Publications

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Infrastructures are networks of dynamically interacting systems designed for the flow of information, energy, and materials. Under certain circumstances, disturbances from a targeted attack or natural disasters can cause cascading failures within and between infrastructures that result in significant service losses and long recovery times. Reliable interdependency models that can capture such multi-network cascading do not exist. The research reported here has extended Sandia's infrastructure modeling capabilities by: (1) addressing interdependencies among networks, (2) incorporating adaptive behavioral models into the network models, and (3) providing mechanisms for evaluating vulnerability to targeted attack and unforeseen disruptions. We have applied these capabilities to evaluate the robustness of various systems, and to identify factors that control the scale and duration of disruption. This capability lays the foundation for developing advanced system security solutions that encompass both external shocks and internal dynamics.

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Our overall intent is to develop improved prosthetic devices with the use of nerve interfaces through which transected nerves may grow, such that small groups of nerve fibers come into close contact with electrode sites, each of which is connected to electronics external to the interface. These interfaces must be physically structured to allow nerve fibers to grow through them, either by being porous or by including specific channels for the axons. They must be mechanically compatible with nerves such that they promote growth and do not harm the nervous system, and biocompatible to promote nerve fiber growth and to allow close integration with biological tissue. They must exhibit selective and structured conductivity to allow the connection of electrode sites with external circuitry, and electrical properties must be tuned to enable the transmission of neural signals. Finally, the interfaces must be capable of being physically connected to external circuitry, e.g. through attached wires. We have utilized electrospinning as a tool to create conductive, porous networks of non-woven biocompatible fibers in order to meet the materials requirements for the neural interface. The biocompatible fibers were based on the known biocompatible material poly(dimethyl siloxane) (PDMS) as well as a newer biomaterial developed in our laboratories, poly(butylene fumarate) (PBF). Both of the polymers cannot be electrospun using conventional electrospinning techniques due to their low glass transition temperatures, so in situ crosslinking methodologies were developed to facilitate micro- and nano-fiber formation during electrospinning. The conductivity of the electrospun fiber mats was controlled by controlling the loading with multi-walled carbon nanotubes (MWNTs). Fabrication, electrical and materials characterization will be discussed along with initial in vivo experimental results.

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Development of sophisticated tools capable of manipulating molecules at their own length scale enables new methods for chemical synthesis and detection. Although nanoscale devices have been developed to perform individual tasks, little work has been done on developing a truly scalable platform: a system that combines multiple components for sequential processing, as well as simultaneously processing and identifying the millions of potential species that may be present in a biological sample. The development of a scalable micro-nanofluidic device is limited in part by the ability to combine different materials (polymers, metals, semiconductors) onto a single chip, and the challenges with locally controlling the chemical, electrical, and mechanical properties within a micro or nanochannel. We have developed a unique construct known as a molecular gate: a multilayered polymer based device that combines microscale fluid channels with nanofluidic interconnects. Molecular gates have been demonstrated to selectively transport molecules between channels based on size or charge. In order to fully utilize these structures, we need to develop methods to actively control transport and identify species inside a nanopore. While previous work has been limited to creating electrical connections off-channel or metallizing the entire nanopore wall, we now have the ability to create multiple, separate conductive connections at the interior surface of a nanopore. These interior electrodes will be used for direct sensing of biological molecules, probing the electrical potential and charge distribution at the surface, and to actively turn on and off electrically driven transport of molecules through nanopores.

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This report describes in-depth analysis of photovoltaic (PV) output variability in a high-penetration residential PV installation in the Pal Town neighborhood of Ota City, Japan. Pal Town is a unique test bed of high-penetration PV deployment. A total of 553 homes (approximately 80% of the neighborhood) have grid-connected PV totaling over 2 MW, and all are on a common distribution line. Power output at each house and irradiance at several locations were measured once per second in 2006 and 2007. Analysis of the Ota City data allowed for detailed characterization of distributed PV output variability and a better understanding of how variability scales spatially and temporally. For a highly variable test day, extreme power ramp rates (defined as the 99^th percentile) were found to initially decrease with an increase in the number of houses at all timescales, but the reduction became negligible after a certain number of houses. Wavelet analysis resolved the variability reduction due to geographic diversity at various timescales, and the effect of geographic smoothing was found to be much more significant at shorter timescales.

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This investigation examined the use of nano-patterned structures on Silicon-on-Insulator (SOI) material to reduce the bulk material melting point (1414 °C). It has been found that sharp-tipped and other similar structures have a propensity to move to the lower energy states of spherical structures and as a result exhibit lower melting points than the bulk material. Such a reduction of the melting point would offer a number of interesting opportunities for bonding in microsystems packaging applications. Nano patterning process capabilities were developed to create the required structures for the investigation. One of the technical challenges of the project was understanding and creating the specialized conditions required to observe the melting and reshaping phenomena. Through systematic experimentation and review of the literature these conditions were determined and used to conduct phase change experiments. Melting temperatures as low as 1030 C were observed.

