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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Dielectric breakdown induced by picosecond laser pulses

The damage thresholds of transparent optical materials were investigated. Single picosecond pulses at 1.06 microns, 0.53 microns and 0.35 microns were obtained from a mode locked Nd-YAG oscillator-amplifier-frequency multiplier system. The pulses were Gaussian in space and time and permitted the determination of breakdown thresholds with a reproducibility of 15%. It was shown that the breakdown thresholds are characteristic of the bulk material, which included nine alkali halides, five different laser host materials, KDP, quartz, sapphire and calcium fluoride. The extension of the damage data to the ultraviolet is significant, because some indication was obtained that two- and three-photon absorption processes begin to play a role in determining the threshold. Throughout the visible region of the spectrum the threshold is still an increasing function of frequency, indicating that avalanche ionization is the dominant factor in determining the breakdown threshold. This was confirmed by a detailed study of the damage morphology with a high resolution microscope just above the threshold. The influence of self focusing is discussed, and evidence for beam distortion below the power threshold for complete self focusing is presented, confirming the theory of Marburger.

Smith, W. L.↗
NASA NTRS1989

DMSK Receiver For Mobile/Satellite Service

Receiver for 2.4-kbit/s differential minimum-shift keying (DMSK) and Gaussian minimum-shift keying(GMSK) suitable for communication between land-mobile stations via geostationary satellites. Operating on phase-shifted signal in 800-MHz band, in presence of fading and Doppler frequency shifts, receiver compact, makes efficient use of frequency spectrum, and wastes little power. Receiver design implemented in very-large-scale-integrated circuits. Basic DMSK receiver design relies on baseband rather than intermediate-frequency processing of in-phase and quadrature signal components because phase errors due to differential delays smaller at baseband.

Davarian, Faramaz↗
NASA NTRS1991

Proton-induced radiation damage in germanium detectors

High-purity germanium (HPGe) detectors will be used in future space missions for gamma-ray measurements and will be subject to interactions with energetic particles. To simulate this process, several large-volume n-type HPGe detectors were incrementally exposed to a particle fluence of up to 10 to the 8th protons/sq cm (proton energy: 1.5 GeV) at different operating temperatures (90 to 120 K) to induce radiation damage. Basic scientific and engineering data on detector performance were collected. During the incremental irradiation, the peak shape produced by the detectors showed a significant change from a Gaussian shape to a broad complex structure. After the irradiation, all detectors were thoroughly characterized by measuring many parameters. To remove the accumulated radiation damage, the detectors were stepwise-annealed at temperatures below 110 C, while kept in their specially designed cryostats. This study shows that n-type HPGe detectors can be used in charged-particle environments as high-energy resolution devices until a certain level of radiation damage is accumulated and that the damage can be removed at moderate annealing temperatures and the detector returned to operating condition.

Brueckner, J.↗
DOE OSTI2014

Stellar encounter driven red-giant star mass loss in globular clusters

Globular cluster (GC) color-magnitude diagrams (CMDs) are reasonably well understood in terms of standard stellar evolution. However, there are still some open issues, such as fully accounting for the horizontal branch (HB) morphology in terms of chemical and dynamical parameters. Mass loss on the red giant branch (RGB) shapes the mass distribution of the HB stars, and the color distribution in turn. The physical mechanisms driving mass loss are still unclear, as direct observations fail to reveal a clear correlation between mass-loss rate and stellar properties. The HB mass distribution is further complicated by helium-enhanced multiple stellar populations due to differences in the evolving mass along the HB. We present a simple analytical mass-loss model based on tidal stripping through Roche-Lobe overflow during stellar encounters. Our model naturally results in a non-Gaussian mass-loss distribution with high skewness and contains only two free parameters. We fit it to the HB mass distribution of four Galactic GCs, as obtained from fitting the CMD with zero age HB models. The best-fit model accurately reproduces the observed mass distribution. If confirmed on a wider sample of GCs, our results would account for the effects of dynamics in RGB mass-loss processes and provide a physically motivated procedure for synthetic CMDs of GCs. Our physical modeling of mass loss may result in the ability to disentangle the effects of dynamics and helium-enhanced multiple populations on the HB morphology and is instrumental in making HB morphology a probe of the dynamical state of GCs, leading to an improved understanding of their evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A Comparison of Machine Learning Methods of Association Tested on Dense Nodal Arrays

