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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads

A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

On the toroidal plasma rotations induced by lower hybrid waves

A theoretical model is developed to explain the plasma rotations induced by lower hybrid waves in Alcator C-Mod. In this model, torodial rotations are driven by the Lorentz force on the bulk-electron flow across flux surfaces, which is a response of the plasma to the resonant-electron flow across flux surfaces induced by the lower hybrid waves. The flow across flux surfaces of the resonant electrons and the bulk electrons are coupled through the radial electric field initiated by the resonant electrons, and the friction between ions and electrons transfers the toroidal momentum to ions from electrons. An improved quasilinear theory with gyrophase dependent distribution function is developed to calculate the perpendicular resonant-electron flow. Toroidal rotations are determined using a set of fluid equations for bulk electrons and ions, which are solved numerically by a finite-difference method. Numerical results agree well with the experimental observations in terms of flow profile and amplitude. The model explains the strong correlation between torodial flow and internal inductance observed experimentally, and predicts both counter-current and co-current flows, depending on the perpendicular wave vectors of the lower hybrid waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Topological monopole's gauge field‐induced anomalous Hall effect in artificial honeycomb lattice

Abstract Vortex magnetic structure in artificial honeycomb lattice provides a unique platform to explore emergent properties due to the additional Berry phase curvature imparted by chiral magnetization to circulating electrons via direct interaction. We argue that while the perpendicularly aligned magnetic component leads to the quantized flux of monopole at the center of the Berry sphere, the in‐plane vortex circulation of magnetization gives rise to unexpected nontrivial topological Berry phase due to the gauge field transformation. The unprecedented effect signifies the importance of vector potential in multiply connected geometrical systems. Experimental confirmations to proposed hypotheses are obtained from Hall resistance measurements on permalloy honeycomb lattice. Investigation of the topological gauge transformation due to the in‐plane chirality reveals anomalous quasi‐oscillatory behavior in Hall resistance as a function of perpendicular field. The oscillatory nature of is owed to the fluctuation in equilibrium current as a function of Fermi wave‐vector , envisaged under the proposed new formulation in this article. Our synergistic approach suggests that artificially tunable nanostructured material provides new vista to the exploration of topological phenomena of strong fundamental importance. Key Points Demonstration of gauge field flux due to vortex magnetism. Anomalous Hall effect in magnetic honeycomb lattice. Topological monopole‐induced magnetic flux.

Guo, Jiasen↗
DOE OSTI2016

Spin-Josephson effects in exchange coupled antiferromagnetic insulators

The spin superfluid analogy can be extended to include Josephson-like oscillations of the spin current. In a system of two antiferromagnetic insulators (AFMIs) separated by a thin metallic spacer, a threshold spin chemical potential established perpendicular to the direction of the N&#233el vector field drives terahertz oscillations of the spin current. This spin current also has a nonlinear, time-averaged component which provides a “smoking gun” signature of spin superfluidity. The time-averaged spin current can be detected via the inverse spin Hall effect in a metallic spacer with large spin-orbit coupling. The physics illustrated here with AFMIs also applies to easy-plane ferromagnetic insulators. We suggest these findings may provide a new approach for experimental verification of spin superfluidity and realization of a terahertz spin oscillator.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems

Accurate and quick identification of high-impedance faults (HIFs) is critical for the reliable operation of distribution systems. Unlike other faults in power grids, HIFs are very difficult to detect by conventional overcurrent relays due to the low fault current. Although HIFs can be affected by various factors, the voltage-current characteristics can substantially imply how the system responds to the disturbance and thus provides opportunities to effectively localize HIFs. In this work, we propose a data-driven approach for the identification of HIF events. To tackle the nonlinearity of the voltage-current trajectory, first, we formulate optimization problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations. Numerical studies on the IEEE 123-node test feeder demonstrate the validity and accuracy of the proposed approach for real-time HIF identification.

explainable artificial intelligence↗
DOE OSTI2024

A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems: Preprint

Accurate and quick identification of high-impedance faults (HIFs) is critical for the reliable operation of distribution systems. Unlike other faults in power grids, HIFs are very difficult to detect by conventional overcurrent relays due to the low fault current. Although HIFs can be affected by various factors, the voltage-current characteristics can substantially imply how the system responds to the disturbance and thus provides opportunities to effectively localize HIFs. In this work, we propose a data-driven approach for the identification of HIF events. To tackle the nonlinearity of the voltage-current trajectory, first, we formulate optimization problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations. Numerical studies on the IEEE 123-node test feeder demonstrate the validity and accuracy of the proposed approach for real-time HIF identification.

