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At least 325 records · Page 18

Regular and Chaotic Quantum Dynamics of Two-Level Atoms in a Selfconsistent Radiation Field

Dynamics of two-level atoms interacting with their own radiation field in a single-mode high-quality resonator is considered. The dynamical system consists of two second-order differential equations, one for the atomic SU(2) dynamical-group parameter and another for the field strength. With the help of the maximal Lyapunov exponent for this set, we numerically investigate transitions from regularity to deterministic quantum chaos in such a simple model. Increasing the collective coupling constant b is identical with 8(pi)N(sub 0)(d(exp 2))/hw, we observed for initially unexcited atoms a usual sharp transition to chaos at b(sub c) approx. equal to 1. If we take the dimensionless individual Rabi frequency a = Omega/2w as a control parameter, then a sequence of order-to-chaos transitions has been observed starting with the critical value a(sub c) approx. equal to 0.25 at the same initial conditions.

Konkov, L. E.↗

Model of ASTM Flammability Test in Microgravity: Iron Rods

There is extensive qualitative results from burning metallic materials in a NASA/ASTM flammability test system in normal gravity. However, this data was shown to be inconclusive for applications involving oxygen-enriched atmospheres under microgravity conditions by conducting tests using the 2.2-second Lewis Research Center (LeRC) Drop Tower. Data from neither type of test has been reduced to fundamental kinetic and dynamic systems parameters. This paper reports the initial model analysis for burning iron rods under microgravity conditions using data obtained at the LERC tower and modeling the burning system after ignition. Under the conditions of the test the burning mass regresses up the rod to be detached upon deceleration at the end of the drop. The model describes the burning system as a semi-batch, well-mixed reactor with product accumulation only. This model is consistent with the 2.0-second duration of the test. Transient temperature and pressure measurements are made on the chamber volume. The rod solid-liquid interface melting rate is obtained from film records. The model consists of a set of 17 non-linear, first-order differential equations which are solved using MATLAB. This analysis confirms that a first-order rate, in oxygen concentration, is consistent for the iron-oxygen kinetic reaction. An apparent activation energy of 246.8 kJ/mol is consistent for this model.

Steinberg, Theodore A↗

Accelerating the Design of Space Vehicles

One of NASA's key goals is to increase the safety and reduce the cost of space transportation. Thus, a key element of NASA's new Integrated Space Transportation Plan is to develop new propulsion, structures, and operations for future generations of reusable launch vehicles (RLVs). As part of this effort to develop the next RLV, the ClCT Program's Computing, Networking, and Information Systems (CNIS) Project is developing and demonstrating collaborative software technologies that use the collective power of the NASA Grid to accelerate spacecraft design. One of these technologies, called AeroDB, automates the execution and monitoring of computational fluid dynamics (CFD) parameter studies on the NASA Grid. About the NASA Grid The NASA Grid, or Information Power Grid,. is being developed to leverage the distributed resources of NASA's many computers. instruments, simulators, and data storage systems. The goal is to use these combined resources to sdve difficult NASA challenges, such as iimulating the entire flight of a space vehicle from ascent to descent.To realize the vision of the NASA Grid, the CNIS Project is developing the software framework and protocols for building domain-specific environments and interfaces, new Grid services based on emerging industry standards, and advanced networking and computing testbeds to support new Grid-based applications such as AeroDB.

Laufenberg, Larry↗

Monitoring and analysis of data in cyberspace

Information from monitored systems is displayed in three dimensional cyberspace representations defining a virtual universe having three dimensions. Fixed and dynamic data parameter outputs from the monitored systems are visually represented as graphic objects that are positioned in the virtual universe based on relationships to the system and to the data parameter categories. Attributes and values of the data parameters are indicated by manipulating properties of the graphic object such as position, color, shape, and motion.