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Existing monochromatic X-ray backlighting diagnostics at 1.865 and 6.151 keV have been combined to create a two-color monochromatic X-ray backlighting diagnostic. The use of different photon energies can allow a much broader range of areal densities to be observed in a single experiment. Here, we apply the two-color backlighter to the study of instability growth on the outside edge of an initially solid copper rod target driven by a 100-ns rise-time current pulse with a peak value of 20 MA. The different opacity of Cu at these two photon energies allows a dynamic range of ∼1600x to be surveyed instead of ∼60x (assuming a useful transmission range of 5%-95%). © 2006 IEEE.

Magnetic implosions provide extremely intense soft X-ray radiation on the Z accelerator. Shock heating at stagnation provides temperatures that are capable of producing K-shell radiation from stainless steel plasma. Time-gated multicolor X-ray pinhole imaging is used to study stagnation and disruption in fast Z pinches. Magnetohydrodynamic instabilities are observed to grow, following peak X-ray power until the Z-pinch column disrupts well after the main power pulse. © 2006 IEEE.

The negative-polarity rod-pinch diode is being developed and tested on the RITS-6 accelerator to expand radiographic capabilities. High current densities at the tip of the rod anode generate a plasma which expands at a rate of 2-4 cm μs. Images of visible light captured with a high-speed intensified charge-coupled device camera show the development and expansion of the plasma. © 2006 IEEE.

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In this paper a simple effective-media analysis (including higher-order multipoles) is used to design a single-resonator, negative-index design based on a metal-core, dielectric-shell (MCDS) unit cell. In addition to comparing the performance of the MCDS design to other core-shell negative-index designs, performance trade-offs resulting from the relative positioning of the electric and magnetic modal resonances in the MCDS design are also discussed. © 2011 IEEE.

The ability to see what is happening during an experiment is often critical to human understanding. High and ultra-high speed cameras have for decades allowed scientists to see these extremely short time-scale events; starting with film cameras and now with digital versions of these cameras. The move to digital cameras has invited the use of computer analysis of the images for obtaining quantitative information well beyond the qualitative usefulness of merely being able to see the event. Digital image correlation (DIC) is one of these powerful and popular quantitative techniques, but by no means the only possible image analysis method. All of these analysis techniques ask more of the camera technology than simply providing images. They require highquality images that are amenable to analysis and do not introduce error sources that compromise the data. Possible error sources include image noise, image distortions, synchronization and spatial sampling issues. As a minimal starting point, the introduced errors must be well understood in order to put error bounds on the results. This is because in many experiments some result is better than no result; with the caveat that the error sources and the relative confidence of the data are understood. The concepts will be framed in relation to ongoing ultra-high speed work being done at Sandia. A call and challenge will be given to begin thinking in more detail about how to successfully turn these cameras into diagnostic instruments. © (2011) Trans tech publications Switzerland.

Bandstructure properties in wurtzite quantum wells can change appreciably with changing carrier density because of screening of quantumconfined Stark effect. An approach for incorporating these changes in an InGaN light-emitting-diode model is described. Bandstructure is computed for different carrier densities by solving Poisson and k·p equations in the envelop approximation. The information is used as input in a dynamical model for populations in momentum-resolved electron and hole states. Application of the approach is illustrated by modeling device internal quantum efficiency as a function of excitation. © 2011 Optical Society of America.

Mudstone pore networks are strong modifiers of sedimentary basin fluid dynamics and have a critical role in the distribution of hydrocarbons and containment of injected fluids. Using core samples from continental and marine mudstones, we investigate properties of pore types and networks from a variety of geologic environments, together with estimates of capillary beam- scanning electron microscopy, suggest seven dominant mudstone pore types distinguished by geometry and connectivity. A dominant planar pore type occurs in all investigated mudstones and generally has high coordination numbers (i.e., number of neighboring connected pores). Connected networks of pores of this type contribute to high mercury capillary pressures due to small pore throats at the junctions of connected pores and likely control most matrix transport in these mudstones. Other pore types are related to authigenic (e.g., replacement or pore-lining precipitation) clay minerals and pyrite nodules; pores in clay packets adjacent to larger, more competent clastic grains; pores in organic phases; and stylolitic and microfracture-related pores. Pores within regions of authigenic clay minerals often form small isolated networks (<3 μm). Pores in stringers of organic phases occur as tubular pores or slit- and/or sheet-like pores. These form short, connected lengths in 3D reconstructions, but appear to form networks no larger than a few microns in size. Sealing efficiency of the studied mudstones increases with greater distal depositional environments and greater maximum depth of burial. © 2011 Geological Society of America.

