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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Simulated Performance of the Orbiting Wide-angle Light Collectors (OWL) Experiment

The Orbiting Wide-angle Light collectors (OWL) experiment is in NASA's mid-term strategic plan and will stereoscopically image, from equatorial orbit, the air fluorescence signal generated by airshowers induced by the ultrahigh energy (E greater than few x 10(exp 19) eV) component of the cosmic radiation. The use of a space-based platform enables an extremely large event acceptance aperture and thus will allow a high statistics measurement of these rare events. Detailed Monte Carlo simulations are required to quantify the physics potential of the mission as well as optimize the instrumental parameters. This paper reports on the results of the GSFC Monte Carlo simulation for two different, OWL instrument baseline designs. These results indicate that, assuming a continuation of the cosmic ray spectrum (theta approximately E(exp -2.75), OWL could have an event rate of 4000 events/year with E greater than or equal to 10(exp 20) eV. Preliminary results, based upon these Monte Carlo simulations, indicate that events can be accurately reconstructed in the detector focal plane arrays for the OWL instrument baseline designs under consideration.

Krizmanic, J. F.↗
NASA NTRS2010

Statistical Properties of SGR J1550-5418 Bursts

Magnetars are slowly rotating neutron stars with extreme magnetic fields, over 10(exp 15) Gauss. Only few have been discovered in the last 30 years. These sources are dormant most of their lifetimes and become randomly active emitting multiple soft gamma-ray bursts. We present here our results on the temporal analysis of ~300 bursts from Soft Gamma Repeater SGR J1550-5418 recorded with the Gamma-ray Burst Monitor (GBM) onboard the Fermi Observatory during its activation on January 22-29, 2009. We employed an un-triggered burst search in the energy range 8-100keV to collect all events from the source, besides the ones that triggered GBM. For the entire sample of bursts we determined their durations, rise and decay times. We study here the statistical properties of these characteristics and discuss how these may help us better understand the physical characteristics of the magnetar model.

Gorgone, Nicholas M.↗
DOE OSTI2015

Recent D0 Measurements of Forward-Backward Asymmetries for $p\overline{p}\rightarrow B^\pm, \Lambda_b^0,$ and $\Lambda_s^0$ Production

The Forward-Backward Asymmetries in the production of B ± , Λ b 0 , and Λ s 0 particles for rapidities | y | < 2 are measured by D0 for pp-bar collisions at √s = 1.96 TeV at the Fermilab Tevatron. A FB (B ± ) and A FB (Λ b 0 ) are consistent with zero, while A FB (Λ s 0 ) exhibits a statistically significant rise with increasing | y |.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Shear dynamo, turbulence, and the magnetorotational instability

The formation, evolution, and detailed structure of accretion disks remain poorly understood, with wide implications across a variety of astrophysical disciplines. While the most pressing question – what causes the high angular momentum fluxes that are necessary to explain observations? – is nicely answered by the idea that the disk is turbulent, a more complete grasp of the fundamental processes is necessary to capture the wide variety of behaviors observed in the night sky. This thesis studies the turbulence in ionized accretion disks from a theoretical standpoint, in particular focusing on the generation of magnetic fields in these processes, known as dynamo. Such fields are expected to be enormously important, both by enabling the magnetorotational instability (which evolves into virulent turbulence), and through large-scale structure formation, which may transport angular momentum in different ways and be fundamental for the formation of jets. The central result of this thesis is the suggestion of a new large-scale dynamo mechanism in shear flows – the “magnetic shear-current effect” – which relies on a positive feedback from smallscale magnetic fields. As well as being a very promising candidate for driving field generation in the central regions of accretion disks, this effect is interesting because small-scale magnetic fields have historically been considered to have a negative effect on the large-scale dynamo, damping growth and leading to dire predictions for final saturation amplitudes. Given that small-scale fields are ubiquitous in plasma turbulence above moderate Reynolds numbers, the finding that they could instead have a positive effect in some situations is interesting from a theoretical and practical standpoint. The effect is studied using direct numerical simulation, analytic techniques, and novel statistical simulation methods. In addition to the dynamo, much attention is given to the linear physics of disks and its relevance to turbulence. This is studied using nonmodal stability theory, which both provides a highly intuitive connection between global domains and the commonly studied shearing box, and suggests that transient linear growth can often be more important than spectral instability. These realizations motivate the use of the quasi-linear models that are applied extensively throughout the turbulence and dynamo studies later in the thesis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

