Past experimental efforts to improve CZT crystals for gamma spectrometer applications have been focused on reducing micron-scale defects such as tellurium inclusions and precipitates. While these micron-scale defects are important, experiments have shown that the micron-scale variations in transport can be caused by the formation and aggregation of atomic-scale defects such as dislocations and point defect clusters. Moreover, dislocation cells have been found to act as nucleation sites that cause the formation of large precipitates. To better solve the uniformity problem of CZT, atomic-scale defects must be understood and controlled. To this end, we have begun to develop an atomistic model that can be used to reveal the effects of small-scale defects and to guide experiments for reducing both atomic- and micron-scale (tellurium inclusions and precipitates) defects. Our model will be based upon a bond order potential (BOP) to enable large-scale molecular dynamics simulations of material structures at a high-fidelity level that was not possible with alternative methods. To establish how BOP improves over existing approaches, we report here our recent work on the assessment of two representative literature CdTe interatomic potentials that are currently widely used: the Stillinger-Weber (SW) potential and the Tersoff-Rockett (TR) potential. Careful examinations of phases, defects, and surfaces of the CdTe system were performed. We began our study by using both potentials to evaluate the lattice constants and cohesive energies of various Cd, Te, and CdTe phases including dimer, trimer, chain, square, rhomboid, tetrahedron, diamond-cubic (dc), simple-cubic (sc), body-centered-cubic (bcc), face-centered cubic (fcc), hexagonal-close-packed (hcp), graphite-sheet, A8, zinc-blende (zb), wurtzite (wz), NaCl, CsCl, etc. We then compared the results with our calculations using the density functional theory (DFT) quantum mechanical method. We also evaluated the suitability of the two potentials to predict the surface reconstructions and surface energies, various defect configurations and defect energies (interstitials and voids), elastic constants, and melting temperatures of different phases. We found that both potentials predicted incorrect energy trends as compared with those predicted by the DFT method. Most seriously, both potentials predicted incorrect lowest energy phases. These studies clearly showed that the existing potentials are not sufficient for correctly predicting the charge transport properties of CdTe demonstrating the need for a new potential. We anticipate that our BOP method will overcome this problem and will accelerate the discovery of a synthesis approach to produce improved CZT crystals.
The development of more reliable scintillator materials can significantly advance the gamma-ray detection technology. Scintillator materials such as lanthanum halides (e.g., LaBr{sub 3}, CsBr{sub 3}), elpasolites (e.g., Cs{sub 2}LiLaBr{sub 6}, Cs{sub 2}NaLaBr{sub 6}, and Cs{sub 2}LiLaI{sub 6}), and alkali halides (e.g., CsI, NaI) are extremely brittle. The fracture of the materials is often a problem causing the failure of the devices. Lanthanum halides typically have a hexagonal crystal structure. These materials have highly anisotropic thermal and mechanical properties, and therefore they are likely to fracture under cyclic thermal and mechanical loading conditions. For example, fracture of lanthanum halides is known to occur in the field. Fracture during synthesis also complicates the growth of large lanthanum halide single crystals needed for sensitive radiation detection, and accounts for the high production cost of these materials. Elpasolites can have both cubic and non-cubic crystal structures depending on the constituent elements and composition of the compounds. This provides an opportunity to design cubic elpasolites with more isotropic properties and therefore improved mechanical performances. However, the design of an optimized cubic elpasolite crystal remains elusive because there is a tremendous number of possible elpasolites and the design criterion for cubic crystals is not clear. Alkali halides have cubic crystal structures. Consequently, large CsI and NaI crystals have been grown and used in devices. However, these materials suffer from an aging problem, i.e., the properties decay rapidly over time especially under harsh environment. Unfortunately, the fundamental mechanisms of this aging have not been understood and the path to improve the alkali halide-based scintillators is not developed. Clearly, improved scintillator materials can be achieved via strengthened/toughened lanthanum halides, optimized cubic elpasolites, or new alkali halide-based crystals that are more resistant to aging. Without a fundamental understanding of the atomic origins of the mechanical and the thermodynamic properties of materials, past experimental efforts to develop improved scintillator materials have been prolonged. Here we report our recent progress on the development of atomistic models that can be used to accelerate the discovery of new scintillator materials with improved properties. First, we have developed a novel embedded-ion method interatomic potential approach that analytically addresses the variable charge interactions between atoms in ionic compound material systems. Based on this potential, molecular dynamics simulations have been used to study the mechanical properties of LaBr3 including slip systems, dislocation core structures, and material strength. We have also developed an atomistic model that can already be used to predict crystal structures and to derive crystal stability rules for alkali halides. This model is under further development for prediction of crystal structures of elpasolites. These efforts will facilitate the design of better scintillator materials.