explainable artificial intelligence↗
DOE OSTI2015

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of already annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

COMBINING PARTICLE ACCELERATION AND CORONAL HEATING VIA DATA-CONSTRAINED CALCULATIONS OF NANOFLARES IN CORONAL LOOPS

We model nanoflare heating of extrapolated active-region coronal loops via the acceleration of electrons and protons in Harris-type current sheets. The kinetic energy of the accelerated particles is estimated using semi-analytical and test-particle-tracing approaches. Vector magnetograms and photospheric Doppler velocity maps of NOAA active region 09114, recorded by the Imaging Vector Magnetograph, were used for this analysis. A current-free field extrapolation of the active-region corona was first constructed. The corresponding Poynting fluxes at the footpoints of 5000 extrapolated coronal loops were then calculated. Assuming that reconnecting current sheets develop along these loops, we utilized previous results to estimate the kinetic energy gain of the accelerated particles. We related this energy to nanoflare heating and macroscopic loop characteristics. Kinetic energies of 0.1-8 keV (for electrons) and 0.3-470 keV (for protons) were found to cause heating rates ranging from 10{sup -6} to 1 erg s{sup -1} cm{sup -3}. Hydrodynamic simulations show that such heating rates can sustain plasma in coronal conditions inside the loops and generate plasma thermal distributions that are consistent with active-region observations. We concluded the analysis by computing the form of X-ray spectra generated by the accelerated electrons using the thick-target approach. These spectra were found to be in agreement with observed X-ray spectra, thus supporting the plausibility of our nanoflare-heating scenario.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

System and method for electric load identification and classification employing support vector machine

A method identifies electric load types of a plurality of different electric loads. The method includes providing a support vector machine load feature database of a plurality of different electric load types; sensing a voltage signal and a current signal for each of the different electric loads; determining a load feature vector including at least six steady-state features with a processor from the sensed voltage signal and the sensed current signal; and identifying one of the different electric load types by relating the load feature vector including the at least six steady-state features to the support vector machine load feature database.

Lu, Bin↗
DOE OSTI2018

A novel FPCL model producing directional contraction through induction of fibroblast alignment by biphasic pulse direct current electric field

Although parallel alignment of fibroblasts to the tension lines of scar has been evidenced in vivo, how scar contracture generates directional contraction remains largely unclear due to the lack of effective in vitro model. Fibroblast populated collagen lattice (FPCL), a widely used in vitro model, fails to mimic scar contracture since it produces concentric contraction with the random orientation of fibroblast. We hypothesized that a novel FPCL model with fibroblast alignment might produce directional contraction and then simulate scar contracture better. Here, we showed that although direct current electric fields (DCEFs) enabled fibroblasts aligned perpendicularly to the field vector, it also promoted electrotactic migration of fibroblast in FPCL. By contrast, biphasic pulse direct current electric fields (BPDCEFs), featured by reversal of the EF direction periodically, abolished the electrotactic migration, but induced fibroblast alignment in a pulse frequency dependent manner. Specifically, BPDCEF at a pulse frequency of 0.0002 Hz induced fibroblast alignment comparable to that induced by DCEF under the same field strength (300 mV/mm), leading to an enhanced contraction of FPCL along the direction of cell alignment. FPCL pretreated by BPDCEF showed an elliptical contraction whereas it was concentric in control FPCL. Further study revealed that F-actin redistributions acted as a key mechanism for the induction of fibroblasts alignment by BPDCEF. Cytochalasin D, an inhibitor of actin dynamics, abolished F-actins redistribution, and significantly suppressed the fibroblasts alignment and the directional contraction of FPCL. Importantly, BPDCEF significantly increased RhoA activity in fibroblasts, while this response was attenuated by C3 transferase pre-treatment, a potent inhibitor of RhoA, caused F-actin depolymerization and actin filament bundle randomly distributed. Taken together, our study suggests a crucial role for fibroblast orientation in scar contracture, and provides a novel FPCL model that may be feasible and effective for investigating scar contracture in vitro.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Excitation of helicons by current antennas

Depending on the angle θ between the wave vector and the magnetic field, helicons are conventionally divided into two branches: proper helicons (H mode), propagating at small θ, and Trivelpiece–Gould waves (TG mode), propagating at large θ. The latter are close to potential waves and have a significant electric component along the external magnetic field. It is believed that it is these waves that provide electron heating in helicon discharges. There is also commonly believed that current antennas, widely used to ignite helicon discharges, excite essentially nonpotential Н modes, which then transform into TG modes due to plasma inhomogeneity. In this work, it is demonstrated that electromagnetic energy can also be efficiently introduced in plasma by means of TG modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Magnetization stability analysis of the Stoner-Wohlfarth model under a spin-polarized current with a tilted polarization

