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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Interpretation of Variations in Modis-Measured Greenness Levels of Amazon Forests During 2000 to 2009

This work investigates variations in satellite-measured greenness of Amazon forests using ten years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data. Corruption of optical remote sensing data with clouds and aerosols is prevalent in this region; filtering corrupted data causes spatial sampling constraints, as well as reducing the record length, which introduces large biases in estimates of greenness anomalies. The EVI data, analyzed in multiple ways and taking into account EVI accuracy, consistently show a pattern of negligible changes in the greenness levels of forests both in the area affected by drought in 2005 and outside it. Small random patches of anomalous greening and browning-especially prominent in 2009-appear in all ten years, irrespective of contemporaneous variations in precipitation, but with no persistence over time. The fact that over 90% of the EVI anomalies are insignificantly small-within the envelope of error (95% confidence interval) in EVI-warrants cautious interpretation of these results: there were no changes in the greenness of these forests, or if there were changes, the EVI data failed to capture these either because the constituent reflectances were saturated or the moderate resolution precluded viewing small-scale variations. This suggests a need for more accurate and spatially resolved synoptic views from satellite data and corroborating comprehensive ground sampling to understand the greenness dynamics of these forests.

MODIS↗
DOE OSTI2025

Resilient information and inference networks under mixed-trust sensing

With ubiquitous digitization, sensing, and computational intelligence deployed in increasingly more and broader domains, including critical infrastructure, potentially misleading and destabilizing effects of multimodal anomalies and adversarial behavior are growing in importance. Here, we develop randomized and reinforcement learning-based strategies for strategically recruiting and utilizing deployed (and, thus, vulnerable and potentially faulty and/or compromised) nodes from information and inference networks, while defending against adversaries that attempt to misguide assessments of inferred variables. Recognizing that, besides communication and other costs, sampling from any observable node can either provide true data or dangerously expose our inference to misinformation (without being easily distinguishable what actually happens), the proposed strategies proceed by progressively recruiting nodes and cautiously scaling their information contribution based on assumed, or, in our reinforcement learning approach, intelligently weighed trustworthiness, with the learning approach also considering network-wide, threat-inclusive risk/value tradeoffs. While avoiding the hardware, communication, analytical and computational burden of explicit redundancy, the proposed defensive schemes enable on-the-fly assessments of underlying processes, and system-wide situational awareness with demonstrable resilience against adversarial activities.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Stellar mass, not dynamical mass nor gravitational potential, drives the mass–metallicity relationship

The widely known relation between stellar mass and gas metallicity [mass–metallicity relation (MZR)] in galaxies is often ascribed to the higher capability of more massive systems to retain metals against the action of galactic outflows. In this scenario the stellar mass would simply be an indirect proxy of the dynamical mass or of the gravitational potential. We test this scenario by using a sample of more than 1000 star-forming galaxies from the MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) survey for which dynamical masses have been accurately determined. By using three different methods (average dispersion, partial correlation coefficients, and random forest), we unambiguously find that the gas metallicity depends primarily and fundamentally on the stellar mass. Once the dependence on stellar mass is taken into account, there is little or no dependence on either dynamical mass or gravitational potential (and, if anything, the metallicity dependence on the latter quantities is inverted). Our result indicates that the MZR is not caused by the retention of metals in more massive galaxies. The direct, fundamental dependence of metallicity on stellar mass suggests the much simpler scenario in which the MZR is just a consequence of the stellar mass being proportional to the integral of metals production in the galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach

Tomography can be used to reveal internal properties of a 3D object using any penetrating wave. Advanced tomographic imaging techniques, however, are vulnerable to both systematic and random errors associated with the experimental conditions, which are often beyond the capabilities of the state-of-the-art reconstruction techniques such as regularizations. Because they can lead to reduced spatial resolution and even misinterpretation of the underlying sample structures, these errors present a fundamental obstacle to full realization of the capabilities of next-generation physical imaging. In this work, we develop efficient and explicit recovery schemes of the most common experimental error: movement of the center of rotation during the experiment. We formulate new physical models to capture the experimental setup, and we devise new mathematical optimization formulations for reliable inversion of complex samples. We demonstrate and validate the efficacy of our approach on synthetic data under known perturbations of the center of rotation.