The association of phase picks to form events is one of the fundamental components of seismology. Large and dense sensor networks, such as >1000 geophone arrays (and distributed acoustic sensing), offer unique challenges in association due to the vast numbers of observations and high likelihood of errant picks. In addition, the large number of stations can greatly increase the time it takes to perform the association. For this reason, machine learning (ML) methods might provide a more optimal method of association for such networks. In this work, we examine how well ML methods (e.g., Gaussian mixture model association, PhaseLink, and Graph Earthquake Neural Interpretation Engine) can incorporate dense seismic arrays into regional networks and how well they handle the increasing numbers of stations. Here, we test their capabilities on two dense seismic deployments, one within Rock Valley Nevada (52 nodes and a 9-station sparse local network), and the LArge-n Seismic Survey in Oklahoma dense nodal array (>1800 vertical-component geophones). Processing data from these two different styles of dense seismic deployments allows testing of how the ML algorithms can merge array data with a broader regional network, how they deal with poorly picked phases, and how they handle anthropogenic noise. We compare the ML-associated bulletins to those obtained using the Rapid Earthquake Association and Location algorithm, a more traditional method of association. We find that there are very small differences in results between the methods for small networks (<100 stations) with low pick rates. For large networks (>1000), there are enough errant picks that some of the ML methods start to create false events out of noise. We also find that the ML methods vary in computation time significantly but are all faster than the traditional method tested here.

58 GEOSCIENCES↗
NASA NTRS1980

Propagation in a shearing plasma. II - Turbulence and the frequency range of pulsar microstructure

Numerical calculations are presented which explore the propagation of radio waves and pulses through a turbulent shearing plasma. A stochastic model is used to describe the turbulent velocity field, in which random fluctuations are superposed on a mean profile. Both Gaussian wave packets and shot-noise pulses polarized in the plane of shearing acquire quasi-periodic intensity modulations above the rest-frame plasma frequency. The frequency range over which these modulations appear is shown to depend on the spatial correlation length of the turbulent fluctuations and on their standard deviation from the mean velocity. The period of the modulations is variable from one realization of the random process to the next, and the average period is frequency dependent. The results of these calculations lend further support to a model for pulsar microstructure in which periodic micropulses are pure temporal modulations of the emitted radiation due to propagation effects in magnetospheric shearing regions. It is shown that turbulence on a scale of approximately 10 cm can produce these quasi-periodic modulations over a frequency range comparable to that of observed microstructure.

Harding, A. K.↗
DOE OSTI2022

An intensity-based post-processing tool for 3D instance segmentation of organelles in soft X-ray tomograms

Investigating the 3D structures and rearrangements of organelles within a single cell is critical for better characterizing cellular function. Imaging approaches such as soft X-ray tomography have been widely applied to reveal a complex subcellular organization involving multiple inter-organelle interactions. However, 3D segmentation of organelle instances has been challenging despite its importance in organelle characterization. Here we propose an intensity-based post-processing tool to identify and separate organelle instances. Our tool separates sphere-like (insulin vesicle) and columnar-shaped organelle instances (mitochondrion) based on the intensity of raw tomograms, semantic segmentation masks, and organelle morphology. We validate our tool using synthetic tomograms of organelles and experimental tomograms of pancreatic β -cells to separate insulin vesicle and mitochondria instances. As compared to the commonly used connected regions labeling, watershed, and watershed + Gaussian filter methods, our tool results in improved accuracy in identifying organelles in the synthetic tomograms and an improved description of organelle structures in β -cell tomograms. In addition, under different experimental treatment conditions, significant changes in volumes and intensities of both insulin vesicle and mitochondrion are observed in our instance results, revealing their potential roles in maintaining normal β -cell function. Our tool is expected to be applicable for improving the instance segmentation of other images obtained from different cell types using multiple imaging modalities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Design and Analysis of a Wake Steering Controller with Wind Direction Variability