The ductile failure in metals has long been associated with void nucleation, growth and coalescence. Many micromechanics-based damage models were developed to study the effects of the voids sizes, shape and orientation to the nucleation, growth and coalescence of voids. However, the experimental methods to quantitatively validate these models were lacking. This paper is aimed to experimentally investigate at the microscale and nanoscale the effects of the shapes, sizes, orientation and density to the nucleation, growth and coalescence of voids and their relation to the ductility of the metal. In this work, notched tensile specimens with various radii were designed along different orientations. These specimens were tensile loaded up to different percentage of ultimate failure strain. The deformed specimens were then sectioned both along and perpendicular to the loading direction to microscopically study the voids size, shape and density. On the other hand, microtensile specimens were made out of these already deformed specimens. Using the advanced imaging capabilities of AFM and SEM combined with in-situ loading, the growth and coalescence of voids were in-situ studied at the microscale and nanoscale.
Deformation bands in high porosity sandstone are an important geological feature for geologists and petroleum engineers; however, their formation is not fully understood. Axisymmetric compression, the common test for this material, is not sufficient to fully evaluate localization criteria. This study seeks to investigate the influence of the second principal stress on the failure and the formation of deformation bands in Castlegate sandstone. Experimental results from tests run in the axisymmetric compression stress state, as well as a stress state between axisymmetric compression and pure shear will be presented. Samples are tested using a custom triaxial testing rig at Sandia National Laboratories capable of applying stresses up to 400 MPa. Acoustic emissions are used to locate deformation bands should they not be visible on the specimen exterior. It is suspected that the second invariant of stress has a strong contribution to the failure mode and band formation. These results could have significant bearing on petroleum extraction as well as carbon dioxide sequestration.
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.
Because digital image correlation (DIC) has become such an important and standard tool in the toolbox of experimental mechanicists, a complete uncertainty quantification of the method is needed. It should be remembered that each DIC setup and series of images will have a unique uncertainty based on the calibration quality and the image and speckle quality of the analyzed images. Any pretest work done with a calibrated DIC stereo-rig to quantify the errors using known shapes and translations, while useful, do not necessarily reveal the uncertainty of a later test. This is particularly true with high-speed applications where actual test images are often less than ideal. Work has previously been completed on the mathematical underpinnings of DIC uncertainty quantification and is already published, this paper will present corresponding experimental work used to check the validity of the uncertainty equations.
A mesoscale dimensional artifact based on silicon bulk micromachining fabrication has been developed and manufactured with the intention of evaluating the artifact both on a high precision coordinate measuring machine (CMM) and video-probe based measuring systems. This hybrid artifact has features that can be located by both a touch probe and a video probe system with a k=2 uncertainty of 0.4 {micro}m, more than twice as good as a glass reference artifact. We also present evidence that this uncertainty could be lowered to as little as 50 nm (k=2). While video-probe based systems are commonly used to inspect mesoscale mechanical components, a video-probe system's certified accuracy is generally much worse than its repeatability. To solve this problem, an artifact has been developed which can be calibrated using a commercially available high-accuracy tactile system and then be used to calibrate typical production vision-based measurement systems. This allows for error mapping to a higher degree of accuracy than is possible with a glass reference artifact. Details of the designed features and manufacturing process of the hybrid dimensional artifact are given and a comparison of the designed features to the measured features of the manufactured artifact is presented and discussed. Measurement results from vision and touch probe systems are compared and evaluated to determine the capability of the manufactured artifact to serve as a calibration tool for video-probe systems. An uncertainty analysis for calibration of the artifact using a CMM is presented.
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).
Forward radiation transport is the problem of calculating the radiation field given a description of the radiation source and transport medium. In contrast, inverse transport is the problem of inferring the configuration of the radiation source and transport medium from measurements of the radiation field. As such, the identification and characterization of special nuclear materials (SNM) is a problem of inverse radiation transport, and numerous techniques to solve this problem have been previously developed. The authors have developed a solver based on nonlinear regression applied to deterministic coupled neutron-photon transport calculations. The subject of this paper is the experimental validation of that solver. This paper describes a series of experiments conducted with a 4.5-kg sphere of alpha-phase, weapons-grade plutonium. The source was measured in six different configurations: bare, and reflected by high-density polyethylene (HDPE) spherical shells with total thicknesses of 1.27, 2.54, 3.81, 7.62, and 15.24 cm. Neutron and photon emissions from the source were measured using three instruments: a gross neutron counter, a portable neutron multiplicity counter, and a high-resolution gamma spectrometer. These measurements were used as input to the inverse radiation transport solver to characterize the solver's ability to correctly infer the configuration of the source from its measured signatures.