The electronic structure and optical properties of Ge-core/Si-shell nanocrystal or quantum dot (QD) are investigated using the atomistic tight binding method as implemented in NEMO3D. The thermionic lifetime that governs the hole leakage mechanism in the Ge/Si QD based laser, as a function of the Ge core size and strain, is also calculated by capturing the bound and extended eigenstates, well below the band edges. We also analyzed the effect of core size and strain on optical properties such as transition energies and transition rates between electron and hole states. Finally, a quantitative and qualitative analysis of the leakage current due to the hole leakage through the Ge-core/Si-shell QD laser, at different temperatures and Ge core sizes, is presented. © 2011 SPIE.

Self-assembled monolayers (SAMs) enable significant changes in the surface energy and/or specific interactions of surfaces, which are desirable for microelectromechanical systems (MEMS), superhydrophobic coatings, sensors, and other applications. However, SAMs often exhibit poor durability and rapid degradation upon mechanical, thermal, or moisture exposure. The chemical and orientational changes in SAMs due to mechanical and thermal degradation were investigated using near-edge X-ray absorption fine structure (NEXAFS) and the water contact angle. SAMs were based on unfluorinated or fluorinated linear hydrocarbons that form highly oriented and densely packed structures on silicon substrates. Complex chemical and orientational changes were observed via NEXAFS following degradation. Under heating in a dry, oxygen-rich environment, unfluorinated SAMs tended to cleave at C-C bonds on the main chain; below 250 °C, CH3 groups were sequentially cleaved toward the surface, whereas above 250 °C, remaining hydrocarbon groups were converted to a graphitic coating dominated by C=C bonds. Under similar conditions, fluorinated SAMs began their chemical degradation at 350 °C and above, although the orientation decreased steadily from 150 to 300 °C; at and above 350 °C, the preferential removal of F occurred and the SAM was slowly converted to a graphitic layer. By contrast, under vacuum the fluorinated molecules were very thermally stable, showing good stability up to 550 °C; when degradation occurred, entire molecules were removed. Mechanical degradation followed two routes; both unfluorinated and fluorinated SAMs that were mechanically rubbed with smooth surfaces exhibited severe chemical degradation of the molecules, leading to an amorphous and poorly defined layer with C=C, C-C, C-H, and C-F bonds. Unfluorinated and fluorinated surfaces that were mechanically rubbed in the presence of free silicon particulates showed the rapid and complete destruction of both the molecular orientation and the protective SAM layer, even for short exposure periods. The resulting NEXAFS spectra were very similar to those produced by heating to 550 °C, suggesting that the friction created by granular particles may lead to extreme local heating. © 2011 American Chemical Society.

Recently, there has been much interest in using radiometric identification (also known as wireless fingerprinting) for the purposes of authentication. Previous work has shown that using radiometric identification can discriminate among devices with a high degree of accuracy when simultaneously using multiple radiometric characteristics. Additionally, researchers have noted the potential for wireless fingerprinting to be used for more devious purposes, specifically that of privacy invasion or compromise. In fact, any such radiometric characteristic that is useful for authentication is useful for privacy compromise. To date, there has not been any proposal of how to mitigate such privacy loss for many of these radiometric characteristics, and specifically no such proposal for how to mitigate such privacy loss in a low-cost manner. In this paper, we investigate some limits of an attacker's ability to compromise privacy, specifically an attacker that uses a transmitter's carrier frequency. We propose low-cost mechanisms for mitigating privacy loss for various radiometric characteristics. In our development and evaluation, we specifically consider a vehicular network (VANET) environment. We consider this environment in particular because VANETs will have the potential to leak significant, longterm information that could be used to compromise drivers' personal information such as home address, work address, and the locations of any businesses the driver frequents. While tracking a vehicle using visually observable information (e.g., license plates) to obtain personal information is possible, such means require line-of-sight, whereas radiometric identification would not. Finally, we evaluate one of our proposed mechanisms via simulation. Specifically, we evaluate our carrier frequency switching mechanism, comparing it to the theory we develop, and we show the precision with which vehicles will need to switch their physical layer identities given our parameterization for VANETs. © 2011 ACM.

Moving-boundary algorithms for the Direct Simulation Monte Carlo (DSMC) method are investigated for a microbeam that moves toward and away from a parallel substrate. The simpler but analogous one-dimensional situation of a piston moving between two parallel walls is investigated using two moving-boundary algorithms. In the first, molecules are reflected rigorously from the moving piston by performing the reflections in the piston frame of reference. In the second, molecules are reflected approximately from the moving piston by moving the piston and subsequently moving all molecules and reflecting them from the moving piston at its new or old position. © 2011 American Institute of Physics.

