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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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The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.
Microtron-based Compact, Portable Gamma-Ray Source. The objective of Phase I of this project was to produce a conceptual design of a prototype compact microtron electron accelerator, which could be designed, built, and demonstrated in Phase II of the project. The conceptual design study included an analysis of the parameters of the microtron and its components, and the expected performance of the prototype microtron as a source of x-rays and/or RF neutrons in the MeV energy range. The major components of the microtron are the magnet, the accelerating system, the power system, the vacuum system, the control system, the beam extraction system and the targets to produce x-rays (and/or neutrons). Our objectives for the design of the prototype were for it to be compact, cost-effective, capable of producing high intensity x-ray (an/or neutron) fluxes. In addition, the prototype was to be easily assembled and disassembled so that components could be easily replaced. The main parameters for the prototype are the following: the range of electron kinetic energies, the output power, the RF frequency band (X-band, C-band, or S-Band), the type of injection (Type I or Type II), the magnet type, i.e. permanent magnet, electromagnet, or a hybrid combination of permanent and electromagnet. The results of the Phase I study and analysis for a prototype microtron are the following: The electron energy range can be varied from below 6 MeV to 9 MeV, the optimal frequency range is S-Band (2-4 GHz) RF frequency, Type II injection (described below), and the magnet type is the hybrid version. The prototype version will be capable of producing gamma ray doses of ~1800 R/min-m and neutron fluxes of up to ~6 x 10 10 n/s with appropriate targets. The results of the Phase I study and analysis are provided below. The proposed Phase II plan was to demonstrate the prototype at low beam power. In the subsequent Phase III, high power tests would be performed, and the design of commercial versions of microtrons with various energies, sizes and types would be produced and marketed, including a more compact and more portable 6 MeV battery-powered model that more closely meets the requirements in the original FOA topic description. In the course of the Phase I study, we also identified another microtron version, one that was larger (not compact) and more powerful than that of the Phase II prototype, which could serve as an intense source of photo- neutrons, up to 4 x 10 12 n/s for use in nuclear medicine, short-lived isotope production, or other applications. In addition, it could produce gamma dose rates up to 130 kR/min-m with a heavy metal bremsstrahlung target. The results and specifications of this were submitted to IPAC16 (Reference [12]) the paper is included in Addendum B. Because this version was beyond the scope of the Phase I project, there is no additional description in the Final Report.
With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.
Here the proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.
This field campaign will address multiple uncertainties in aerosol intensive properties, which are poorly represented in climate models, by means of aircraft measurements in biomass burning plumes. Key topics to be investigated are: 1. Aerosol mixing state and morphology 2. Mass absorption coefficients (MACs) 3. Chemical composition of non-refractory material associated with light-absorbing carbon (LAC) 4. Production rate of secondary organic aerosol (SOA) 5. Microphysical processes relevant to determining aerosol size distributions and single scattering albedo (SSA) 6. CCN activity. These topics will be investigated through measurements near active fires (0-5 hours downwind), where limited observations indicate rapid changes in aerosol properties, and in biomass burning plumes aged >5 hours. Aerosol properties and their time evolution will be determined as a function of fire type, defined according to fuel and the mix of flaming and smoldering combustion at the source.
This field campaign will address multiple uncertainties in aerosol intensive properties, which are poorly represented in climate models, by means of aircraft measurements in biomass burning plumes. Key topics to be investigated are: Aerosol mixing state and morphology Mass absorption coefficients (MACs) Chemical composition of non-refractory material associated with light-absorbing carbon (LAC) Production rate of secondary organic aerosol (SOA) Microphysical processes relevant to determining aerosol size distributions and single scattering albedo (SSA) CCN activity.
The measurement and analysis of the depolarization and attenuation that occur when millimeter wave radio signals propagate through rain are described. Progress was made in three major areas: the processing of recorded 1972 data, acquisition and processing of a large amount of 1973 data, and the development of a new theoretical model to predict rain cross polarization and attenuation. Each of these topics is described in detail along with radio frequency system design for cross polarization measurements.
An evaluation of existing theories on the existence of the planet's metallic core is presented. Topics considered are: (1) magnetic fields; (2) surface geology; (3) cosmochemical models.
Calibration of an airborne sidelooking radar is accomplished by the use of a model that relates the radar parameters to the physical mapping situation. Topics discussed include: characteristics of the transmitters; the antennas; target absorption and reradiation; the receiver and map making or radar data processing; and the calibration process.
Coupled equations are developed for mass and heat transport in a seasonal Mars model with condensation and sublimation of CO2 at the polar caps. Topics covered include physical considerations of planetary as mass and energy balance; effects of phase changes at the surface on mass and heat flux; atmospheric transport and governing equations; and numerical analysis.
A brief review is given of non-flare investigations using data obtained by the Ultraviolet Spectrometer and Polarimeter on the Solar Maximum Mission. The major topics described are sunspot research including magnetic field measurements, oscillations, and models; mass motions in quiet and active regions including steady flows and acoustic waves; and prominence research including physical conditions, dynamics, and mass motions around prominences. Also discussed are studies of UV bursts, the formation of the Cl I line at 1351 A, ozone in the terrestrial atmosphere, and active regions using correlated observations from other instruments on the spacecraft or on the ground.
Conference topics included definition of tool requirements, advanced multibody component representation descriptions, model reduction, parallel computation, real time simulation, control design and analysis software, user interface issues, testing and verification, and applications to spacecraft, robotics, and aircraft.
The theoretical basis and numerical implementation of NESSUS (Numerical Evaluation of Stochastic Structures Under Stress; Cruse et al., 1988), a computer code for probabilistic structural analyses of aerospace components, are described, with an emphasis on the use of NESSUS for reliability and risk assessment. Topics addressed include the structure of NESSUS, the material-properties model, computational procedures, probabilistic models of fatigue-crack initiation, risk/cost evaluation, fatigue-fracture analyses, and fatigue-crack propagation. Numerical results from typical applications are presented in extensive graphs and briefly characterized; the usefulness of NESSUS predictions for establishing inspection and retirement schedules and for component certification is indicated.
Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.
A brief survey of recent U.S. investigations in the field of heliospheric plasmas and their manifestations is presented, introducing the following collection of detailed reviews (accessions A91-46959 to A91-46964). Topics examined include the large-scale structure of interplanetary plasmas, models of Galactic cosmic-ray production and propagation, solar-wind turbulence, long-period solar-terrestrial variability, the possible relation between solar-neutrino counts and the sunspot cycle, X-ray studies of solar flares and their implications for solar processes, and the near-sun magnetic field.
Viewgraphs on active damping in a flexible manipulator are presented. Topics covered include: Shuttle Remote Manipulator System (SRMS); flexible structures; vibration; modeling of a flexible manipulator dynamical structure; designing control law criterion that minimizes vibration; and candidate application of fuzzy logic control law to the problem.
Viewgraphs on Rubber Airplane: Constraint-based Component-Modeling for Knowledge Representation in Computer Aided Conceptual Design are presented. Topics covered include: computer aided design; object oriented programming; airfoil design; surveillance aircraft; commercial aircraft; aircraft design; and launch vehicles.
The topics covered include the following: a test of a Space Shuttle model with various base enhancements intended to help reduce the drag of the Shuttle in the landing configuration; further tests conducted using a Shuttle model to explore base drag improvement techniques; testing of parafoils having different airfoil shapes and line lengths; a study of ground effects on a Shuttle model; and three dimensional velocity profiles in the wake aft of the Space Shuttle were determined to study the effects of wake velocities on the Orbiter drag chute.