We have developed algorithms to automatically learn a detection map of a deployed sensor field for a virtual presence and extended defense (VPED) system without apriori knowledge of the local terrain. The VPED system is an unattended network of sensor pods, with each pod containing acoustic and seismic sensors. Each pod has the ability to detect and classify moving targets at a limited range. By using a network of pods we can form a virtual perimeter with each pod responsible for a certain section of the perimeter. The site's geography and soil conditions can affect the detection performance of the pods. Thus, a network in the field may not have the same performance as a network designed in the lab. To solve this problem we automatically estimate a network's detection performance as it is being installed at a site by a mobile deployment unit (MDU). The MDU will wear a GPS unit, so the system not only knows when it can detect the MDU, but also the MDU's location. In this paper, we demonstrate how to handle anisotropic sensor-configurations, geography, and soil conditions.
In this paper we will demonstrate that the computational effort of FWI can be reduced significantly by applying it to data formed by encoding and summing source gathers, if the encoding of the sources is changed between iterations. Changing the encoding between iterations changes the crosstalk noise caused by the summation of the sources. Thus, the source crosstalk-noise stacks out of the inverted earth model, allowing summation of a large number of encoded sources. We call this method encoded simultaneous-source FWI (ESSFWI).
The U.S. Department of Energy (DOE) provides scientific infrastructure and data archives to the international Arctic research community through a national user facility, the ARM Climate Research Facility, located on the North Slope of Alaska. The ARM sites at Barrow and Atqasuk, Alaska have been collecting and archiving atmospheric data for more than 10 years. These data have been used for scientific investigation as well as remote sensing validations. Funding from the Recovery Act (American Recovery and Reinvestment Act of 2009) will be used to install new instruments and upgrade existing instruments at the North Slope sites. These instruments include: scanning precipitation radar; scanning cloud radar; automatic balloon launcher; high spectral resolution lidar; eddy correlation flux systems; and upgraded ceilometer, AERI, micropulse lidar, and millimeter cloud radar. Information on these planned additions and upgrades will be provided in our poster. An update on activities planned at Oliktok Point will also be provided.
The objective of this Standard is the specification of a verification and validation approach that quantifies the degree of accuracy inferred from the comparison of solution and data for a specified variable at a specified validation point. The approach uses the concepts from experimental uncertainty analysis to consider the errors and uncertainties in both the solution and the data. The scope of this Standard is the quantification of the degree of accuracy of simulation of specified validation variables at a specified validation point for cases in which the conditions of the actual experiment are simulated. Consideration of solution accuracy at points within a domain other than the validation points, for example interpolation/extrapolation in a domain of validation, is a matter of engineering judgment specific to each family of problems and is beyond the scope of this Standard.
The purpose of this work is to improve detection methods that can reliably identify special nuclear material (SNM). One method that can be used to identify special nuclear material is neutron multiplicity analysis. This method detects multiple time-correlated neutrons released from a fission event in the SNM. This work investigates the ability of the software code MCNP-PoliMi to simulate neutron multiplicity measurements from a highly moderated SNM source. A measurement of a 4.5-kg alpha-phase metal plutonium sphere surrounded by up to 6 inches of polyethylene shells has recently been performed by Sandia National Laboratories personnel at the Nevada Test Site. A post-processing code was developed to account for dead-time effects within the detector and to determine the neutron multiplicity distributions for various time intervals. With the distributions calculated, the Feynman-Y can be determined. The Feynman-Y is a metric that measures the level of correlation present in a sample. At this time MCNP-PoliMi is able predict the Feynman-Y within 10% of the measured value.