Schwuttke, Ursula M.↗

GSFC DORIS Contribution to ITRF2008

The NASA GSFC DORIS analysis center has provided weekly DORIS solutions from November 1992 to January 2009 (839 SINEX files) of station positions and Earth Orientation Parameters for inclusion in the DORIS contribution to ITRF2008. The NASA GSFC GEODYN orbit determination software was used to process the orbits and produce the normal equations. The weekly SINEX gscwd 10 submissions included DORIS data from Envisat, TOPEX!Poseidon, SPOT-2, SPOT-3, SPOT-4, SPOT-5. The orbits were mostly seven days in length (except for weeks with data gaps or maneuvers). The processing used the GRACE-derived EIGEN-GL04S1 gravity model, updated modeling for time-variable gravity, the GOT4.7 ocean tide model and tuned satellite-specific macromodels for SPOT -2, SPOT -3, SPOT -4, SPOT-5 and TOPEX/Poseidon. The University College London (UCL) radiation pressure model for Envisat improves nonconservative force modeling for this satellite, reducing the median residual empirical daily along-track accelerations from 3.75 x 10-9 m/s(exp 2) with the a priori macromodel to 0.99 x 10-9 m/s2 with the UCL model. For the SPOT and Envisat DORIS satellite orbits from 2003 to 2008, we obtain average RMS overlaps of 0.8-0.9 cm in the radial direction, 2.1-3.4 cm cross-track, and 1.7-2.3 cm along-track. The RMS orbit differences between Envisat DORIS-only and SLR & DORIS orbits are 1.1 cm radially, 6.4 cm along-track and 3.7 cm cross-track and are characterized by systematic along-track mean offsets due to the Envisat DORIS system time bias of +/- 5-1O micro s. We obtain a good agreement between the geometrically-determined geocenter parameters and geocenter parameters determined dynamically from analysis of the degree one terms of the geopotential. The intrinsic RMS weekly position repeatability with respect to the IDS-3 combination ranges from 2.5 to 3.0 cm in 1993-1994 to 1.5 cm in 2007-2008.

Le Bail, K.↗

Inductive Pulsed Plasma Thruster Model with Time-Evolution of Energy and State Properties

A model for pulsed inductive plasma acceleration is presented that consists of a set of circuit equations coupled to both a one-dimensional equation of motion and an equation governing the partitioning of energy. The latter two equations are obtained for the plasma current sheet by treating it as a single element of finite volume and integrating the governing equations over that volume. The integrated terms are replaced where necessary by physically-equivalent quantities that are calculated through the solution of other parts of the governing equation set. The model improves upon previous one-dimensional performance models by permitting the time-evolution of the energy and state properties of the plasma, the latter allowing for the tailoring of the model to different gases that may be chosen as propellants. The time evolution of the various energy modes in the system and the associated plasma properties, calculated for argon propellant, are presented to demonstrate the efficacy of the model. The model produces a result where efficiency is maximized at a given value of the electrodynamic scaling term known as the dynamic impedance parameter. Qualitatively and quantitatively, the model compares favorably with performance measured for two separate inductive pulsed plasma thrusters, with disagreements attributable to simplifying assumptions employed in the generation of the model solution.

Polzin, Kurt A.↗

Examining Dense Data Usage near the Regions with Severe Storms in All-Sky Microwave Radiance Data Assimilation and Impacts on GEOS Hurricane Analyses

Many numerical weather prediction (NWP) centers assimilate radiances affected by clouds and precipitation from microwave sensors, with the expectation that these data can provide critical constraints on meteorological parameters in dynamically sensitive regions to make significant impacts on forecast accuracy for precipitation. The Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center assimilates all-sky microwave radiance data from various microwave sensors such as all-sky GPM Microwave Imager (GMI) radiance in the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS), which includes the GEOS atmospheric model, the Gridpoint Statistical Interpolation (GSI) atmospheric analysis system, and the Goddard Aerosol Assimilation System (GAAS). So far, most of NWP centers apply same large data thinning distances, that are used in clear-sky radiance data to avoid correlated observation errors, to all-sky microwave radiance data. For example, NASA GMAO is applying 145 km thinning distances for most of satellite radiance data including microwave radiance data in which all-sky approach is implemented. Even with these coarse observation data usage in all-sky assimilation approach, noticeable positive impacts from all-sky microwave data on hurricane track forecasts were identified in GEOS-5 system. The motivation of this study is based on the dynamic thinning distance method developed in our all-sky framework to use of denser data in cloudy and precipitating regions due to relatively small spatial correlations of observation errors. To investigate the benefits of all-sky microwave radiance on hurricane forecasts, several hurricane cases selected between 2016-2017 are examined. The dynamic thinning distance method is utilized in our all-sky approach to understand the sources and mechanisms to explain the benefits of all-sky microwave radiance data from various microwave radiance sensors like Advanced Microwave Sounder Unit (AMSU-A), Microwave Humidity Sounder (MHS), and GMI on GEOS-5 analyses and forecasts of various hurricanes.