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.
We present Poblano v1.0, a Matlab toolbox for solving gradient-based unconstrained optimization problems. Poblano implements three optimization methods (nonlinear conjugate gradients, limited-memory BFGS, and truncated Newton) that require only first order derivative information. In this paper, we describe the Poblano methods, provide numerous examples on how to use Poblano, and present results of Poblano used in solving problems from a standard test collection of unconstrained optimization problems.
The difficulty of calculating the ambient properties of molecular crystals, such as the explosive PETN, has long hampered much needed computational investigations of these materials. One reason for the shortcomings is that the exchange-correlation functionals available for Density Functional Theory (DFT) based calculations do not correctly describe the weak intermolecular van der Waals' forces present in molecular crystals. However, this weak interaction also poses other challenges for the computational schemes used. We will discuss these issues in the context of calculations of lattice constants and structure of PETN with a number of different functionals, and also discuss if these limitations can be circumvented for studies at non-ambient conditions.
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.
Liquid foams are viscoelastic liquids, exhibiting a fast relaxation attributed to local bubble motions and a slow response due to structural evolution of the intrinsically unstable system. In this work, these processes are examined in unique organic foams that differ from the typically investigated aqueous systems in two major ways: the organic foams (1) posses a much higher continuous phase viscosity and (2) exhibit a coarsening response that involves coalescence of cells. The transient and dynamic relaxation responses of the organic foams are evaluated and discussed in relation to the response of aqueous foams. The change in the foam response with increasing gas fraction, from that of a Newtonian liquid to one that is strongly viscoelastic, is also presented. In addition, the temporal dependencies of the linear viscoelastic response are assessed in the context of the foam structural evolution. These foams and characterization techniques provide a basis for testing stabilization mechanisms in epoxy-based foams for encapsulation applications.
Alkali nitrate eutectic mixtures are finding application as industrial heat transfer fluids in concentrated solar power generation systems. An important property for such applications is the melting point, or phase coexistence temperature. We have computed melting points for lithium, sodium and potassium nitrate from molecular dynamics simulations using a recently developed method, which uses thermodynamic integration to compute the free energy difference between the solid and liquid phases. The computed melting point for NaNO3 was within 15K of its experimental value, while for LiNO3 and KNO3, the computed melting points were within 100K of the experimental values [4]. We are currently extending the approach to calculate melting temperatures for binary mixtures of lithium and sodium nitrate.
The annual program report provides detailed information about all aspects of the SNL/CA Pollution Prevention Program for a given calendar year. It functions as supporting documentation to the SNL/CA Environmental Management System Program Manual. The program report describes the activities undertaken during the past year, and activities planned in future years to implement the Pollution Prevention Program, one of six programs that supports environmental management at SNL/CA.
Development of silicon, enhancement mode nanostructures for solid-state quantum computing will be described. A primary motivation of this research is the recent unprecedented manipulation of single electron spins in GaAs quantum dots, which has been used to demonstrate a quantum bit. Long spin decoherence times are predicted possible in silicon qubits. This talk will focus on silicon enhancement mode quantum dot structures that emulate the GaAs lateral quantum dot qubit but use an enhancement mode field effect transistor (FET) structure. One critical concern for silicon quantum dots that use oxides as insulators in the FET structure is that defects in the metal oxide semiconductor (MOS) stack can produce both detrimental electrostatic and paramagnetic effects on the qubit. Understanding the implications of defects in the Si MOS system is also relevant for other qubit architectures that have nearby dielectric passivated surfaces. Stable, lithographically defined, single-period Coulomb-blockade and single-electron charge sensing in a quantum dot nanostructure using a MOS stack will be presented. A combination of characterization of defects, modeling and consideration of modified approaches that incorporate SiGe or donors provides guidance about the enhancement mode MOS approach for future qubits and quantum circuit micro-architecture.