This presentation discusses the following topics: (1) Red Sky Background; (2) 3D Torus Interconnect Concepts; (3) Difficulties of Torus in IB; (4) New Routing Code for IB a 3D Torus; (5) Red Sky 3D Torus Implementation; and (6) Managing a Large IB Machine. Computing at Sandia: (1) Capability Computing - Designed for scaling of single large runs, Usually proprietary for maximum performance, and Red Storm is Sandia's current capability machine; (2) Capacity Computing - Computing for the masses, 100s of jobs and 100s of users, Extreme reliability required, Flexibility for changing workload, Thunderbird will be decommissioned this quarter, Red Sky is our future capacity computing platform, and Red Mesa machine for National Renewable Energy Lab. Red Sky main themes are: (1) Cheaper - 5X capacity of Tbird at 2/3 the cost, Substantially cheaper per flop than our last large capacity machine purchase; (2) Leaner - Lower operational costs, Three security environments via modular fabric, Expandable, upgradeable, extensible, and Designed for 6yr. life cycle; and (3) Greener - 15% less power-1/6th power per flop, 40% less water-5M gallons saved annually, 10X better cooling efficiency, and 4x denser footprint.
The readout of a solid state qubit often relies on single charge sensitive electrometry. However the combination of fast and accurate measurements is non trivial due to large RC time constants due to the electrometers resistance and shunt capacitance from wires between the cold stage and room temperature. Currently fast sensitive measurements are accomplished through rf reflectrometry. I will present an alternative single charge readout technique based on cryogenic CMOS circuits in hopes to improve speed, signal-to-noise, power consumption and simplicity in implementation. The readout circuit is based on a current comparator where changes in current from an electrometer will trigger a digital output. These circuits were fabricated using Sandia's 0.35 {micro}m CMOS foundry process. Initial measurements of comparators with an addition a current amplifier have displayed current sensitivities of < 1nA at 4.2K, switching speeds up to {approx}120ns, while consuming {approx}10 {micro}W. I will also discuss an investigation of noise characterization of our CMOS process in hopes to obtain a better understanding of the ultimate limit in signal to noise performance.
Constructing high-fidelity control pulses that are robust to control and system/environment fluctuations is a crucial objective for quantum information processing (QIP). We combine dynamical decoupling (DD) with optimal control (OC) to identify control pulses that achieve this objective numerically. Previous DD work has shown that general errors up to (but not including) third order can be removed from {pi}- and {pi}/2-pulses without concatenation. By systematically integrating DD and OC, we are able to increase pulse fidelity beyond this limit. Our hybrid method of quantum control incorporates a newly-developed algorithm for robust OC, providing a nested DD-OC approach to generate robust controls. Motivated by solid-state QIP, we also incorporate relevant experimental constraints into this DD-OC formalism. To demonstrate the advantage of our approach, the resulting quantum controls are compared to previous DD results in open and uncertain model systems.
Growth of high quality graphene films on SiC is regarded as one of the more viable pathways toward graphene-based electronics. Graphitic films form on SiC at elevated temperature because of preferential sublimation of Si. Little is known, however, about the atomistic processes of interrelated SiC decomposition and graphene growth. We have observed the formation of graphene on SiC by Si sublimation in an Ar atmosphere using low energy electron microscopy, scanning tunneling microcopy and atomic force microscopy. This work reveals that the growth mechanism depends strongly on the initial surface morphology, and that carbon diffusion governs the spatial relationship between SiC decomposition and graphene growth. Isolated bilayer SiC steps generate narrow ribbons of graphene, whereas triple bilayer steps allow large graphene sheets to grow by step flow. We demonstrate how graphene quality can be improved by controlling the initial surface morphology specifically by avoiding the instabilities inherent in diffusion-limited growth.
Establishing the atomic structure and composition of interfaces in thermoelectric materials is important to understanding how these defects mediate thermal and electronic transport. Here, we discuss our experimental observations and theoretical calculations of the Bi{sub 2}Te{sub 3} (0001) basal twin in nanocrystalline Bi{sub 2}Te{sub 3}. This interface is important both because it is common in tetradymite-structured thermoelectric compounds and because it serves as a useful model system for more complex interfaces. Macroscopically, the (0001) twin corresponds to a 180 rotation of the crystal about the [0001] axis, which reverses the stacking of the basal planes. The basal planes of Bi{sub 2}Te{sub 3} are arranged in 5-plane groupings of alternating Bi and Te layers. Microscopically, one envisions three possible interface terminations: at the Te layer in the middle of the 5-layer packet, at a Bi layer, or at the Te-double layer at the junction of the 5-layer packet. Using aberration-corrected HAADF-STEM imaging, we have established that the twin boundary terminates at the Te-double layer. This result is consistent with ab initio calculations, which predict that the lowest energy for the three candidate structures is for this termination.
