximations or local Gaussian process regressors. Our theoretical results reinforce the key observation underlying this article: when the likelihood has some local regularity, the number of model evaluations per Markov chain Monte Carlo (MCMC) step can be greatly reduced without biasing the Monte Carlo average. Numerical experiments demonstrate multiple order-of-magnitude reductions in the number of forward model evaluations used in representative ordinary differential equation (ODE) and partial differential equation (PDE) inference problems, with both synthetic and real data. Supplementary materials for this article are available online.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Altering Terahertz Sound Propagation in a Liquid upon Nanoparticle Immersion

One of the grand challenges of new generation Condensed Matter physicists is the development of novel devices enabling the control of sound propagation at terahertz frequency. Indeed, phonon excitations in this frequency window are the leading conveyor of heat transfer in insulators. Their manipulation is thus critical to implementing heat management based on the structural design. To explore the possibility of controlling the damping of sound waves, we used high spectral contrast Inelastic X-ray Scattering (IXS) to comparatively study terahertz acoustic damping in a dilute suspension of 50 nm nanospheres in glycerol and on pure glycerol. Bayesian inference-based modeling of measured spectra indicates that, at sufficiently large distances, the spectral contribution of collective modes in the glycerol suspension becomes barely detectable due to the enhanced damping, the weakening, and the slight softening of the dominant acoustic mode.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond those of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.

Bioinformatics, Visualisation, Transcription, Regu↗