Nonlinear optimization↗
DOE OSTI2016

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are used for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The Color and Stellar Mass Dependence of Small-scale Galaxy Clustering in SDSS-III BOSS

We measure the color and stellar mass dependence of clustering in spectroscopic galaxies at 0.6 < z < 0.65 using data from the Baryon Oscillation Spectroscopic Survey component of the Sloan Digital Sky Survey. We greatly increase the statistical precision of our clustering measurements by using the cross-correlation of 66,657 spectroscopic galaxies to a sample of 6.6 million fainter photometric galaxies. The clustering amplitude w(R) is measured as the ratio of the mean excess number of photometric galaxies found within a specified radius annulus around a spectroscopic galaxy to that from a random photometric galaxy distribution. We recover many of the familiar trends at high signal-to-noise ratio. We find the ratio of the clustering amplitudes of red and blue massive galaxies to be w{sub red}/w{sub blue}=1.92±0.11 in our smallest annulus of 75–125 kpc. At our largest radii (2–4 Mpc), we find w{sub red}/w{sub blue}=1.24±0.05. Red galaxies therefore have denser environments than their blue counterparts at z ∼ 0.625, and this effect increases with decreasing radius. Irrespective of color, we find that w(R) does not obey a simple power-law relation with radius, showing a dip around 1 Mpc. Holding stellar mass fixed, we find a clear differentiation between clustering in red and blue galaxies, showing that clustering is not solely determined by stellar mass. Holding color fixed, we find that clustering increases with stellar mass, especially for red galaxies at small scales (more than a factor of 2 effect over 0.75 dex in stellar mass).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1960

A Homing Missile Control System to Reduce the Effects of Radome Diffraction

The problem of radome diffraction in radar-controlled homing missiles at high speeds and high altitudes is considered from the point of view of developing a control system configuration which will alleviate the deleterious effects of the diffraction. It is shown that radome diffraction is in essence a kinematic feedback of body angular velocities which causes the radar to sense large apparent line-of-sight angular velocities. The normal control system cannot distinguish between the erroneous and actual line-of-sight rates, and entirely wrong maneuvers are produced which result in large miss distances. The problem is resolved by adding to the control system a special-purpose computer which utilizes measured body angular velocity to extract from the radar output true line-of-sight information for use in steering the missile. The computer operates on the principle of sampling and storing the radar output at instants when the body angular velocity is low and using this stored information for maneuvering commands. In addition, when the angular velocity is not low the computer determines a radome diffraction compensation which is subtracted from the radar output to reduce the error in the sampled information. Analog simulation results for the proposed control system operating in a coplanar (vertical plane) attack indicate a potential decrease in miss distance to an order of magnitude below that for a conventional system. Effects of glint noise, random target maneuvers, initial heading errors, and missile maneuverability are considered in the investigation.

Smith, Gerald L.↗
NASA NTRS2004

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Evaluation of Estimates Using Independent Data - Part 2

Rainfall rate estimates from space-borne k&ents are generally accepted as reliable by a majority of the atmospheric science commu&y. One-of the Tropical Rainfall Measuring Mission (TRh4M) facility rain rate algorithms is based upon passive microwave observations fiom the TRMM Microwave Imager (TMI). Part I of this study describes improvements in the TMI algorithm that are required to introduce cloud latent heating and drying as additional algorithm products. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, OP5resolution estimates of surface rain rate over ocean fiom the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over forerunning algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm, and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly, 2.5 deg. -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data are limited, TMI estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with: (a) additional contextual information brought to the estimation problem, and/or; (b) physically-consistent and representative databases supporting the algorithm. A model of the random error in instantaneous, 0.5 deg-resolution rain rate estimates appears to be consistent with the levels of error determined from TMI comparisons to collocated radar. Error model modifications for non-raining situations will be required, however. Sampling error appears to represent only a fraction of the total error in monthly, 2S0-resolution TMI estimates; the remaining error is attributed to physical inconsistency or non-representativeness of cloud-resolving model simulated profiles supporting the algorithm.