Electrons on the surface of superfluid helium have extremely high mobilities and long predicted spin coherence times, making them ideal mobile qubits. Previous work has shown that electrons localized in helium filled channels can be reliably transported between multiple underlying gates. Silicon chips have been designed, fabricated, and post processed by reactive ion etching to leverage the large scale integration capabilities of silicon technology. These chips, which serve as substrates for the electrons on helium research, utilize silicon CMOS for on-chip signal amplification and multiplexing and the uppermost metal layers for defining the helium channels and applying electrical potentials for moving the electrons. We will discuss experimental results for on-chip circuitry and clocked electron transport along etched channels.
A light beam induced current (LBIC) measurement is a non-destructive technique that produces a spatial graphical representation of current response in photovoltaic cells with respect to position when stimulated by a light beam. Generally, a laser beam is used for these measurements because the spot size can be made very small, on the order of microns, and very precise measurements can be made. Sandia National Laboratories Photovoltaic System Evaluation Laboratory (PSEL) uses its LBIC measurement technique to characterize single junction mono-crystalline and multi-crystalline solar cells ranging from miniature to conventional sizes. Sandia has modified the already valuable LBIC technique to enable multi-junction PV cells to be characterized.
Nanoporous metallic particles are of great interest for a range of applications including catalysis, gas storage, and electrical energy storage. In particular, recent work has shown that bulk powders of porous palladium can be synthesized in a scalable fashion. This material has pore sizes in the 2-5 nm range and has promise for use in hydrogen storage applications. However, because of the small pore size such materials are very susceptible to morphological evolution during aging, especially at elevated temperatures, leading to degradation of their storage properties. To better understand and predict the phenomena at work in nanoporous metal aging, we have developed a kinetic Monte Carlo (kMC) model for the simulation of atomic diffusion in a Pd lattice. The model is implemented in Sandia's parallelized kMC code SPPARKS. SPPARKS utilizes a spatial decomposition parallelization scheme, allowing large-scale simulations including millions of atoms. The diffusion model includes single-atom hops as well as Schwoebel barrier events that mimic concerted atom motions involving multiple lattice sites. Our simulations show that for statistically homogeneous nanoporous networks, coarsening at elevated temperature as measured by the surface area can be described by a scaling law that closely follows the L {approx} {sup 1/4} scaling predicted by continuum surface diffusion theory. This scaling holds despite the presence of surface faceting due to our simulations being run at temperatures below the roughening temperature of the material. Sensitivities of the rate of coarsening, the scaling exponent, and the amount of surface faceting to model parameters including temperature and event activation rates are explored. Because of the large spatial scales attainable in our computations, we are able to simulate nanoporous particle geometries similar to those synthesized in the laboratory, and compare directly to material aging experiments including porosimetry measurements and TEM images of particles.
JMP and design of experiments (DOE) have been successfully applied to security system technologies from sensors to communication and display systems. In all cases, the technologies have been complex enough to warrant the need for a statistical determination of significant factors and/or the generation of predictive models. For the sensors, it was the task of calibrating a fiber optic intrusion detection sensor (FOIDS) with 32 adjustable settings. In addition to the numerous settings, the FOIDS also had two software processors for detecting different types of alarms. The problem was made more complex when the different types of alarms occurred on the wrong processors, causing nuisance alarms. JMP's ability to optimize several predictive models simultaneously with JMP's Prediction Profiler flash files was an important factor in producing field solutions. For the Communications and Display testbed system, numerous hardware and software network components had been integrated to build a functional system. Although the components of the system had been tested individually, the system's performance could not be piecewise evaluated. Through the application of JMP's design of experiments and data mining capabilities, it was possible to test some of the factors affecting the system's performance and to differentiate between some of the software and hardware contributors. This paper will discuss design of experiments and the JMP tools applied to the solutions for both security systems.