The microscopic Polymer Reference Interaction Site Model theory has been applied to spherical and rodlike fillers dissolved in three types of chemically heterogeneous polymer melts: alternating AB copolymer, random AB copolymers, and an equimolar blend of two homopolymers. In each case, one monomer species adsorbs more strongly on the filler mimicking a specific attraction, while all inter-monomer potentials are hard core which precludes macrophase or microphase separation. Qualitative differences in the filler potential-of-mean force are predicted relative to the homopolymer case. The adsorbed bound layer for alternating copolymers exhibits a spatial moduluation or layering effect but is otherwise similar to that of the homopolymer system. Random copolymers and the polymer blend mediate a novel strong, long-range bridging interaction between fillers at moderate to high adsorption strengths. The bridging strength is a non-monotonic function of random copolymer composition, reflecting subtle competing enthalpic and entropic considerations.
The low-energy properties of the Anderson model for a single impurity coupled to two leads are studied using the GW approximation. We find that quantities such as the spectral function at zero temperature, the linear-response conductance as function of temperature or the differential conductance as function of bias voltage exhibit universal scaling behavior in the Kondo regime. We show how the form of the GW scaling functions relates to the form of the scaling functions obtained from the exact solution at equilibrium. We also compare the energy scale that goes inside the GW scaling functions with the exact Kondo temperature, for a broad range of the Coulomb interaction strength in the asymptotic regime. This analysis allows to clarify a presently suspended question in the literature, namely whether or not the GW solution captures the Kondo resonance.
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.
FRMAC was born out of circumstances 25 years ago when 17 federal agencies descended on the states with good intention during the Three-Mile Island nuclear power plant incident. At that time it quickly became evident that a better way was needed to support state and local governments in their time of emergency and recovery process. FRMAC's single voice of Federal support coordinates the multiple agencies that respond to a radiological event. Over the years, FRMAC has exercised, evaluated, and honed its ability to quickly respond to the needs of our communities. As the times have changed, FRMAC has expanded its focus from nuclear power plant incidents, to threats of a terrorist radiological dispersal device (RDD), to the unthinkable - an Improvised nuclear device (IND). And just as having the right tools are part of any trade, FRMAC's tool set has and is evolving to meet contemporary challenges - not just to improve the time it takes to collect data and assess the situation, but to provide a quality and comprehensive product that supports a stressed decision maker, responsible for the protection of the public. Innovations in the movement of data and information have changed our everyday lives. So too, FRMAC is capitalizing on industry innovations to improve the flow of information: from the early predictive models, to streamlining the process of getting data out of the field; to improving the time it takes to get assessed products in to the hands of the decision makers. FRMAC is focusing on the future through the digital age of electronic data processing. Public protective action and dose avoidance is the challenge.
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).
In many industrial processes, gaseous moisture is undesirable as it can lead to metal corrosion, polymer degradation, and other materials aging processes. However, generating and measuring precise moisture concentrations is challenging due to the need to cover a broad concentration range (parts-per-billion to percent) and the affinity of moisture to a wide range surfaces and materials. This document will discuss the techniques employed by the Mass Spectrometry Laboratory of the Materials Reliability Department at Sandia National Laboratories to generate and measure known gaseous moisture concentrations. This document highlights the use of a chilled mirror and primary standard humidity generator for the characterization of aluminum oxide moisture sensors. The data presented shows an excellent correlation in frost point measured between the two instruments, and thus provides an accurate and reliable platform for characterizing moisture sensors and performing other moisture related experiments.
The goal of z-pinch inertial fusion energy (IFE) is to extend the single-shot z-pinch inertial confinement fusion (ICF) results on Z to a repetitive-shot z-pinch power plant concept for the economical production of electricity. Z produces up to 1.8 MJ of x-rays at powers as high as 230 TW. Recent target experiments on Z have demonstrated capsule implosion convergence ratios of 14-21 with a double-pinch driven target, and DD neutron yields up to 8x10exp10 with a dynamic hohlraum target. For z-pinch IFE, a power plant concept is discussed that uses high-yield IFE targets (3 GJ) with a low rep-rate per chamber (0.1 Hz). The concept includes a repetitive driver at 0.1 Hz, a Recyclable Transmission Line (RTL) to connect the driver to the target, high-yield targets, and a thick-liquid wall chamber. Recent funding by a U.S. Congressional initiative for $4M for FY04 is supporting research on RTLs, repetitive pulsed power drivers, shock mitigation, full RTL cycle planned experiments, high-yield IFE targets, and z-pinch power plant technologies. Recent results of research in all of these areas are discussed, and a Road Map for Z-Pinch IFE is presented.