The stationary-state solutions of magnetization dynamics under a spin-polarized current that was polarized in an arbitrary direction were investigated by solving the Landau-Lifshitz-Gilbert-Slonczewski equation for a single-domain magnet. Taking into consideration the uniaxial magnetic anisotropy, the equilibrium directions of the magnetization vectors were analytically obtained by solving an algebraic cubic equation. It was found that one to three pairs of magnetization equilibrium states existed, depending on the current intensity and the direction of the spin polarization. By numerically analyzing the stabilities of these equilibrium states, the threshold switching current for the reversing the magnetic vector was obtained under different current polarization configurations, which may be useful for use in future spintronics devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2002

Ground Operations of the ISS GNC Babb-Mueller Atmospheric Density Model

The ISS GNC system was updated recently with a new software release that provides onboard state determination capability. Prior to this release, only the Russian segment maintained and propagated the onboard state, which was periodically updated through Russian ground tracking. The new software gives the US segment the capability for maintaining the onboard state, and includes new GPS and state vector propagation capabilities. Part of this software package is an atmospheric density model based on the Babb-Mueller algorithm. Babb-Mueller efficiently mimics a full analytical density model, such as the Jacchia model. While lacchia is very robust and is used in the Mission Control Center, it is too computationally intensive for use onboard. Thus, Babb-Mueller was chosen as an alternative. The onboard model depends on a set of calibration coefficients that produce a curve fit to the lacchia model. The ISS GNC system only maintains one set of coefficients onboard, so a new set must be uplinked by controllers when the atmospheric conditions change. The onboard density model provides a real-time density value, which is used to calculate the drag experienced by the ISS. This drag value is then incorporated into the onboard propagation of the state vector. The propagation of the state vector, and therefore operation of the BabbMueller algorithm, will be most critical when GPS updates and secondary state vector sources fail. When GPS is active, the onboard state vector will be updated every ten seconds, so the propagation error is irrelevant. When GPS is inactive, the state vector must be updated at least every 24 hours, based on current protocol. Therefore, the Babb-Mueller coefficients must be accurate enough to fulfill the state vector accuracy requirements for at least one day. A ground operations concept was needed in order to manage both the on board Babb-Mueller density model and the onboard state quality. The Babb-Mueller coefficients can be determined operationally in two ways. The first method is to calibrate the coefficients in real-time, where a set of custom coefficients is generated for the real-time atmospheric conditions. The second approach is to generate pre-canned sets of coefficients that encompass the expected atmospheric conditions over the lifetime of the vehicle. These predetermined sets are known as occurrences. Even though a particular occurrence will not match the true atmospheric conditions, the error will be constrained by limiting the breadth of each occurrence. Both methods were investigated and the advantages and disadvantages of each were considered. The choice between these implementations was a trade-off between the additional accuracy of the real-time calibration and the simpler development for the approach using occurrences. The operations concept for the frequency of updates was also explored, and depends on the deviation in solar flux that still achieves the necessary accuracy of the coefficients. This was determined based on historical solar flux trends. This analysis resulted in an accurate and reliable implementation of the Babb-Mueller coefficients and how flight controllers use them during realtime operations.

Brogan, Jonathan↗
NASA NTRS1988

Statistical analysis of SSME system data

A statistical methodology to enhance the Space Shuttle Main Engine (SSME) performance prediction accuracy is proposed. This methodology was to be used in conjunction with existing SSME performance prediction computer codes to improve parameter prediction accuracy and to quantify that accuracy. However, after a review of related literature, researchers concluded that the proposed problem required a coverage of areas such as linear and nonlinear system theory, measurement theory, statistics, and stochastic estimation. Since state space theory is the foundation for a more complete study of each of the before mentioned areas, these researchers chose to refocus emphasis to cover the more specialized topic of state vector estimation procedures. State vector estimation was also selected because of current and future concerns by NASA for SSME performance evaluation; i.e., there is a current interest in an improved evaluation procedure for actual SSME post flight performance as well as for post static test performance of a single SSME. A current investigation of analytical methods may be used to improve test stand failure detection. This paper considers the issue of post flight/test state variable reconstruction through the application of observations made on the output of the Space Shuttle propulsion system. Rogers used the Kalman filtering procedure to reconstruct the state variables of the Space Shuttle propulsion system. An objective of this paper is to give the general setup of the Kalman filter and its connection to linear regression. A second objective is to examine the reconstruction methodology for application to the reconstruction of the state vector of a single Space Shuttle Main Engine (SSME) by using static test firing data.