Ion Beam Induced Charge (IBIC) is the basic mechanism of the operation of semiconductor detectors and it can lead to Single Event Effects (SEEs) in microelectronic devices. To be able to predict SEEs in ICs and detector responses one needs to be able to simulate the radiation-induced current as the function of time on the electrodes of the devices and detectors. There are analytical models, which work for very simple detector configurations, but fail for anything more complex. Technology Computer Aided Design (TCAD) programs can simulate this process in microelectronic devices, but these TCAD codes costs hundreds of thousands of dollars and they require huge computing resources. In addition, in certain cases they fail to predict the correct behavior. Here a simulation model based on the Gunn theorem was developed and used with the COMSOL Multiphysics framework, version 3.5. In the model, the induced current can be calculated both directly and in certain cases using the powerful adjoint method. A brief description of the model will be given in the paper with examples for detectors and microelectronic devices using both the direct and the adjoint method.

The ion photon emission microscope (IPEM) is a technique developed at Sandia National Laboratories (SNL) to study radiation effects in integrated circuits with high energy, heavy ions, such as those produced by the 88" cyclotron at Lawrence Berkeley National Laboratory (LBNL). In this method, an ion-luminescent film is used to produce photons from the point of ion impact. The photons emitted due to an ion impact are imaged on a position-sensitive detector to determine the location of a single event effect (SEE). Due to stringent resolution, intensity, wavelength, decay time, and radiation tolerance demands, an engineered material with very specific properties is required to act as the luminescent film. The requirements for this material are extensive. It must produce a high enough induced luminescent intensity so at least one photon is detected per ion hit. The emission wavelength must match the sensitivity of the detector used, and the luminescent decay time must be short enough to limit accidental coincidences. In addition, the material must be easy to handle and its luminescent properties must be tolerant to radiation damage. Materials studied for this application include plastic scintillators, GaN and GaN/InGaN quantum well structures, and lanthanide-activated ceramic phosphors. Results from characterization studies on these materials will be presented; including photoluminescence, cathodoluminescence, ion beam induced luminescence, luminescent decay times, and radiation damage. Results indicate that the ceramic phosphors are currently proving to be the ideal material for IPEM investigations.

The next generation of compact tandem-type DD or DT neutron generators requires a robust electron stripper with high charge exchange efficiency. In this study, stripping foils of various types were tested, and the H- to H+ conversion efficiency, endurance to the heat load, and durability were investigated in terms of suitability in the tandem-type neutron generator. In the experiments, a H- beam was accelerated to about 180 keV, passes through a stripping foil, and produces a mixed beam of H -, H0, and H+. These ions were separated by an electric field, and detected by a movable Faraday cup to determine the conversion efficiency. The experimental results using thin foils of diamond-like carbon, gold, and carbon nano-tubes revealed issues on the robustness. As a new concept, a H- beam was injected onto a metal surface with an oblique angle, and reflected H+ ions are detected. It was found that the conversion efficiency, H+ fraction in the reflected particles, depends on the surface condition, with the maximum value of about 90%.© 2011 American Institute of Physics.

Over the past 2 decades, the U.S. nuclear power plant (NPP) fire protection community and overseas has been transitioning toward risk-informed and performance-based (RI/PB) practice in design, operation and regulation. To make more realistic decisions for risk-informed regulation, fire probabilistic risk analysis (PRA) methods needed further development. To address this need, in 2001, the U.S. Nuclear Regulatory Commission's (NRCs) Office of Nuclear Regulatory Research (RES) and the Electric Power Research Institute (EPRI) collaborated under a joint Memorandum of Understanding (MOU) to develop NUREG/CR-6850 (EPRI 101989), "EPRI/NRC-RES Fire PRA Methodology for Nuclear Power Facilities," a state-of-art fire PRA methodology. The fire human reliability analysis (HRA) guidance provided in NUREG/CR-6850 included: (1) a process for identification and inclusion of the human failure events (HFEs), (2) a methodology for assigning quantitative screening values to these HFEs, and (3) initial considerations of performance shaping factors (PSFs) and related fire effects that might need to be addressed in developing best-estimate human error probabilities (HEPs). However, NUREG/CR-6850 did not identify or produce a methodology to develop these best-estimate HEPs given the PSFs and the fire-related effects. In 2007, EPRI and RES embarked upon another cooperative project - building on existing HRA methods - to develop explicit guidance for estimating HEPs for human error events under fire-generated conditions. This collaborative project produced draft NUREG-1921, "EPRI/NRC-RES Fire Human Reliability Analysis Guidelines." The guidance presented in this report is intended to be both an improvement upon and an expansion of the initial guidance provided in NUREG/CR-6850. This paper will summarize the fire HRA guidance developed through this collaborative project, which addresses the range of fire procedures used in existing plants, the range of strategies for main control room (MCR) abandonment, and the potential impact of fire-induced electrical spurious actuation effects on crew performance. This guidance presents a three tiered, progressive approach for fire HRA quantification. The quantification approaches include: a screening approach per NUREG/CR-6850 guidance, a scoping approach, and detailed quantification using either EPRI's Cause-Based Decision Tree (CBDT) and Human cognitive Reliability/Operator Reliability Experiment (HCR/ORE) or NRC's A Technique for Human Event ANAlysis (ATHEANA) approach with modifications to account for fire effects. The newly developed scoping approach is intended to be less resource intensive than a detailed HRA, while providing less conservative HEPs than rough screening. The expectation is that the majority of the actions can be quantified using the scoping approach, thus detailed HRA will only be used for the more complex actions that do not meet the criteria for the scoping approach. It is anticipated that this guidance will be used by the industry as part of transition to the risk-informed, performance-based fire protection rule, 10 CFR 50.48c, that endorsed National Fire Protection Association (NFPA) 805, "Performance-Based Standard for Fire Protection for Light Water Reactor Electric Generating Plants" and possibly in response to other regulatory issues such as multiple spurious operation (MSO) and operator manual actions (OMAs). As the methodology is applied at a wide variety of NPPs, the guidance may benefit from future improvements to better support industry wide issues being addressed by fire PRAs.