Wind farm control strategies are being developed to mitigate wake losses in wind farms, increasing energy production. Wake steering is a type of wind farm control in which a wind turbine's yaw position is misaligned from the wind direction, causing its wake to deflect away from downstream turbines. Current modeling tools used to optimize and estimate energy gains from wake steering are designed to represent wakes for fixed wind directions. However, wake steering controllers must operate in dynamic wind conditions and a turbine's yaw position cannot perfectly track changing wind directions. Research has been conducted on robust wake steering control optimized for variable wind directions. In this paper, the design and analysis of a wake steering controller with wind direction variability is presented for a two-turbine array using the FLOw Redirection and Induction in Steady State (FLORIS) control-oriented wake model. First, the authors propose a method for modeling the turbulent and low-frequency components of the wind direction, where the slowly varying wind direction serves as the relevant input to the wake model. Next, we explain a procedure for finding optimal yaw offsets for dynamic wind conditions considering both wind direction and yaw position uncertainty. We then performed simulations with the optimal yaw offsets applied using a realistic yaw offset controller in conjunction with a baseline yaw controller, showing good agreement with the predicted energy gain using the probabilistic model. Using the Gaussian wake model in FLORIS as an example, we compared the performance of yaw offset controllers optimized for static and dynamic wind conditions for different turbine spacings and turbulence intensity values. For a spacing of 5 rotor diameters and a turbulence intensity of 10%, robust yaw offsets optimized for variable wind directions yielded an energy gain improvement of 128%. In general, accounting for wind direction variability in the yaw offset optimization process was found to improve energy production more as the separation distance increased, whereas the relative improvement remained roughly the same for the range of turbulence intensity values considered.

17 WIND ENERGY↗
NASA NTRS1996

The barberplaid illusion: plaid motion is biased by elongated apertures

The perceived direction of motion of plaids windowed by elongated spatial Gaussians is biased toward the window's long axis. The bias increases as the relative angle between the plaid motion and the long axis of the window increases, peaks at a relative angle of approximately 45 deg, and then decreases. The bias increases as the window is made narrower (at fixed height) and decreases as the component spatial frequency increases (at fixed aperture size). We examine several models of human motion processing (cross-correlation, motion-energy, intersection-of-constraints, and vector-sum), and show that none of these standard models can predict our data. We conclude that spatial integration of motion signals plays a crucial role in plaid motion perception and that current models must be explicitly expanded to include such spatial interactions.

NASA Center ARC↗
DOE OSTI2024

Probabilistic Analysis of Long-Term Degradation of Microwave Cavity Flow Sensor

We are investigating a microwave resonant cavity transducer for flow sensing in the vessel of a high temperature fluid advanced reactor (AR), such as a molten salt cooled reactor (MSCR) or a sodium fast reactor (SFR). This transducer is a hollow metallic cylindrical cavity, with the flat wall of the cylinder flexible enough to undergo microscopic deflection due to dynamic fluid pressure. Membrane deflection leads to a shift in the resonant frequency, which can be detected with a spectrum analyzer. We have performed a proof-of-concept experiment of flow sensing with the transducer in liquid sodium at 340°C in impinging liquid jet geometry. The transducer remained in liquid sodium for 70 days. After removal, no structural damage was observed, and the expected transducer response was verified in a water test. Because long-term (multi-year) experimental tests of transducer resilience to harsh environment are not practical, we have developed a probabilistic model of creep to estimate transducer resilience to the harsh environment. The probabilistic model considers diffusion creep under the condition of high temperature and low stress, where the stress and temperature are allowed to be random variables with Gaussian distributions. Using the probabilistic model, we estimate inelastic membrane deflections due to creep for several temperature ranges. We conclude that for temperatures less than 650°C, creep has negligible long-term effect on the transducer performance. Since a yellowish residue was observed on the transducer surface after 70 days of immersion in liquid sodium, we have investigated possible evidence of corrosion. Chromium depletion is a typical indicator of the corrosion process in stainless steel. Scraping off a residue from the transducer and performing scanning electron microscopy (SEM) with energy dispersive analysis (EDS) did not find any chromium in the residue. Approximately 60% of the residue consisted of copper, which can be attributed to contamination of sodium due to powder residue from machining of copper and brass components of the transducer.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2015

