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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 883 records · Page 49

Interactions of two and three mesons including higher partial waves from lattice QCD

We study two- and three-meson systems composed either of pions or kaons at maximal isospin using Monte Carlo simulations of lattice QCD. Utilizing the stochastic LapH method, we are able to determine hundreds of two- and three-particle energy levels, in nine different momentum frames, with high precision. We fit these levels using the relativistic finite-volume formalism based on a generic effective field theory in order to determine the parameters of the two- and three-particle K-matrices. We find that the statistical precision of our spectra is sufficient to probe not only the dominant s-wave interactions, but also those in d waves. In particular, we determine for the first time a term in the three-particle K-matrix that contains two-particle d waves. We use three N f = 2 + 1 CLS ensembles with pion masses of 200, 280, and 340 MeV. This allows us to study the chiral dependence of the scattering observables, and compare to the expectations of chiral perturbation theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simulation and flow physics of a shocked and reshocked high-energy-density mixing layer

This work describes a computational investigation of multimode instability growth and multimaterial mixing induced by multiple shock waves in a high-energy-density (HED) environment, where pressures exceed 1 Mbar. The simulations are based on a series of experiments performed at the National Ignition Facility (NIF) and designed as an HED analogue of non-HED shock-tube studies of the Richtmyer–Meshkov instability and turbulent mixing. A three-dimensional computational modelling framework is presented. It treats many complications absent from canonical non-HED shock-tube flows, including distinct ion and free-electron internal energies, non-ideal equations of state, radiation transport and plasma-state mass diffusivities, viscosities and thermal conductivities. The simulations are tuned to the available NIF data, and traditional statistical quantities of turbulence are analysed. Integrated measures of turbulent kinetic energy and enstrophy both increase by over an order of magnitude due to reshock. Large contributions to enstrophy production during reshock are seen from both the baroclinic source and enstrophy–dilatation terms, highlighting the significance of fluid compressibility in the HED regime. Dimensional analysis reveals that Reynolds numbers and diffusive Péclet numbers in the HED flow are similar to those in a canonical non-HED analogue, but conductive Péclet numbers are much smaller in the HED flow due to efficient thermal conduction by free electrons. It is shown that the mechanism of electron thermal conduction significantly softens local spanwise gradients of both temperature and density, which causes a minor but non-negligible decrease in enstrophy production and small-scale mixing relative to a flow without this mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation of the photodetachment spectra of the nitrate anion (NO 3 ₋ ) in the B ~ 2 E' energy range and non-adiabatic electronic population dynamics of NO 3

The photodetachment spectrum of the nitrate anion (NO 3 ₋ ) in the energy range of the NO 3 second excited state is simulated from first principles using quantum wave packet dynamics. The prediction at 10 K and 435 K relies on the use of an accurate full-dimensional fully coupled five state diabatic potential model utilizing an artificial neural network. The ability of this model to reproduce experimental spectra was demonstrated recently for the lower energy range. Analysis of the spectra indicates a weaker Jahn–Teller coupling compared to the first excited state. The detailed non-adiabatic dynamics is studied by computing the population dynamics. An ultra-fast non-statistical radiationless decay is found only among the Jahn–Teller components, which is followed by a slow statistical non-radiative decay among the different state manifolds. The latter is reproduced perfectly by a simple first order kinetics model. The dynamics in the second excited state is not affected by the presence of a conical intersection with the first excited state manifold.

36 MATERIALS SCIENCE↗

Nuclear rotation at the fission limit in Rf 254

A ground-state rotational band in the fissile nucleus Rf254 was observed for the first time. Levels up to spin 14 and excitation energy of 1.56 MeV were observed. The Rf254 nuclei were produced using the Pb206(Ti50,2n) fusion-evaporation reaction. It is the weakest reaction channel ever studied using in-beam γ-ray spectroscopic methods. The reaction products were separated from the beam in the Argonne gas-filled analyzer (AGFA). The Rf254 nuclei were implanted into a double-sided Si strip detector at the AGFA focal plane and tagged with subsequent ground-state spontaneous fission decays using temporal and spatial correlations. Prompt γ rays in coincidence with the Rf254 recoils were detected in the Gammasphere array of Ge detectors. In order to identify the ground-state rotational band in Rf254, a method for identifying rotational bands in low statistics γ-ray spectra was developed. The deduced Rf254 kinematic moment of inertia is smaller compared to neighboring even-even nuclei. This is most likely associated with a slightly lower quadrupole deformation and stronger pairing correlations in Rf254. The behavior of the moment of inertia as a function of rotational frequency is similar to that of the lighter N=150 isotones Fm250 and No252.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Joint Estimation of Topology and Injection Statistics in Distribution Grids with Missing Nodes

Optimal operation of distribution grid resources relies on accurate estimation of its state and topology. Practical estimation of such quantities is complicated by the limited presence of real-time meters. This article discusses a theoretical framework to jointly estimate the operational topology and statistics of injections in radial distribution grids under limited availability of nodal voltage measurements. In particular, we show that our proposed algorithms are able to provably learn the exact grid topology and injection statistics at all unobserved nodes as long as they are not adjacent. The algorithm design is based on novel ordered trends in voltage magnitude fluctuations at node groups, that are independently of interest for radial physical flow networks. The complexity of the designed algorithms is theoretically analyzed and their performance is validated using both linearized and nonlinear ac power flow samples in test distribution grids.