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.
The strain rate sensitivity of materials is measured through a combination of quasistatic, Hopkinson bar, and pressure-shear experiments. The pressure-shear technique has largely been limited to strain rates of order 1E6 1/s. Recent advances in laser and magnetically driven ramp loading have made it possible to achieve significantly higher rates, 1E5-1E8 1/s, under uniaxial strain compression. Strength in these experiments can be calculated by comparing the loading response to the hydrostatic (pressure-density) response of the material for the same density and temperature [Fowles, 1961]. This must be done accounting for the heating due to plastic work in the experiments. Experimental uniaxial strain data for aluminum for strain rates up to 1E8 1/s are examined and compared with existing data. The results are consistent with conventional views of the strain rate sensitivity of aluminum. However, when one considers the higher mean stress (pressure) present in the uniaxial strain experiments and, to a lesser extent, the pressure-shear experiments, one finds the material remains rate insensitive to about 1E7 1/s, two orders of magnitude higher than previously thought. Important caveats about determining strength in this manner will be discussed, and recommendations for future work will be made.
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.
This paper discusses implications and appropriate treatment of systematic uncertainty in experiments and modeling. Systematic uncertainty exists when experimental conditions, and/or measurement bias errors, and/or bias contributed by post-processing the data, are constant over the set of experiments but the particular values of the conditions and/or biases are unknown to within some specified uncertainty. Systematic uncertainties in experiments do not automatically show up in the output data, unlike random uncertainty which is revealed when multiple experiments are performed. Therefore, the output data must be properly 'conditioned' to reflect important sources of systematic uncertainty in the experiments. In industrial scale experiments the systematic uncertainty in experimental conditions (especially boundary conditions) is often large enough that the inference error on how the experimental system maps inputs to outputs is often quite substantial. Any such inference error and uncertainty thereof also has implications in model validation and calibration/conditioning; ignoring systematic uncertainty in experiments can lead to 'Type X' error in these procedures. Apart from any considerations of modeling and simulation, reporting of uncertainty associated with experimental results should include the effects of any significant systematic uncertainties in the experiments. This paper describes and illustrates the treatment of multivariate systematic uncertainties of interval and/or probabilistic natures, and combined cases. The paper also outlines a practical and versatile 'real-space' framework and methodology within which experimental and modeling uncertainties (correlated and uncorrelated, systematic and random, aleatory and epistemic) are treated to mitigate risk in model validation, calibration/conditioning, hierarchical modeling, and extrapolative prediction.
The goals of this project are to understand the fundamental principles that govern the formation and function of novel nanoscale and nanocomposite materials. Specific scientific issues being addressed include: design and synthesis of complex molecular precursors with controlled architectures, controlled synthesis of nanoclusters and nanoparticles, development of robust two or three-dimensionally ordered nanocomposite materials with integrated functionalities that can respond to internal or external stimuli through specific molecular interactions or phase transitions, fundamental understanding of molecular self-assembly mechanisms on multiple length scales, and fundamental understanding of transport, electronic, optical, magnetic, catalytic and photocatalytic properties derived from the nanoscale phenomena and unique surface and interfacial chemistry for DOE's energy mission.
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.
The increased demand for Liquefied Natural Gas (LNG) as a fuel source in the U.S. has prompted a study to improve our capability to predict cascading damage to LNG tankers from cryogenic spills and subsequent fire. To support this large modeling and simulation effort, a suite of experiments were conducted on two tanker steels, ABS Grade A steel and ABS Grade EH steel. A thorough and complete understanding of the mechanical behavior of the tanker steels was developed that was heretofore unavailable for the span of temperatures of interest encompassing cryogenic to fire temperatures. This was accomplished by conducting several types of experiments, including tension, notched tension and Charpy impact tests at fourteen temperatures over the range of -191 C to 800 C. Several custom fixtures and special techniques were developed for testing at the various temperatures. The experimental techniques developed and the resulting data will be presented, along with a complete description of the material behavior over the temperature span.
We develop a switched feedback controller that optimizes the rate of convergence of the state trajectories to the origin for a class of second order LTI systems. Specifically, we derive an algorithm which optimizes the rate of convergence by employing a controller that switches between symmetric gains. As a byproduct of our investigation, we find that, in general, the controllers which optimize the rate of convergence switch between two linear subsystems, one of which is unstable. The algorithm we investigate will design optimal switching laws for the specific case of second order LTI plants of relative degree two.