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Xu, Kuan-Man↗
DOE OSTI2014

Group Additivity Determination for Enthalpies of Formation of Carbenium Ions

Modeling of acid-catalyzed hydrocarbon conversion processes at the mechanistic level requires rate coefficients for a large number of reactions. The computational demand of finding activation energy barriers for each reaction is substantially reduced by employing structure–reactivity correlations such as the Evans–Polanyi relationship that correlates activation energy with the enthalpy of reaction. However, there are many species for which the enthalpies of formation are unknown. Therefore, group additivity methods to specify enthalpies of formation for each species involved in the reaction network are valuable. Quantum mechanical (QM) calculations and isodesmic reactions were used to calculate enthalpies of formation for a number of acyclic and cyclic carbenium ions, including allylic carbenium ions. These values compare favorably with experimental values, establishing Gaussian-4 as an accurate QM method for these calculations. Using these values, Benson-type group additivity values for enthalpies of formation were then derived through multiple linear regression. Enthalpies of formation values calculated from the group additivity scheme capture experimental and QM enthalpies of formation well and enhance the range of species that can be described by the group additivity approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Accelerating Subsurface Transport Simulation on Heterogeneous Clusters

Reactive transport numerical models simulate chemical and microbiological reactions that occur along a flowpath. These models have to compute reactions for a large number of locations. They solve the set of ordinary differential equations (ODEs) that describes the reaction for each location through the Newton-Raphson technique. This technique involves computing a Jacobian matrix and a residual vector for each set of equation, and then solving iteratively the linearized system by performing Gaussian Elimination and LU decomposition until convergence. STOMP, a well known subsurface flow simulation tool, employs matrices with sizes in the order of 100x100 elements and, for numerical accuracy, LU factorization with full pivoting instead of the faster partial pivoting. Modern high performance computing systems are heterogeneous machines whose nodes integrate both CPUs and GPUs, exposing unprecedented amounts of parallelism. To exploit all their computational power, applications must use both the types of processing elements. For the case of subsurface flow simulation, this mainly requires implementing efficient batched LU-based solvers and identifying efficient solutions for enabling load balancing among the different processors of the system. In this paper we discuss two approaches that allows scaling STOMP's performance on heterogeneous clusters. We initially identify the challenges in implementing batched LU-based solvers for small matrices on GPUs, and propose an implementation that fulfills STOMP's requirements. We compare this implementation to other existing solutions. Then, we combine the batched GPU solver with an OpenMP-based CPU solver, and present an adaptive load balancer that dynamically distributes the linear systems to solve between the two components inside a node. We show how these approaches, integrated into the full application, provide speed ups from 6 to 7 times on large problems, executed on up to 16 nodes of a cluster with two AMD Opteron 6272 and a Tesla M2090 per node.

GPU↗
NASA NTRS1985

Review of image processing fundamentals

Image processing through convolution, transform coding, spatial frequency alterations, sampling, and interpolation are considered. It is postulated that convolution in one domain (real or frequency) is equivalent to multiplication in the other (frequency or real), and that the relative amplitudes of the Fourier components must be retained to reproduce any waveshape. It is suggested that all digital systems may be considered equivalent, with a frequency content approximately at the Nyquist limit, and with a Gaussian frequency response. An optimized cubic version of the interpolation continuum image is derived as a set of cubic spines. Pixel replication has been employed to enlarge the visable area of digital samples, however, suitable elimination of the extraneous high frequencies involved in the visable edges, by defocusing, is necessary to allow the underlying object represented by the data values to be seen.