Significant progress has been made over the last few years in understanding properties of matter subject to strong shocks and other extreme conditions. High-accuracy multi-Mbar experiments and first-principles theoretical studies together provide detailed insights into the physics and chemistry of high energy-density matter. While comprehensive advances have been made for pure elements like deuterium, helium, and carbon, progress has been slower for equally important, albeit more challenging, materials like molecular crystals, polymers, and foams. Hydrocarbon based polymer foams are common materials and in particular they are used in designing shock- and inertial confinement fusion experiments. Depending on their initial density, foams shock to relatively higher pressure and temperature compared to shocked dense polymers/plastics. As foams and polymers are shocked, they exhibit both structural and chemical transitions. We will present experimental and theoretical results for shocked polymers in the Mbar regime. By shock impact of magnetically launched flyer plates on poly(4-methyl-1-pentene) foams, we create multi-Mbar pressures in a dense plasma mixture of hydrogen, carbon, at temperatures of several eV. Concurrently with executing experiments, we analyze the system by multi-scale simulations, from density functional theory to continuum magneto-hydrodynamics simulations. In particular, density functional theory (DFT) molecular dynamics (MD) and classical MD simulations of the principal shock Hugoniot will be presented in detail for two hydrocarbon polymers: polyethylene (PE) and poly(4-methyl-1-pentene) (PMP).
The political dynamics associated with an election are typically a function of the interplay between political leaders and voters, as well as endogenous and exogenous factors that impact the perceptions and goals of the electorate. This paper describes an effort by Sandia National Laboratories to model the attitudes and behaviors of various political groups along with that population's primary influencers, such as government leaders. To accomplish this, Sandia National Laboratories is creating a hybrid system dynamics-cognitive model to simulate systems- and individual-level political dynamics in a hypothetical society. The model is based on well-established psychological theory, applied to both individuals and groups within the modeled society. Confidence management processes are being incorporated into the model design process to increase the utility of the tool and assess its performance. This project will enhance understanding of how political dynamics are determined in democratic society.
The Office of Nuclear Regulatory Research (RES) at the US Nuclear Regulatory Commission (USNRC) is sponsoring work in response to a Staff Requirements Memorandum (SRM) directing an effort to establish a single human reliability analysis (HRA) method for the agency or guidance for the use of multiple methods. As part of this effort an attempt to develop a comprehensive HRA qualitative approach is being pursued. This paper presents a draft of the method's middle layer, a part of the qualitative analysis phase that links failure mechanisms to performance shaping factors. Starting with a Crew Response Tree (CRT) that has identified human failure events, analysts identify potential failure mechanisms using the mid-layer model. The mid-layer model presented in this paper traces the identification of the failure mechanisms using the Information-Diagnosis/Decision-Action (IDA) model and cognitive models from the psychological literature. Each failure mechanism is grouped according to a phase of IDA. Under each phase of IDA, the cognitive models help identify the relevant performance shaping factors for the failure mechanism. The use of IDA and cognitive models can be traced through fault trees, which provide a detailed complement to the CRT.
A low-temperature upturn of the Coulomb drag resistivity {rho}{sub D} measured in undoped electron-hole bilayer devices, possibly manifesting from formation of a superfluid condensate or density modulated state, was recently observed. Here the effects of perpendicular and parallel magnetic fields on the drag upturn are examined. Measurements of {rho}{sub D} and drive layer resistivity {rho}{sub xx-e} as a function of temperature and magnetic field in two uEHBL devices are presented. In B{sub {perpendicular}}, the drag upturn was enhanced as the field increased up to roughly .2 T, beyond which oscillations in {rho}{sub D} and {rho}{sub xx-e}, reflecting Landau level formation, begin appearing. A small phase offset between those oscillations, which decreased at higher fields and temperatures, was also observed. In B{sub {parallel}}, the drag upturn magnitude diminished as the field increased. Above the upturn regime, both {rho}{sub D} and {rho}{sub xx-e} were enhanced by B{sub {parallel}}, the latter via decreased screening of the uniform background impurities.
Silicon is an ideal system for investigating single electron or isolated donor spins for quantum computation, due to long spin coherence times. Enhancement mode strained-silicon/silicon germanium (sSi/SiGe) devices would offer an as-yet untried path toward electron or electron/donor quantum dot systems. Thin, undoped SiGe dielectrics allow tight electrostatic confinement, as well as potential Lande g-factor engineered spin manipulation. In this talk we summarize recent progress toward sSi/SiGe enhancement mode devices on sSi on insulator, including characterization with X-ray diffraction and atomic force microscopy, as well as challenges faced and progress on integration of either top-down and bottom-up donor placement approaches in a sSi/SiGe enhancement mode structure.