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Orthogonalization consumes much of the run time of many iterative methods for solving sparse linear systems and eigenvalue problems. Commonly used algorithms, such as variants of Gram-Schmidt or Householder QR, have performance dominated by communication. Here, "communication" includes both data movement between the CPU and memory, and messages between processors in parallel. Our Tall Skinny QR (TSQR) family of algorithms requires asymptotically fewer messages between processors and data movement between CPU and memory than typical orthogonalization methods, yet achieves the same accuracy as Householder QR factorization. Furthermore, in block orthogonalizations, TSQR is faster and more accurate than existing approaches for orthogonalizing the vectors within each block ("normalization"). TSQR's rank-revealing capability also makes it useful for detecting deflation in block iterative methods, for which existing approaches sacrifice performance, accuracy, or both. We have implemented a version of TSQR that exploits both distributed-memory and shared-memory parallelism, and supports real and complex arithmetic. Our implementation is optimized for the case of orthogonalizing a small number (5 - 20) of very long vectors. The shared-memory parallel component uses Intel's Threading Building Blocks, though its modular design supports other shared-memory programming models as well, including computation on the GPU. Our implementation achieves speedups of 2 times or more over competing orthogonalizations. It is available now in the development branch of the Trilinos software package, and will be included in the 10.8 release. © 2011 IEEE.

Neutron multiplicity measurements are a useful technique for the characterization of special nuclear material. This technique relies on the detection of correlated neutrons from fission events. As correlated events are detected it is possible to determine the neutron multiplicity distribution for the sample. This distribution is useful for identifying the material and estimating the mass. This work focuses on the ability of the Monte Carlo code MCNP-PoliMi to simulate measured distributions. The experiment used as the basis of comparison consisted of a 4.5 kg plutonium metal sphere surrounded by up to 6 in. of polyethylene. A bank of 15 3He detectors was used to detect the correlated neutron events. MCNP-PoliMi was used to simulate the particle transport and a post-processing algorithm was developed to apply detector deadtime effects and to determine the neutron multiplicity distributions. These simulated distributions were then compared to the measured results. The simulation provided an adequate estimation of the measured data. However, we observed a systematic over-prediction in both the mean and the variance of the measured distribution. © 2011 Elsevier B.V.

Dissimilar metal bonds between CuCrZr and 316L stainless steel were prepared using two different solid state joining techniques. In the first instance, hot isostatic pressing, a high temperature diffusion bonding process was used to join the copper alloy to the stainless steel substrate at temperatures near 1000 °C. In the second instance, explosion bonding at ambient temperature was employed. These two techniques both yielded mechanically robust joints, where the strength of the interface exceeded that of the copper alloy, the weaker of the two substrates. However, the two bonding techniques produced near-joint microstructures that were very different. The microstructure and mechanical performance of CuCrZr/316L stainless steel joints prepared via both techniques are compared. Microstructural analysis of the joints included scanning electron microscopy, electron microprobe analysis and Auger spectroscopy techniques. The bulk mechanical properties of the substrate alloys were very different as well and are described. Particular emphasis is placed on the residual mechanical properties of the CuCrZr after thermal processing that simulate beryllium tile bonding since once the Be tiles are in place, the copper alloy cannot be solutionized and age-hardened to return it to full strength. © 2010 Elsevier B.V. All rights reserved.

Antineutrino detection using inverse beta-decay conversion has demonstrated capability to measure nuclear reactor power and fissile material content for nuclear safeguards. Current efforts focus on aboveground deployment scenarios, for which a successful background rejection strategy will be needed to measure the anticipated antineutrino event rates. In this paper, we report on initial studies to quantify the intrinsic capture efficiency and particle identification capabilities of a new scintillation-based segmented design that uses layers of ZnS:Ag/6LiF to capture and identify neutrons created in the inverse beta-decay reaction. Laboratory efficiency measurements are consistent with MCNP5 calculations, estimating 6Li neutron conversion efficiency above 50% for practical full-scale detector configurations. © 2010 Elsevier B.V.