Yang, Song↗
DOE OSTI2015

Sensitivities and correlations of critical experiments due to uncertainties of system parameters and nuclear data - 14416

With increasing demand on accuracy of criticality calculations, correlations between benchmark experiments due to system parameter uncertainties become of interest in bias determination. The impact of different interpretations of system parameter uncertainties on the calculation of covariances and correlations of k{sub eff} is discussed in this article. Following the suggestion of the OECD/NEA EGUACSA Benchmark phase IV [1], 21 experiments from the ICSBEP international Handbook of Evaluated Criticality Safety Benchmarks [2] are used for this analysis (LEU-COMP-THERM series 07, exp. 01-04 and 39, exp. 01-17). The experiments share certain assembly and fuel features and were carried out in the same lab. Therefore, correlations in the calculation of k{sub eff} appear. Correlation coefficients between experiments due to nuclear data uncertainties are calculated with TSUNAMI [3] and show high values for most experiments. For the correlation analysis due to system parameter uncertainties mainly two scenarios are considered: In scenario A all uncertain parameters are varied mutually for all fuel rods, representing a systematic deviation of the actual experimental setup from the design value. This analysis is performed for all experiments listed above. In scenario E certain parameters like the outer cladding diameter are varied for each fuel rod individually, representing a random scattering of the varied parameter. Scenarios B, C and D represent intermediate scenarios between A and E, which are discussed shortly. Uncertainty and sensitivity calculations of k{sub eff} on the uncertain experimental parameters based on Monte Carlo sampling are presented and discussed. The calculations were performed with SUnCISTT (Sensitivities and Uncertainties in Criticality Inventory and Source Term Tool [4]) and SCALE 6.1.2 [3]. For the 21 EGUACSA proposed experiments the outer cladding diameter is the leading effect for the uncertainty of k{sub eff} for scenario A. In contrast, for scenario E the impact of the cladding diameter on k{sub eff} cancels out due to rod wise variations leaving the fuel diameter as the leading effect. The correlation analysis based on system parameter uncertainties indicates a significant dependence of the correlation coefficients on the interpretation of the uncertainties. It shows high values for scenario A, if the neutronic features are similar (EALF, H/U). For scenario E the overall correlations are significantly smaller and variations between experiments decrease. The impact of the determined correlations on bias calculations of application cases will be discussed by the authors in the accompanying paper 'Impact of correlated data in validation procedures'. (authors)

42 ENGINEERING↗
NASA NTRS1999

Detection in fixed and random noise in foveal and parafoveal vision explained by template learning

Foveal and parafoveal contrast detection thresholds for Gabor and checkerboard targets were measured in white noise by means of a two-interval forced-choice paradigm. Two white-noise conditions were used: fixed and twin. In the fixed noise condition a single noise sample was presented in both intervals of all the trials. In the twin noise condition the same noise sample was used in the two intervals of a trial, but a new sample was generated for each trial. Fixed noise conditions usually resulted in lower thresholds than twin noise. Template learning models are presented that attribute this advantage of fixed over twin noise either to fixed memory templates' reducing uncertainty by incorporation of the noise or to the introduction, by the learning process itself, of more variability in the twin noise condition. Quantitative predictions of the template learning process show that it contributes to the accelerating nonlinear increase in performance with signal amplitude at low signal-to-noise ratios.

NASA Center ARC↗
DOE OSTI2017

Giant Metrewave Radio Telescope Observations of Head–Tail Radio Galaxies

We present results from a study of seven large known head–tail radio galaxies based on observations using the Giant Metrewave Radio Telescope at 240 and 610 MHz. These observations are used to study the radio morphologies and distribution of the spectral indices across the sources. The overall morphology of the radio tails of these sources is suggestive of random motions of the optical host around the cluster potential. The presence of multiple bends and wiggles in several head–tail sources is possibly due to the precessing radio jets. We find steepening of the spectral index along the radio tails. The prevailing equipartition magnetic field also decreases along the radio tails of these sources. These steepening trends are attributed to the synchrotron aging of plasma toward the ends of the tails. The dynamical ages of these sample sources have been estimated to be ∼10{sup 8} yr, which is a factor of six more than the age estimates from the radiative losses due to synchrotron cooling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Statistical Analysis of Supernova Remnants in the Large Magellanic Cloud