Kim, Min-Jeong↗

Method of Obtaining High Resolution Intrinsic Wire Boom Damping Parameters for Multi-Body Dynamics Simulations

The goal of NASA's Magnetospheric MultiScale (MMS) mission is to understand magnetic reconnection with sensor measurements from four spinning satellites flown in a tight tetrahedron formation. Four of the six electric field sensors on each satellite are located at the end of 60- meter wire booms to increase measurement sensitivity in the spin plane and to minimize motion coupling from perturbations on the main body. A propulsion burn however, might induce boom oscillations that could impact science measurements if oscillations do not damp to values on the order of 0.1 degree in a timely fashion. Large damping time constants could also adversely affect flight dynamics and attitude control performance. In this paper, we will discuss the implementation of a high resolution method for calculating the boom's intrinsic damping, which was used in multi-body dynamics simulations. In summary, experimental data was obtained with a scaled-down boom, which was suspended as a pendulum in vacuum. Optical techniques were designed to accurately measure the natural decay of angular position and subsequently, data processing algorithms resulted in excellent spatial and temporal resolutions. This method was repeated in a parametric study for various lengths, root tensions and vacuum levels. For all data sets, regression models for damping were applied, including: nonlinear viscous, frequency-independent hysteretic, coulomb and some combination of them. Our data analysis and dynamics models have shown that the intrinsic damping for the baseline boom is insufficient, thereby forcing project management to explore mitigation strategies.

Yew, Alvin G.↗

Evolution of Tropical Cyclone Properties Across the Development Cycle of the GISS-E3 Global Climate Model

The next-generation global climate model from the NASA Goddard Institute for Space Studies, GISS-E3, contains many improvements to resolution and physics that allow for improved representation of tropical cyclones (TCs) in the model. This study examines the properties of TCs in two different versions of E3 at different points in its development cycle, run for 20 years at 0.5 degree resolution, and compares these TCs with observations, the previous generation GISS model, E2, and other climate models. E3 shares many TC biases common to global climate models, such as having too few tropical cyclones, but is much improved from E2. E3 produces strong enough TCs that observation-based wind speed thresholds can now be used to detect and track them, and some storms now reach hurricane intensity; neither of these was true of E2. Model development between the first and second versions of E3 further increased the number and intensity of TCs and reduced TC count biases globally and in most regions. One-year sensitivity tests to changes in various microphysical and dynamical tuning parameters are also examined. Increasing the entrainment rate for the more strongly-entraining plume in the convection scheme increases the number of TCs (though also affecting other climate variables, and in some cases increasing biases). Variations in divergence damping did not have a strong effect on simulated TC properties, contrary to expectations based on previous studies. Overall, the improvements in E3 make it more credible for studies of TC activity and its relationship to climate.

Tropical Cyclones↗

Development of Data Reduction Methods for Dynamic Stability Tests in a Magnetic Suspension and Balance System

The NASA/ODU 6-inch Magnetic Suspension and Balance System (MSBS) is operational in a “free-to-yaw” configuration in a subsonic wind tunnel. The MSBS hardware has been heavily modified over recent years to utilize a transverse magnetization scheme, with mixed electromagnetic and motion tracking camera position sensors and a relatively sophisticated control system. The project aims to provide a unique test capability for dynamic stability testing of planetary entry capsules, free from support interference. Aerodynamic tests are being conducted, with a focus of validation of the data reduction methods used to extract dynamic stability parameters. The unique complication is the existence of magnetic, aerodynamic, and mass centers, where magnetic, aerodynamic, and inertia forces respectively are resolved. The paper will report on tests of a family of EEV-like geometries, where the conical half-angle varied between 45 and 60 degrees in steps of 3.75 degrees. The paper will present experimental results from the parametric family of EEV-like geometries. Simulation results will also be presented, based on a two or three degree-of-freedom Simulink model. The model allows the exploration of the effects of non-coincident centers and the sensitivity of results arising from uncertainties in location.