Continuous jets of non-Newtonian fluids impinging on a fluid surface exhibit instabilities from jet buckling and coiling at low Reynolds numbers to delayed die swell, mounding, and air entrainment at higher Reynolds numbers. Filling containers with complex fluids is an important process for many industries, where the need for high throughput requires operating at high Reynolds numbers. In this regime, air entrainment can produce a visually unappealing product, causing a major quality control issue. Just prior to the onset of air entrainment, however, there exists an ideal filling regime which we term " planar filling," as it is characterized by a relatively flat free surface that maintains its shape over time. In this paper, we create a steady-state, 2-D axisymmetric finite element model to study the transition from planar filling to the onset of air entrainment in a container filling process with generalized-Newtonian fluids. We use this model to explore the operating window for Newtonian and shear-thinning (or, more generally, deformation-rate-thinning) fluids, demonstrating that the flow behavior is characterized by a balance between inertial, viscous, and gravitational forces, as characterized by the Reynolds and Froude numbers. A scaling analysis suggests that the relevant parameters for calculating these dimensionless numbers are located where the jet impacts the liquid surface, and simulations show that the transition from planar filling to air entrainment often occurs when Re~O(10). We found that the bottom and side surfaces of the container drastically influence this transition to entrainment, stabilizing the flow. © 2011 Elsevier B.V.

Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.

The purpose of this report is to develop a project management plan for maintaining and monitoring liquid radioactive waste tanks at Iraq's Al-Tuwaitha Nuclear Research Center. Based on information from several sources, the Al-Tuwaitha site has approximately 30 waste tanks that contain varying amounts of liquid or sludge radioactive waste. All of the tanks have been non-operational for over 20 years and most have limited characterization. The program plan embodied in this document provides guidance on conducting radiological surveys, posting radiation control areas and controlling access, performing tank hazard assessments to remove debris and gain access, and conducting routine tank inspections. This program plan provides general advice on how to sample and characterize tank contents, and how to prioritize tanks for soil sampling and borehole monitoring.

Pressure-shear experiments were performed on granular tungsten carbide and sand using a newly-refurbished slotted barrel gun. The sample is a thin layer of the granular material sandwiched between driver and anvil plates that remain elastic. Because of the obliquity, impact generates both a longitudinal wave, which compresses the sample, and a shear wave that probes the strength of the sample. Laser velocity interferometry is employed to measure the velocity history of the free surface of the anvil. Since the driver and anvil remain elastic, analysis of the results is, in principal, straightforward. Experiments were performed at pressures up to nearly 2 GPa using titanium plates and at higher pressure using zirconium plates. Those done with the titanium plates produced values of shear stress of 0.1-0.2 GPa, with the value increasing with pressure. On the other hand, those experiments conducted with zirconia anvils display results that may be related to slipping at an interface and shear stresses mostly at 0.1 GPa or less. Recovered samples display much greater particle fracture than is observed in planar loading, suggesting that shearing is a very effective mechanism for comminution of the grains.

A reference design and operational procedures for the disposal of high-level radioactive waste in deep boreholes have been developed and documented. The design and operations are feasible with currently available technology and meet existing safety and anticipated regulatory requirements. Objectives of the reference design include providing a baseline for more detailed technical analyses of system performance and serving as a basis for comparing design alternatives. Numerous factors suggest that deep borehole disposal of high-level radioactive waste is inherently safe. Several lines of evidence indicate that groundwater at depths of several kilometers in continental crystalline basement rocks has long residence times and low velocity. High salinity fluids have limited potential for vertical flow because of density stratification and prevent colloidal transport of radionuclides. Geochemically reducing conditions in the deep subsurface limit the solubility and enhance the retardation of key radionuclides. A non-technical advantage that the deep borehole concept may offer over a repository concept is that of facilitating incremental construction and loading at multiple perhaps regional locations. The disposal borehole would be drilled to a depth of 5,000 m using a telescoping design and would be logged and tested prior to waste emplacement. Waste canisters would be constructed of carbon steel, sealed by welds, and connected into canister strings with high-strength connections. Waste canister strings of about 200 m length would be emplaced in the lower 2,000 m of the fully cased borehole and be separated by bridge and cement plugs. Sealing of the upper part of the borehole would be done with a series of compacted bentonite seals, cement plugs, cement seals, cement plus crushed rock backfill, and bridge plugs. Elements of the reference design meet technical requirements defined in the study. Testing and operational safety assurance requirements are also defined. Overall, the results of the reference design development and the cost analysis support the technical feasibility of the deep borehole disposal concept for high-level radioactive waste.