The principal design drivers in the certification of wind turbine blades are ultimate strength, fatigue resistance, adequate tip-tower clearance, and buckling resistance. Buckling resistance is typically strongly correlated to both ultimate strength and fatigue resistance. A composite shell with spar caps forms the airfoil shape of a blade and reinforcing shear webs are placed inside the blade to stiffen the blade in the flap-wise direction. The spar caps are dimensioned and the shear webs are placed so as to add stiffness to unsupported panel regions and reduce their length. The panels are not the major flap-wise load carrying element of a blade; however, they must be designed carefully to avoid buckling while minimizing blade weight. Typically, buckling resistance is evaluated by consideration of the load-deflection behavior of a blade using finite element analysis (FEA) or full-scale static testing of blades under a simulated extreme loading condition. The focus of this paper is on the use of experimental modal analysis to measure localized resonances of the blade panels. It can be shown that the resonant behavior of these panels can also provide a means to evaluate buckling resistance by means of analytical or experimental modal analysis. Further, panel resonances have use in structural health monitoring by observing changes in modal parameters associated with panel resonances, and use in improving panel laminate model parameters by correlation with test data. In recent modal testing of wind turbine blades, a set of panel modes were measured. This paper will report on the findings of these tests and accompanying numerical and analytical modeling efforts aimed at investigating the potential uses of panel resonances for blade evaluation, health monitoring, and design.
When elastic-plastic materials, such as metals, are subjected to moderately high strain rates or dynamic loadings, the plastic stress wave trails behind the elastic wave because of its slower wave speed. Due to the inherent time-dependent nature of the plastic deformation, the elastic precursor generally loads the material to a metastable elastic state at a stres level that is higher than the static strength of the material. This metastable state gradually relaxes to the equilibrium state and the relaxation results in the so-called precursor decay. In a recent work by Asay et al. (J. Appl. Phys., 2009), the inelastic response of annealed and cold-rolled pure polycrystalline tantalum at intermediate strain rates ({approx} 106/sec) was experimentally characterized with ramp wave loading. It was found that the precursor of the annealed tantalum showed little decay over a propagation distance of 6 mm even though the peak precursor stress was well above the static strength of the mateiral. The precursor for the cold-rolled sample was more dispersive and did not exhibit the characteristics depicted by the annealed samples. In this study, a constitutive model based on the concept of dislocation motion and generation was developed to gain insights into this somewhat unusual precursor behavior, particularly for the annealed samples, and the possible underlying deformation mechanisms for tantalum. Despite its simplicity, the model worked quite well for both the annealed and cold-rolled materials. The tantalum studied here essentially exhibits strong rate sensitivity and this behavior is modeled through the low dislocation density and the strong stress dependence of the dislocation velocity. Both of these contributions may be related to the low mobility of the screw dislocations in bcc metals. This low mobility may result from its extended, three-dimensional core structure.
An overview of the study of the effects that electrical power and signal cables introduce on the dynamic response of precision structures is presented, along with a summary of lessons learned and most significant results. This was a three-year effort conducted at the Air Force Research Laboratory, Space Vehicles Directorate to discover a set of practical approaches for updating well defined dynamical models of cableless structures where knowledge of the cable type, position, and tie-down method are known. While cables can be found on many different types of structures, the focus of this effort was on precision, low-damping, and low-first modal frequency structures. Various obstacles, classified as tangents, rat holes, and dead ends, were encountered along the way. Rather than following a strictly technical flow, the paper presents the historical, experiential progression of the project. First, methods were developed to estimate cable properties. Problems were encountered because of the flexible, highly damped nature of cables. A simple beam was used as a test article to validate experimentally derived cable properties and to refine the assumptions regarding boundary conditions. A spacecraft bus-like panel with cables attached was designed, and finite element models were developed and validated through experiment. Various paths were investigated at each stage before a consistent test and analysis methodology was developed. These twists and turns are described.