We construct the most complete sample of supernova remnants (SNRs) in any galaxy—the Large Magellanic Cloud (LMC) SNR sample. We study their various properties such as spectral index (α), size, and surface brightness. We suggest an association between the spatial distribution and environment density of LMC SNRs, and their tendency to be located around supergiant shells. We find evidence that the 16 known type Ia LMC SNRs are expanding in a lower density environment compared to the Core-Collapse (CC) type. The mean diameter of our entire population (74) is 41 pc, which is comparable to nearby galaxies. We did not find any correlation between the type of SN explosion, ovality, or age. The N(<D) relationship with slope a = 0.96 implies that the randomized diameters are readily mimicking such an exponent. The rate of SNe occurring in the LMC is estimated to be ∼1 per 200 yr. The mean α of the entire LMC SNR population is −0.52, which is typical of most SNRs. However, our estimates show a clear flattening of the synchrotron α as the remnants age. As predicted, the CC SNRs in our sample are significantly brighter radio emitters than type Ia remnants. We also estimate the Σ--D relation for the LMC to have a slope ∼3.8, which is comparable with other nearby galaxies. We also find the residency time of electrons in the galaxy (4.0–14.3 Myr), implying that SNRs should be the dominant mechanism for the production and acceleration of CRs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

N-3 polyunsaturated fatty acids ameliorate hepatic steatosis via the PPAR-α/CPT-1α pathway in a mouse model of parenteral nutrition

Parenteral nutrition (PN) is one of the basic therapies for patients with intestinal failure; however, hepatic steatosis associated with PN limits the long-term use of PN. N-3 polyunsaturated fatty acids (PUFAs) have been used to improve clinical outcomes of patients receiving PN; however, the mechanisms by which n-3 PUFAs ameliorate hepatic steatosis remain unclear. In the present study, C57BL/6J mice were randomly assigned to three treatment groups, namely, enteral nutrition (EN), n-3 PUFAs, and n-6 PUFAs. Additionally, MK 886 was used to inhibit PPAR-α. After 7 days of intervention, mice were sacrificed, and liver tissue and serum samples were collected. Results from liver weight and liver triglyceride measurements and Oil Red O staining showed that n-3 PUFAs significantly reduced the liver triglyceride levels. In addition, treatment with n-3 PUFAs resulted in a greater decrease in serum triglyceride and low-density lipoprotein cholesterol levels compared to n-6 PUFAs. The key enzymes involved in FA oxidation, namely, PPAR-α and CPT-1α, were significantly restored at both the mRNA and protein levels in the n-3 PUFAs group. However, the benefits of n-3 PUFAs in improving serum and liver TG levels were abolished when the PPAR-α/CPT-1α pathway was blocked by MK 886. The results of this study indicated that n-3 PUFAs ameliorated the PN-associated hepatic steatosis by activating the PPAR-α/CPT-1α pathway. The present study provided a reliable scientific basis supporting the potential benecial effects of n-3 PUFAs for improving hepatic steatosis in patients receiving long-term parenteral nutrition.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Learning local, quenched disorder in plasticity and other crackling noise phenomena

Abstract When far from equilibrium, many-body systems display behavior that strongly depends on the initial conditions. A characteristic such example is the phenomenon of plasticity of crystalline and amorphous materials that strongly depends on the material history. In plasticity modeling, the history is captured by a quenched, local and disordered flow stress distribution. While it is this disorder that causes avalanches that are commonly observed during nanoscale plastic deformation, the functional form and scaling properties have remained elusive. In this paper, a generic formalism is developed for deriving local disorder distributions from field-response (e.g., stress/strain) timeseries in models of crackling noise. We demonstrate the efficiency of the method in the hysteretic random-field Ising model and also, models of elastic interface depinning that have been used to model crystalline and amorphous plasticity. We show that the capacity to resolve the quenched disorder distribution improves with the temporal resolution and number of samples.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Stabilization of the 81-channel coherent beam combination using machine learning

We develop a rapidly converging algorithm for stabilizing a large channel-count diffractive optical coherent beam combination. An 81-beam combiner is controlled by a novel, machine-learning based, iterative method to correct the optical phases, operating on an experimentally calibrated numerical model. A neural-network is trained to detect phase errors based on interference pattern recognition of uncombined beams adjacent to the combined one. Due to the non-uniqueness of solutions in the full space of possible phases, the network is trained within a limited phase perturbation/error range. This also reduces the number of samples needed for training. Simulations have proven that the network can converge in one step for small phase perturbations. When the trained neural-network is applied to a realistic case of 360 degree full range, an iterative scheme exploits random walking at the beginning, with the accuracy of prediction on phase feedback direction, to allow the neural-network to step into the training range for fast convergence. This neural-network-based iterative method of phase detection works tens of times faster than the commonly used stochastic parallel gradient descent approach (SPGD) using a single-detector and random dither when both are tested with random phase perturbations.

Wang, Dan↗