Planar shock experiments were conducted on granular tungsten carbide (WC) and tantalum oxide (Ta{sub 2}O{sub 5}) using the Z machine and a 2-stage gas gun. Additional shock experiments were also conducted on a nearly fully dense form of Ta{sub 2}O{sub 5}. The experiments on WC yield some of the highest pressure results for granular materials obtained to date. Because of the high distention of Ta{sub 2}O{sub 5}, the pressures obtained were significantly lower, but the very high temperatures generated led to large contributions of thermal energy to the material response. These experiments demonstrate that the Z machine can be used to obtain accurate shock data on granular materials. The data on Ta{sub 2}O{sub 5} were utilized in making improvements to the P-{lambda} model for high pressures; the model is found to capture the results not only of the Z and gas gun experiments but also those from laser experiments on low density aerogels. The results are also used to illustrate an approach for generating an equation of state using only the limited data coming from nanoindentation. Although the EOS generated in this manner is rather simplistic, for this material it gives reasonably good results.

We investigate Bayesian techniques that can be used to reconstruct field variables from partial observations. In particular, we target fields that exhibit spatial structures with a large spectrum of lengthscales. Contemporary methods typically describe the field on a grid and estimate structures which can be resolved by it. In contrast, we address the reconstruction of grid-resolved structures as well as estimation of statistical summaries of subgrid structures, which are smaller than the grid resolution. We perform this in two different ways (a) via a physical (phenomenological), parameterized subgrid model that summarizes the impact of the unresolved scales at the coarse level and (b) via multiscale finite elements, where specially designed prolongation and restriction operators establish the interscale link between the same problem defined on a coarse and fine mesh. The estimation problem is posed as a Bayesian inverse problem. Dimensionality reduction is performed by projecting the field to be inferred on a suitable orthogonal basis set, viz. the Karhunen-Loeve expansion of a multiGaussian. We first demonstrate our techniques on the reconstruction of a binary medium consisting of a matrix with embedded inclusions, which are too small to be grid-resolved. The reconstruction is performed using an adaptive Markov chain Monte Carlo method. We find that the posterior distributions of the inferred parameters are approximately Gaussian. We exploit this finding to reconstruct a permeability field with long, but narrow embedded fractures (which are too fine to be grid-resolved) using scalable ensemble Kalman filters; this also allows us to address larger grids. Ensemble Kalman filtering is then used to estimate the values of hydraulic conductivity and specific yield in a model of the High Plains Aquifer in Kansas. Strong conditioning of the spatial structure of the parameters and the non-linear aspects of the water table aquifer create difficulty for the ensemble Kalman filter. We conclude with a demonstration of the use of multiscale stochastic finite elements to reconstruct permeability fields. This method, though computationally intensive, is general and can be used for multiscale inference in cases where a subgrid model cannot be constructed.

Molecular dynamics simulation (MD) is an invaluable tool for studying problems sensitive to atomscale physics such as structural transitions, discontinuous interfaces, non-equilibrium dynamics, and elastic-plastic deformation. In order to apply this method to modeling of ramp-compression experiments, several challenges must be overcome: accuracy of interatomic potentials, length- and time-scales, and extraction of continuum quantities. We have completed a 3 year LDRD project with the goal of developing molecular dynamics simulation capabilities for modeling the response of materials to ramp compression. The techniques we have developed fall in to three categories (i) molecular dynamics methods (ii) interatomic potentials (iii) calculation of continuum variables. Highlights include the development of an accurate interatomic potential describing shock-melting of Beryllium, a scaling technique for modeling slow ramp compression experiments using fast ramp MD simulations, and a technique for extracting plastic strain from MD simulations. All of these methods have been implemented in Sandia's LAMMPS MD code, ensuring their widespread availability to dynamic materials research at Sandia and elsewhere.

Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

The overarching goal of this Truman LDRD project was to explore mechanisms of thermal transport at interfaces of nanomaterials, specifically linking the thermal conductivity and thermal boundary conductance to the structures and geometries of interfaces and boundaries. Deposition, fabrication, and post possessing procedures of nanocomposites and devices can give rise to interatomic mixing around interfaces of materials leading to stresses and imperfections that could affect heat transfer. An understanding of the physics of energy carrier scattering processes and their response to interfacial disorder will elucidate the potentials of applying these novel materials to next-generation high powered nanodevices and energy conversion applications. An additional goal of this project was to use the knowledge gained from linking interfacial structure to thermal transport in order to develop avenues to control, or 'tune' the thermal transport in nanosystems.

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The Method of Nearby Problems (MNP), a form of defect correction, is examined as a method for generating exact solutions to partial differential equations and as a discretization error estimator. For generating exact solutions, four-dimensional spline fitting procedures were developed and implemented into a MATLAB code for generating spline fits on structured domains with arbitrary levels of continuity between spline zones. For discretization error estimation, MNP/defect correction only requires a single additional numerical solution on the same grid (as compared to Richardson extrapolation which requires additional numerical solutions on systematically-refined grids). When used for error estimation, it was found that continuity between spline zones was not required. A number of cases were examined including 1D and 2D Burgers equation, the 2D compressible Euler equations, and the 2D incompressible Navier-Stokes equations. The discretization error estimation results compared favorably to Richardson extrapolation and had the advantage of only requiring a single grid to be generated.