The hybrid mesons quest: the MesonEx experiment at Jefferson Laboratory

The meson spectroscopy plays nowadays a central role in the investigation of hadron structure thanks to the possible existence of exotic hybrid mesons, quark-antiquark-gluon bound states. Their explicit gluonic degrees of freedom which should clearly emerge from a Partial Wave Analysis (PWA) of the corresponding Dalitz plot of the exotic particle decay, may result in final JPC configurations not allowed in the constituent quark model. Besides this clear signature, hybrid mesons are also expected to have a large particle multiplicity decays, requiring for their search an experimental apparatus with high performances in terms of rate capability, resolution and almost a full acceptance to apply PWA methods. New-generation experiments are planned at Thomas Jefferson National Laboratory (VA, USA) for which an unprecedented statistics of large multiplicity decay events with fully reconstructed kinematics will be available. In particular for the MesonEx (CLAS12) experiment in Hall B, a wide scientific program that will start in 2016 has been deployed to study the meson spectrum at energies up to 11 GeV. A key role in such program is played by the Forward Tagger apparatus of the experiment, which will allow to extend the study of meson electro-production to very low Q2 values, in a quasi-real photo production kinematical region, where the production of hybrid mesons is expected to be favorite. Currently a new analysis framework for the search of the hybrid mesons is being set up by the HASPECT network, an international structure which gather people involved into theoretical and experimental hadronic physics all over the world. The goals of the network is to develop new analysis models and statistical techniques to unfold the signal and background distributions in high-statistics datasets. In this work are briefly presented the first preliminary results from the application of a statistical technique, namely the sPlot, to the data already acquired by the CLAS experiment for the decay f 1 (1285) --> (eta)pi+pi-.

Rizzo, Alessandro↗
DOE OSTI2020

Physics-informed semantic inpainting: Application to geostatistical modeling

A fundamental problem in geostatistical modeling is to infer the heterogeneous geological field based on limited measurements and some prior spatial statistics. Semantic inpainting, a technique for image processing using deep generative models, has been recently applied for this purpose, demonstrating its effectiveness in dealing with complex spatial patterns. However, the original semantic inpainting framework incorporates only information from direct measurements, while in geostatistics indirect measurements are often plentiful. In this work, to overcome this limitation, we propose a physics-informed semantic inpainting framework, employing the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) and jointly incorporating the direct and indirect measurements by exploiting the underlying physical laws. Our simulation results for a high-dimensional problem with 512 dimensions show that in the new method, the physical conservation laws are satisfied and contribute in enhancing the inpainting performance compared to using only the direct measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

String Theory Bounds on the Cosmological Constant, the Higgs Mass, and the Quark and Lepton Masses

In this paper, we elaborate on the new understanding of the cosmological constant and the gauge hierarchy problems in the context of string theory in its metastring formulation, based on the concepts of modular spacetime and Born geometry. The interplay of phase space (and Born geometry), the Bekenstein bound, the mixing between ultraviolet (UV) and infrared (IR) physics and modular invariance in string theory is emphasized. This new viewpoint is fundamentally rooted in quantum contextuality and not in statistical observer bias (anthropic principle). We also discuss the extension of this point of view to the problem of masses of quarks and leptons and their respective mixing matrices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Illuminating the Role of Women at the Department of Energy National Laboratories

The early contributions of female researchers such as Marie Curie and Lisa Meitner to physics—and ultimately to the Manhattan Project—have been widely recognized and documented. In addition, numerous historical accounts have revealed the significant impacts of other female scientists, engineers, and technologists during the Manhattan Project. Despite the strong role of women in the Manhattan Project, the momentum has not continued into the present day, as reflected by the current demographics of the Department of Energy (DOE) National Laboratories. Although the overall U.S. workforce is about 50% female, the workforce at the DOE National Labs is only about 30% female. The statistics for technical management and research staff at the DOE National Labs are even more dire; women make up only about 18% of these ranks in contrast to the percentages of women in computer science (25%) and physical science (39%) in the U.S. workforce. These current statistics are not the desired state for the DOE National Labs and contrast sharply with the long history of accomplishments by women at the Labs. We believe the DOE National Labs should lead the charge on diversity and inclusion (D&I) and serve as a model enterprise for bringing women into our scientific and technical workforce.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2019