Entry Systems Modeling↗

Diagnostics for Linac Optimization With Machine Learning

The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator chain. Providing stable intensity, energy, and emittance is key since it directly affects downstream machines. To counter fluctuations of Linac output due to various effects to be described below we are working on implementing dynamic longitudinal parameter optimization based on Machine Learning (ML). As inputs for the ML model, signals from beam diagnostics have to be well understood and reliable. In this paper we discuss the status and plans for ML-based optimization as well as preliminary results of diagnostics studies.

43 PARTICLE ACCELERATORS↗

Distributed deep reinforcement learning for simulation control

Abstract Several applications in the scientific simulation of physical systems can be formulated as control/optimization problems. The computational models for such systems generally contain hyperparameters, which control solution fidelity and computational expense. The tuning of these parameters is non-trivial and the general approach is to manually ‘spot-check’ for good combinations. This is because optimal hyperparameter configuration search becomes intractable when the parameter space is large and when they may vary dynamically. To address this issue, we present a framework based on deep reinforcement learning (RL) to train a deep neural network agent that controls a model solve by varying parameters dynamically. First, we validate our RL framework for the problem of controlling chaos in chaotic systems by dynamically changing the parameters of the system. Subsequently, we illustrate the capabilities of our framework for accelerating the convergence of a steady-state computational fluid dynamics solver by automatically adjusting the relaxation factors of the discretized Navier–Stokes equations during run-time. The results indicate that the run-time control of the relaxation factors by the learned policy leads to a significant reduction in the number of iterations for convergence compared to the random selection of the relaxation factors. Our results point to potential benefits for learning adaptive hyperparameter learning strategies across different geometries and boundary conditions with implications for reduced computational campaign expenses 4 4 Data and codes available at https://github.com/Romit-Maulik/PAR-RL . .

42 ENGINEERING↗

Summary of directional divergence characteristics of several high performance aircraft configurations

The present paper summarizes the high-angle-of-attack characteristics of a number of high-performance aircraft as determined from model force tests and free-flight model tests and correlates these characteristics with the dynamic directional-stability parameter. This correlation shows that the dynamic directional-stability parameter correlates fairly well with directional divergence. Data are also presented to show the effect of some airframe modifications on the directional divergence potential of the configuration. These results show that leading-edge slates seem to be the most effective airframe modification for reducing or eliminating the directional divergence potential of aircraft with moderately swept wings.

Greer, H. D.↗

An Ab Initio Molecular Dynamics Study of Key Thermodynamic Input Parameters for Computer Simulation of U-6Nb Solidification

The key to metallic fuel development is the fabrication of uranium metal and alloys into fuel forms. U-Nb alloys are one of the best candidates for a metallic fuel alloy with high-temperature strength sufficient to support the core, acceptable nuclear properties, good fabricability, and compatibility with usable coolant media. Melt processing has been a key component of the metallic fuel cycle, and process models require thermophysical parameters at elevated temperatures, particularly above the melting temperatures, regarding which experimental data are scarce, for accurate simulations and process development. By means of ab initio density-functional theory (DFT) quantum molecular dynamics (QMD), we have calculated the main thermophysical parameters—the density, thermal expansion coefficient, specific heat, thermal conductivity, melting temperature, latent heat of fusion, and viscosity—used in the modeling of the U-6 wt.% Nb alloy casting. The melting temperature of the U-6 wt.% Nb alloy at ambient pressure is obtained by means of QMD simulations using the Z-method. The ambient volume change and latent heat of melting of U-6 wt.% Nb are also derived from QMD simulations in conjunction with analytical fitting for the energy and pressure. The thermal conductivity for the solid U-Nb alloy is calculated from the semi-classical Boltzmann transport equation combined with an estimate of the electron relaxation time obtained from DFT simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Variations in density and chemical composition at 120 km from chemical and dynamical processes.

Atmospheric parameters show both systematic and random patterns of behavior at 120 km altitude. Variations in density, temperature, pressure, and especially atomic oxygen concentration are important. The variations are particularly significant because constant boundary conditions at this altitude have commonly been assumed in atmospheric model making. It is surprising how well the assumption of constant boundary conditions has served over the past decade. However, their use has probably introduced erroneous concepts into the field of atmospheric structure, or at least held off the recognition and introduction of important new concepts. The variations at 120 km are caused by changes in energy input into the upper atmosphere, including internal gravity waves and tidal energy from below, and changes in the transport processes within the atmosphere.

Johnson, F. S.↗