Network measurement is a discipline that provides the techniques to collect data that are fundamental to many branches of computer science. While many capturing tools and comparisons have made available in the literature and elsewhere, the impact of these packet capturing tools on existing processes have not been thoroughly studied. While not a concern for collection methods in which dedicated servers are used, many usage scenarios of packet capturing now requires the packet capturing tool to run concurrently with operational processes. In this work we perform experimental evaluations of the performance impact that packet capturing process have on web-based services; in particular, we observe the impact on web servers. We find that packet capturing processes indeed impact the performance of web servers, but on a multi-core system the impact varies depending on whether the packet capturing and web hosting processes are co-located or not. In addition, the architecture and behavior of the web server and process scheduling is coupled with the behavior of the packet capturing process, which in turn also affect the web server's performance.

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Nuclear fuel reprocessing plants contain a wealth of plant monitoring data including material measurements, process monitoring, administrative procedures, and physical protection elements. Future facilities are moving in the direction of highly-integrated plant monitoring systems that make efficient use of the plant data to improve monitoring and reduce costs. The Separations and Safeguards Performance Model (SSPM) is an analysis tool that is used for modeling advanced monitoring systems and to determine system response under diversion scenarios. This report both describes the architecture for such a future monitoring system and present results under various diversion scenarios. Improvements made in the past year include the development of statistical tests for detecting material loss, the integration of material balance alarms to improve physical protection, and the integration of administrative procedures. The SSPM has been used to demonstrate how advanced instrumentation (as developed in the Material Protection, Accounting, and Control Technologies campaign) can benefit the overall safeguards system as well as how all instrumentation is tied into the physical protection system. This concept has the potential to greatly improve the probability of detection for both abrupt and protracted diversion of nuclear material.

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In this project, we developed a confined cooperative self-assembly process to synthesize one-dimensional (1D) j-aggregates including nanowires and nanorods with controlled diameters and aspect ratios. The facile and versatile aqueous solution process assimilates photo-active macrocyclic building blocks inside surfactant micelles, forming stable single-crystalline high surface area nanoporous frameworks with well-defined external morphology defined by the building block packing. Characterizations using TEM, SEM, XRD, N{sub 2} and NO sorption isotherms, TGA, UV-vis spectroscopy, and fluorescence imaging and spectroscopy indicate that the j-aggregate nanostructures are monodisperse and may further assemble into hierarchical arrays with multi-modal functional pores. The nanostructures exhibit enhanced and collective optical properties over the individual chromophores. This project was a small footprint research effort which, nonetheless, produced significant progress towards both the stated goal as well as unanticipated research directions.

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Thermal detection has made extensive progress in the last 40 years, however, the speed and detectivity can still be improved. The advancement of silicon photonic microring resonators has made them intriguing for detection devices due to their small size and high quality factors. Implementing silicon photonic microring or microdisk resonators as a means of a thermal detector gives rise to higher speed and detectivity, as well as lower noise compared to conventional devices with electrical readouts. This LDRD effort explored the design and measurements of silicon photonic microdisk resonators used for thermal detection. The characteristic values, consisting of the thermal time constant ({tau} {approx} 2 ms) and noise equivalent power were measured and found to surpass the performance of the best microbolometers. Furthermore the detectivity was found to be D{sub {lambda}} = 2.47 x 10{sup 8} cm {center_dot} {radical}Hz/W at 10.6 {mu}m which is comparable to commercial detectors. Subsequent design modifications should increase the detectivity by another order of magnitude. Thermal detection in the terahertz (THz) remains underdeveloped, opening a door for new innovative technologies such as metamaterial enhanced detectors. This project also explored the use of metamaterials in conjunction with a cantilever design for detection in the THz region and demonstrated the use of metamaterials as custom thin film absorbers for thermal detection. While much work remains to integrate these technologies into a unified platform, the early stages of research show promising futures for use in thermal detection.

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This report describes the laboratory directed research and development work to model relevant areas of the brain that associate multi-modal information for long-term storage for the purpose of creating a more effective, and more automated, association mechanism to support rapid decision making. Using the biology and functionality of the hippocampus as an analogy or inspiration, we have developed an artificial neural network architecture to associate k-tuples (paired associates) of multimodal input records. The architecture is composed of coupled unimodal self-organizing neural modules that learn generalizations of unimodal components of the input record. Cross modal associations, stored as a higher-order tensor, are learned incrementally as these generalizations form. Graph algorithms are then applied to the tensor to extract multi-modal association networks formed during learning. Doing so yields a novel approach to data mining for knowledge discovery. This report describes the neurobiological inspiration, architecture, and operational characteristics of our model, and also provides a real world terrorist network example to illustrate the model's functionality.

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