Nucleon and $\Omega$ Baryon Masses with All-HISQ Fermions at the Physical Point

We present the results of the nucleon and $\Omega$ baryon masses using staggered action for both valence and sea quarks. Three ensembles with the physical pion mass at approximate lattice spacings of $0.15$, $0.12$, and $0.088$fm are employed to extrapolate the masses to continuum and we obtain $M_N = 964(16)$ MeV and $M_\Omega = 1678(9)$. Both statistical and systematic uncertainties are included in the nucleon mass, whereas only the statistical uncertainty is accounted for in the $\Omega$ baryon mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well as histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Correlates of Sensitive Technologies

By “Quantitative Empirical Analysis” (QEA) is intended the use of statistical methods to infer, from data that often tend to be of a historical nature, the characteristics of states that correlate with some designated dependent variable (e.g. proliferation of nuclear weapons). QEA is a well-established approach in the social sciences, but is not notably well-known among physical scientists, who tend to think of the social sciences as inherently qualitative. This article attempts to provide a snapshot of research, most of which has evolved over the past decade, involving the application of QEA to issues in which the dependent variable of interest is intended as some measure of nuclear proliferation. Standard practices in QEA are described, especially as they relate to data collection. The QEA approach is compared and contrasted to other quantitative approaches to studying proliferation-related issues, including a “figure of merit” approach that has largely been developed within the DOE complex, and two distinct methodologies termed in a recent US National Academy of Sciences study as “case by case” and “predefined framework.” Sample results from QEA applied to proliferation are indicated, as are doubts about such quantitative approaches. A simplistic decision-theoretic model of the optimal time for the international community to intervene in a possible proliferation scenario is used to illustrate the possibility of synergies between different approaches

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Unitary Quantization and Para-Fermi Statistics of Order 2

We consider the relationship between the unitary quantization scheme and the para-Fermi statistics of order 2. We propose an appropriate generalization of Green’s ansatz, which has made it possible to transform bilinear and trilinear commutation relations for the creation and annihilation operators for two different para-Fermi fields φ{sub a} and φ{sub b} into identities. We also propose a method for incorporating para-Grassmann numbers ξ{sub k} into the general unitary quantization scheme. For the parastatistics of order 2, a new fact has been revealed: the trilinear relations containing both para-Grassmann variables ξ{sub k} and field operators ak and bm are transformed under a certain reversible mapping into unitary equivalent relations in which commutators are replaced by anticommutators, and vice versa. It is shown that this leads to the existence of two alternative definitions of the coherent state for para-Fermi oscillators. The Klein transformation for Green’s components of operators a{sub k} and b{sub m} is constructed in explicit form, which enabled us to reduce the initial commutation rules for the components to the normal commutation relations for ordinary Fermi fields. We have analyzed a nontrivial relationship between the trilinear commutation relations of the unitary quantization scheme and the so-called Lie supertriple system. The possibility of incorporating the Duffin–Kemmer–Petiau theory into the unitary quantization scheme is discussed briefly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

The importance of atmospheric turbulence and stability in machine-learning models of wind farm power production

Machine learning is frequently applied in the wind energy industry to build statistical models of wind farm power production using atmospheric data as input. In the field of wind power forecasting, in particular, there has been substantial research into finding the best-performing learning algorithms that improve model predictions. Overlooked in the literature, however, is the influence of atmospheric turbulence and stability measurements in improving model predictions. It has been well-established through observations and physical models that these effects can have considerable influence on wind farm power production; yet consideration of these effects in statistical models is almost entirely absent from the literature. In this work, we examine the impact of atmospheric turbulence and stability inputs on statistical model predictions of wind farm power output. Hourly observations from a wind farm in the Pacific Northwest United States located in very complex terrain are used. Five common learning algorithms and nine atmospheric variables are considered, five of which represent some measure of turbulence or stability. Here, we find a considerable improvement in hourly power predictions when some measure of turbulence or stability is included in the model. In particular, turbulent kinetic energy was found to be the most important variable apart from wind speed and more important than wind direction, pressure, and temperature. By contrast, the choice of learning algorithm is shown to be relatively less important in improving predictions. Based on this work, we recommend that turbulence and stability variables become standard inputs into statistical models of wind farm power production.