Temple, Enoch C.↗
DOE OSTI2017

Precision probes of QCD at high energies

New physics, that is too heavy to be produced directly, can leave measurable imprints on the tails of kinematic distributions at the LHC.We use energetic QCD processes to perform novel measurements of the Standard Model (SM) Effective Field Theory. We show that the dijet invariant mass spectrum, and the inclusive jet transverse momentum spectrum, are sensitive to a dimension 6 operator that modifies the gluon propagator at high energies. The dominant effect is constructive or destructive interference with SM jet production. Here, we compare differential next-to-leading order predictions from POWHEG to public 7TeV jet data, including scale, PDF, and experimental uncertainties and their respective correlations. Furthermore, we constrain a New Physics (NP) scale of 3.5TeV with current data. We project the reach of future 13 and 100TeV measurements, which we estimate to be sensitive to NP scales of 8 and 60TeV, respectively. As an application, we apply our bounds to constrain heavy vector octet colorons that couple to the QCD current. We conclude that effective operators will surpass bump hunts, in terms of coloron mass reach, even for sequential couplings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1985

Ram-wake effects on plasma current collection of the PIX 2 Langmuir probe

The Plasma Interaction Experiment 2 (PIX 2) Langmuir probe readings of the same polar magnetospheric regions taken on consecutive orbits showed occasional apparent densities as much as 10 times lower than the average, although each pass clearly showed density structures related to the day/night boundary. At other points in the orbit, Langmuir probe currents varied by as much as a factor of 20 on a time scale of minutes. The hypothesis is advanced that these apparent inconsistencies in Langmuir probe current are the results of the probe's orientation relative to the body of the spacecraft and the velocity vector. Theoretical studies predict a possible depletion in collected electron current by a factor of 100 in the wake. Experimental results from other spacecraft indicate that a wake electron depletion by a factor of 10 or so is realistic. This amount of depletion is consistent with the PIX 2 data if the spacecraft was rotating. Both the Sun sensor and temperature sensor data on PIX 2 show a complex variation consistent with rotation of the Langmuir probe into and out of the spacecraft wake on a time scale of minutes. Furthermore, Langmuir probe data taken when the probe was not in the spacecraft wake are consistent from orbit to orbit. This supports the interpretation that ram/wake effects may be the source of apparent discrepancies at other orientations.

Ferguson, D. C.↗
DOE OSTI2014

Inflationary buildup of a vector field condensate and its cosmological consequences

Light vector fields during inflation obtain a superhorizon perturbation spectrum when their conformal invariance is appropriately broken. Such perturbations, by means of some suitable mechanism (e.g. the vector curvaton mechanism), can contribute to the curvatue perturbation in the Universe and produce characteristic signals, such as statistical anisotropy, on the microwave sky, most recently surveyed by the Planck satellite mission. The magnitude of such characteristic features crucially depends on the magnitude of the vector condensate generated during inflation. However, in the vast majority of the literature the expectation value of this condensate has so-far been taken as a free parameter, lacking a definite prediction or a physically motivated estimate. In this paper, we study the stochastic evolution of the vector condensate and obtain an estimate for its magnitude. Our study is mainly focused in the supergravity inspired case when the kinetic function and mass of the vector boson is time-varying during inflation, but other cases are also explored such as a parity violating axial theory or a non-minimal coupling between the vector field and gravity. As an example, we apply our findings in the context of the vector curvaton mechanism and contrast our results with current observations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2000

A Prospective Method for Predicting Coronal Mass Ejections from Vector Magnetograms

Two quantitative measures of the global nonpotentiality of predominantly bipolar active regions are explored for their usefulness as indicators of whether an active region is likely to produce coronal mass ejections (CMEs). The two measures, length of strong-field strong-shear main neutral line (L(sub ss)) and global net current (I(sub N)), are obtained directly from vector magnetograms of the regions. From measurements of L(sub ss) and I(sub N) in four active regions for which the global nonpotentiality and CME productivity are assessed independently of L(sub ss) and I(sub N), it appears that L(sub ss) and I(sub N) are each a useful indicator of an active region's likely CME productivity. The results also suggest that L(sub ss) and I(sub N) may be more reliable predictors of the CME productivity of active regions than is the presence or absence of sigmoidal structure in coronal X-ray images of the regions, and that there might be threshold values of L(sub ss) and I(sub N) above which CME production is likely and below which CME production is unlikely. While these results need to be certified by an expansion of this pilot study to more active regions, they show the promise of Lss and I(sub N) as quantitative measures of global nonpotentiality for CME prediction.

Falconer, D. A.↗