97 MATHEMATICS AND COMPUTING↗

Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

Security-constrained unit commitment (SCUC) is a fundamental problem in power systems and electricity markets. In practical settings, SCUC is repeatedly solved via mixed-integer linear programming (MIP), sometimes multiple times per day, with only minor changes in input data. In this work, we propose a number of machine learning techniques to effectively extract information from previously solved instances in order to significantly improve the computational performance of MIP solvers when solving similar instances in the future. Based on statistical data, we predict redundant constraints in the formulation, good initial feasible solutions, and affine subspaces where the optimal solution is likely to lie, leading to a significant reduction in problem size. Computational results on a diverse set of realistic and large-scale instances show that using the proposed techniques, SCUC can be solved on average 4.3 times faster with optimality guarantees and 10.2 times faster without optimality guarantees, with no observed reduction in solution quality. Out-of-distribution experiments provide evidence that the method is somewhat robust against data-set shift. Summary of Contribution. The paper describes a novel computational method, based on a combination of mixed-integer linear programming (MILP) and machine learning (ML), to solve a challenging and fundamental optimization problem in the energy sector. The method advances the state-of-the-art, not only for this particular problem, but also, more generally, in solving discrete optimization problems via ML. We expect that the techniques presented can be readily used by practitioners in the energy sector and adapted, by researchers in other fields, to other challenging operations research problems that are solved routinely.

Machine Learning↗

Computer analysis of X-band radar data

The effectiveness of using currently available computer techniques for interpretation of MSS data to interpret SAR imagery for forest monitoring was assessed. Data were gathered with NASA's airborne APQ-102 dual-polarized, X-band SAR in a flight at 60,000 ft. Microdensitometry was employed to digitize the HH- and HV-polarized imagery. A ground spatial resolution of 15 m was obtained, control points were identified, a second order biquadratic transformation was applied to compensate for orientation, and rms errors were calculated. A second data set was taken with 30 m resolution in order to simulate thematic mapper operation. Classification was performed with pixel-by-pixel and textural classification algorithms. A statistical analysis was also carried out to find any significant differences between classifiers in a data set for a given classifier. Each polarization featured an independent distortion which required appropriate preprocessing to correct. Further studies are recommended with multiple frequencies viewing and multiple polarizations and look angles to define the actual forest classifications that can be made with the SAR imagery.

Knowlton, D. J.↗

Digital image filtering in visualized boundary layers

The application of two-dimensional low-pass matched filtering is presented for use in objective processing of digitized flow visualization images in order to identify instantaneous large-scale organized structures in turbulent boundary layers. The images were digitally acquired simultaneously with the outputs of a two-dimensional rake of hot-wire sensors in the field of view of the digital camera. Two-dimensional low wavenumber analysis brought out patterns in the visualization images which consisted of slender inclined structures having an average streamwise scale of 100-200 v/u (tau) and a length on the order of 1-2 delta. The similarly processed two-dimensional streamwise velocity reconstructions reveal similar features. The ensemble statistics indicate that these inclined features brought out by this processing may be a basic flow module in higher Reynolds number flows which links the so-called wall 'bursting' process and the larger outer scale motions.

Corke, T. C.↗

A covariance analysis algorithm for interconnected systems

A covariance analysis algorithm for propagation of signal statistics in arbitrarily interconnected nonlinear systems is presented which is applied to six-degree-of-freedom systems. The algorithm uses statistical linearization theory to linearize the nonlinear subsystems, and the resulting linearized subsystems are considered in the original interconnection framework for propagation of the signal statistics. Some nonlinearities commonly encountered in six-degree-of-freedom space-vehicle models are referred to in order to illustrate the limitations of this method, along with problems not encountered in standard deterministic simulation analysis. Moreover, the performance of the algorithm shall be numerically exhibited by comparing results using such techniques to Monte Carlo analysis results, both applied to a simple two-dimensional space-intercept problem.