17 WIND ENERGY↗
NASA NTRS2020

Non-linear Least Square Fitting Technique for the Determination of Field Line Resonance Frequency in Ground Magnetometer Data: Application to Remote Sensing of Plasmaspheric Mass Density

The accurate determination of the Field Line Resonance (FLR) frequency of a resonating geomagnetic field line is necessary to remotely monitor the plasmaspheric mass density during geomagnetic storms and quiet times alike. Under certain assumptions the plasmaspheric mass density at the equator is inversely proportional to the square of the FLR frequency. The most common techniques to determine the FLR frequency from ground magnetometer measurements are the amplitude ratio and phase difference techniques, both based on geomagnetic field observations at two latitudinally separated ground stations along the same magnetic meridian. Previously developed automated techniques have used statistical methods to pinpoint the FLR frequency using the amplitude ratio and phase difference calculations. We now introduce a physics-based automated technique, using non-linear least square fitting of the ground magnetometer data to the analytical resonant wave equations, that reproduces the wave characteristics on the ground, and from those determine the FLR frequency. One of the advantages of the new technique is the estimation of physics-based errors of the FLR frequency, and as a result of the equatorial plasmaspheric mass density. We present analytical results of the new technique, and test it using data from the Inner-Magnetospheric Array for Geospace Science (iMAGS) ground magnetometer chain along the coast of Chile and the east coast of the United States. We compare the results with the results of previously published statistical automated techniques.

A. Boudouridis↗
DOE OSTI2017

Spectrum of Virtual Photons in the Electroproduction of Negatively Charged Pions on Deuterons

Numerical and analytical calculations of the virtual photon spectrum have been performed for the electroproduction of negatively charged pions on a deuteron. The numerical calculations of the virtual photon spectrum were performed without recourse to any approximations while a number of approximations were admitted in the derivation of the analytical expression. A comparison of the results of an exact numerical calculation of the virtual photon spectrum with the results of a calculation obtained using an approximate analytical expression for the virtual photon spectrum has been performed for the first time. It is shown that the discrepancy between the virtual photon spectra obtained with the help of numerical and analytical methods can reach 10% in the kinematic region of photoproduction of pions with intermediate energies. It follows from the obtained results that in the statistical modeling of the yields of the reaction of photoproduction of negatively charged pions on a deuteron it is necessary to use the exact virtual photon spectrum obtained with the help of numerical methods whereas in the statistical modeling of the asymmetry of reactions of photoproduction of negatively charged pions on a deuteron it is sufficient to use the approximate analytical expression for the virtual photon spectrum.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

An efficient direct solver for rarefied gas flows with arbitrary statistics

A new numerical methodology associated with a unified treatment is presented to solve the Boltzmann–BGK equation of gas dynamics for the classical and quantum gases described by the Bose–Einstein and Fermi–Dirac statistics. Utilizing a class of globally-stiffly-accurate implicit–explicit Runge–Kutta scheme for the temporal evolution, associated with the discrete ordinate method for the quadratures in the momentum space and the weighted essentially non-oscillatory method for the spatial discretization, the proposed scheme is asymptotic-preserving and imposes no non-linear solver or requires the knowledge of fugacity and temperature to capture the flow structures in the hydrodynamic (Euler) limit. The proposed treatment overcomes the limitations found in the work by Yang and Muljadi (2011) [33] due to the non-linear nature of quantum relations, and can be applied in studying the dynamics of a gas with internal degrees of freedom with correct values of the ratio of specific heat for the flow regimes for all Knudsen numbers and energy wave lengths. The present methodology is numerically validated with the unified treatment by the one-dimensional shock tube problem and the two-dimensional Riemann problems for gases of arbitrary statistics. Descriptions of ideal quantum gases including rotational degrees of freedom have been successfully achieved under the proposed methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

HEPfit: a code for the combination of indirect and direct constraints on high energy physics models

HEPfit is a flexible open-source tool which, given the Standard Model or any of its extensions, allows to (i) fit the model parameters to a given set of experimental observables; (ii) obtain predictions for observables. HEPfit can be used either in Monte Carlo mode, to perform a Bayesian Markov Chain Monte Carlo analysis of a given model, or as a library, to obtain predictions of observables for a given point in the parameter space of the model, allowing HEPfit to be used in any statistical framework. In the present version, around a thousand observables have been implemented in the Standard Model and in several new physics scenarios. In this paper, we describe the general structure of the code as well as models and observables implemented in the current release.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