Billingsley, F. C.↗
DOE OSTI2018

Filtration of stationary Gaussian statistical experiments

The filtration of stationary Gaussian statistical experiments is determined by a solution of the equation of optimum filtration, which is characterized by the two-dimensional matrix of covariances. The parameters of a filtered signal are set by empiric covariances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Problem-free time-dependent variational principle for open quantum systems

Methods of quantum nuclear wave-function dynamics have become very efficient in simulating large isolated systems using the time-dependent variational principle (TDVP). However, a straightforward extension of the TDVP to the density matrix framework gives rise to methods that do not conserve the energy in the isolated system limit and the total system population for open systems where only energy exchange with environment is allowed. These problems arise when the system density is in a mixed state and is simulated using an incomplete basis. Thus, the basis set incompleteness, which is inevitable in practical calculations, creates artificial channels for energy and population dissipation. To overcome this unphysical behavior, we have introduced a constrained Lagrangian formulation of TDVP applied to a non-stochastic open system Schrödinger equation [L. Joubert-Doriol, I. G. Ryabinkin, and A. F. Izmaylov, J. Chem. Phys. 141, 234112 (2014)]. While our formulation can be applied to any variational ansatz for the system density matrix, derivation of working equations and numerical assessment is done within the variational multiconfiguration Gaussian approach for a two-dimensional linear vibronic coupling model system interacting with a harmonic bath.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2001

Classification Experiments on Real-World Texture

Many papers have been published concerning the analysis of visual texture and yet, very few application domains use texture for image classification. A possible reason for this low transfer of the technology is the lack of experience and testing in real-world imagery. In this paper, we assess the performance of texture-based classification methods on a number of real-world images relevant to autonomous navigation on cross-country terrain and to autonomous geology. Texture analysis will form part of the closed loop that allows a robotic system to navigate autonomously. We have implemented two different classifiers on features extracted by Gabor filter banks. The first classifier models feature distributions for each texture class using a mixture of Gaussians. Classification is performed using Maximum Likelihood. The second classifier represents local statistics using marginal histograms of the features over a region centered on the pixel to be classified. We measure system performance by comparison to ground truth image labels.

image segmentation↗
NASA NTRS2021

The Asymmetric Inner Disk of the Herbig Ae Star HD 163296 in the Eyes of VLTI/MATISSE: Evidence for a Vortex?

Context.A complex environment exists in the inner few astronomical units of planet-forming disks. High-angular-resolution observa-tions play a key role in our understanding of the disk structure and the dynamical processes at work.Aims.In this study we aim to characterize the mid-infrared brightness distribution of the inner disk of the young intermediate-massstar HD 163296 from early VLTI/MATISSE observations taken in theL- andN-bands. We put special emphasis on the detection ofpotential disk asymmetries.Methods.We use simple geometric models to fit the interferometric visibilities and closure phases. Our models include a smoothedring, a flat disk with an inner cavity, and a 2D Gaussian. The models can account for disk inclination and for azimuthal asymmetriesas well. We also perform numerical hydrodynamical simulations of the inner edge of the disk.Results.Our modeling reveals a significant brightness asymmetry in theL-band disk emission. The brightness maximum of the asym-metry is located at the NW part of the disk image, nearly at the position angle of the semimajor axis. The surface brightness ratio inthe azimuthal variation is3.5±0.2. Comparing our result on the location of the asymmetry with other interferometric measurements,we confirm that the morphology of ther<0.3au disk region is time-variable. We propose that this asymmetric structure, located in ornear the inner rim of the dusty disk, orbits the star. To find the physical origin of the asymmetry, we tested a hypothesis where a vortexis created by Rossby wave instability, and we find that a unique large-scale vortex may be compatible with our data. The half-lightradius of theL-band-emitting region is0.33±0.01au, the inclination is52◦+5◦−7◦, and the position angle is143◦±3◦. Our models predictthat a non-negligible fraction of theL-band disk emission originates inside the dust sublimation radius forμm-sized grains. Refractorygrains or large (&10μm-sized) grains could be the origin of this emission.N-band observations may also support a lack of smallsilicate grains in the innermost disk (r.0.6au), in agreement with our findings fromL-band data.

J Varga↗