Cheng, Victor H. L.↗

Statistics of backscatter radar return from vegetation

The statistical characteristics of radar return from vegetation targets are investigated through a simulation study based upon the first-order scattered field. For simulation purposes, the vegetation targets are modeled as a layer of randomly oriented and spaced finite cylinders, needles, or discs, or a combination of them. The finite cylinder is used to represent a branch or a trunk, the needle for a stem or a coniferous leaf, and the disc for a decidous leaf. For a plane wave illuminating a vegetation canopy, simulation results show that the signal returned from a layer of disc- or needle-shaped leaves follows the Gamma distribution, and that the signal returned from a layer of branches resembles the log normal distribution. The Gamma distribution also represents the signal returned from a layer of a mixture of branches and leaves regardless of the leaf shapes. Results also indicate that the polarization state does not have a significant impact on signal distribution.

Karam, M. A.↗

Characterization of Global Near-Nadir Backscatter for Remote Sensing Radar Design

In order to evaluate side-lobe contamination from the near-nadir region for Ku-Band radars, a statistical characterization of global near-nadir backscatter is constructed. This characterization is performed for a variety of surface types using data from TRMM, Seasat, and Topex. An assessment of the relative calibration accuracy of these sensors is also presented.

Spencer, Michael W.↗

Characterization of Global Near-Nadir Backscatter for Remote Sensing Radar Design

In order to evaluate side-lobe contamination from the near-nadir region for Ku-Band radars, a statistical characterization of global near-nadir backscatter is constructed. This characterization is performed for a variety of surface types using data from TRMM, Seasat, and Topex. An assessment of the relative calibration accuracy of them sensors is also presented.

Spencer, Michael W.↗

Ocean Wave Studies with Applications to Ocean Modeling and Improvement of Satellite Altimeter Measurements

Combining analysis of satellite data (altimeter, scatterometer, high-resolution visible and infrared images, etc.) with mathematical modeling of non-linear wave processes, we investigate various ocean wave fields (on scales from capillary to planetary), their role in ocean dynamics and turbulent transport (of heat and biogeochemical quantities), and their effects on satellite altimeter measuring accuracy. In 1998 my attention was focused on long internal gravity waves (10 to 1000 km), known also as baroclinic inertia-gravity (BIG) waves. We found these waves to be a major factor of altimeter measurements "noise," resulting in a greater uncertainty [up to 10 cm in terms of sea surface height (SSH) amplitude] in the measured SSH signal than that caused by the sea state bias variations (up to 5 cm or so). This effect still remains largely overlooked by the satellite altimeter community. Our studies of BIG waves address not only their influence on altimeter measurements but also their role in global ocean dynamics and in transport and turbulent diffusion of biogeochemical quantities. In particular, in collaboration with Prof Peter Weichman, Caltech, we developed a theory of turbulent diffusion caused by wave motions of most general nature. Applied to the problem of horizontal turbulent diffusion in the ocean, the theory yielded the effective diffusion coefficient as a function of BIG wave parameters obtainable from satellite altimeter data. This effort, begun in 1997, has been successfully completed in 1998. We also developed a theory that relates spatial fluctuations of scalar fields (such as sea surface temperature, chlorophyll concentration, drifting ice concentration, etc.) to statistical characteristics of BIG waves obtainable from altimeter measurements. A manuscript is in the final stages of preparation. In order to verify the theoretical predictions and apply them to observations, we are now analyzing Sea-viewing Wide Field of view Sensor (SeaWiFS) and Field of view Sensor (SeaWiFS) and Advanced Very High-Resolution Radiometer (AVHRR) data on sea surface temperature (SST) and chlorophyll concentration jointly with TOPEX/POSEIDON data on SSH variations.

Glazman, Roman E.↗

Evolution of Galaxies and the Star Formation Rate in the Infrared

A central goal of extragalactic observational astronomy is to understand how normal galaxies evolve with redshift, and particularly when galaxies formed their stars. While optical and rest-frame UV observations have begun to address these issues, the interpretation of such data is particularly challenging because of the sensitivity to dust obscuration (at optical and UV wavelengths). The absorbed light is reradiated at IR wavelengths, hence the optimal indicators of the star-formation rate (SFR) is at a rest-frame wavelength of approx. 60 microns. The Spitzer Space Telescope mission is beginning to revolutionize the study of the global properties and evolution of galaxies. Spitzer reaches nearly two orders of magnitude more sensitivity than previous IR space missions. This research program is to study the SFR using statistical samples of galaxies in the local universe, at intermediate redshifts, and set the stage for continuing studies up to z=5. The overall research program is divided into three main investigations: A Mid-IR Hubble Atlas and SFR estimators in the local universe, Evolution of the SFR at 0 < z < 1 using pencil beam redshift surveys, and Galaxy formation and evolution at 1 < z < 5. The Spitzer Space Telescope launched during the past year and the first papers from it are currently being submitted to The Astrophysical Journal. This is clearly an exciting time for IR astronomy!

Pahre, Michael A.↗

Evolution of Galaxies and the Star Formation Rate in the Infrared

A central goal of extragalactic observational astronomy is to understand how normal galaxies evolve with redshift, and particularly when galaxies formed their stars. While optical and rest-frame UV observations have begun to address these issues, the interpretation of such data is particularly challenging because of the sensitivity to dust obscuration (at optical and UV wavelengths). The absorbed light is re-radiated at IR wavelengths, hence the optimal indicators of the star formation rate (SFR) is at a rest-frame wavelength of approx. 60 microns. The Spitzer Space Telescope mission is revolutionizing the study of the global properties and evolution of galaxies. Spitzer reaches nearly two orders of magnitude more sensitivity than previous IR space missions. This research program is to study the SFR using statistical samples of galaxies in the local universe, at intermediate redshifts, and set the stage for continuing studies up to z=5. The overall research program is divided into three main investigations: A Mid-IR Hubble Atlas and SFR estimators in the local universe, Evolution of the SFR at 0 < z < 1 using pencil beam redshift surveys, and Galaxy formation and evolution at 1 < z < 5. The first papers from Spitzer were published during the last year, including ten refereed journal papers where the PI was first or co-author.

Pahre, Michael A.↗

Data Assimilation and Data Fusion for Planetary Atmospheres

The overarching goal of this Cooperative Agreement was to develop a model and procedures for the data assimilation of planetary spacecraft atmospheric observations. Data assimilation - in its application to weather analysis and prediction - is the process of finding an initial state of the meteorological variables (winds, temperatures, pressures, etc.) of an atmosphere, which, when propagated forward in time using a deterministic general circulation model, reproduces all of the available observations over that time to within the measurement and computational errors. With this definition, data assimilation is seen to be a natural extension of well-known least-squares minimization techniques. The primary complication arises from the scale of the problem: For the Martian atmosphere with the available nadir-viewing Thermal Emission Spectrometer data from Mars Global Surveyor, approximately 1,000,000 individual measurements of channel radiances (in the 15-micrometer region, where these radiances relate directly to the surface and atmospheric temperature) were made per day. A suitable general circulation model for dealing with this data set has on the order of 20,000 independent variables. After some spatial and temporal averaging of the data - which provides a necessary statistical estimate of the representativeness of the measurements, a crucial issue in data assimilation - the problem reduces in scale to the solution of approximately 50,000 equations for the 20,000 variables.

Houben, Howard↗

Characterization of Days Based On Analysis of National Airspace System Performance Metrics

Days of operations in the National Airspace System can be described in term of traffic demand, runway conditions, equipment outages, and surface and enroute weather conditions. These causes manifest themselves in terms of departure delays, arrival delays, enroute delays and traffic flow management delays, Traffic flow management initiatives such as, ground stops, ground delay programs, miles-in-trail restrictions, rerouting and airborne holding are imposed to balance the air traffic demand with respect to the available capacity, In order to maintain operational efficiency of the National Airspace System, the Federal Aviation Administration (FAA) maintains delay sad other statistics in the Air Traffic Operations Network (OPSNET) and the Aviation System Performance Metrics (ASPM) databases. OPSNET data includes reportable delays of fifteen minutes ox more experienced by Instrument Flight Rule (IFR) flights. Numbers of aircraft affected by departure delays, enroute delays, arrival delays and traffic flow delays are recorded in the OPSNET data. ASPM data consist of number of actual departures, number of canceled departures, percentage of on time departures, percentage of on time gate arrivals, taxi-out delays. taxi-in delays, gate delays, arrival delays and block delays. Surface conditions at the major U.S. airports are classified in terms of Instrument Meteorological Condition (IMC) and Visual Meteorological Condition (VMC) as a function of the time of the day in the ASPM data. The main objective of this paper is to use OPSNET and ASPM data to classify the days in the datasets into few distinct groups, where each group is separated from the other groups in terms of a distance metric. The motivations for classifying the days are two-fold, 1) to enable selection of days of traffic with particular operational characteristics for concept evaluation using system-wide simulation systems such as the National Aeronautics and Space Administration's Airspace Concepts Evaluation Tool (ACES) and 2) to enable evaluation of a given day with respect to the characteristics of the classified groups. The first part of the paper is devoted to the analysis of major trends seen in the OPSNET and ASPM data. The second part of the paper is devoted to describing features or measures derived from the OPSNET and ASPM data that are suitable for characterizing days, and the classification algorithm used for grouping the days. Finally, the method for evaluating the characteristics of a given day with respect to the properties of the groups is described.

Chatterji, Gano B.↗