The United States is now re-assessing its nuclear waste disposal policy and re-evaluating the option of moving away from the current once-through open fuel cycle to a closed fuel cycle. In a closed fuel cycle, used fuels will be reprocessed and useful components such as uranium or transuranics will be recovered for reuse. During this process, a variety of waste streams will be generated. Immobilizing these waste streams into appropriate waste forms for either interim storage or long-term disposal is technically challenging. Highly volatile or soluble radionuclides such as iodine ({sup 129}I) and technetium ({sup 99}Tc) are particularly problematic, because both have long half-lives and can exist as gaseous or anionic species that are highly soluble and poorly sorbed by natural materials. Under the support of Sandia National Laboratories (SNL) Laboratory-Directed Research & Development (LDRD), we have developed a suite of inorganic nanocomposite materials (SNL-NCP) that can effectively entrap various radionuclides, especially for {sup 129}I and {sup 99}Tc. In particular, these materials have high sorption capabilities for iodine gas. After the sorption of radionuclides, these materials can be directly converted into nanostructured waste forms. This new generation of waste forms incorporates radionuclides as nano-scale inclusions in a host matrix and thus effectively relaxes the constraint of crystal structure on waste loadings. Therefore, the new waste forms have an unprecedented flexibility to accommodate a wide range of radionuclides with high waste loadings and low leaching rates. Specifically, we have developed a general route for synthesizing nanoporous metal oxides from inexpensive inorganic precursors. More than 300 materials have been synthesized and characterized with x-ray diffraction (XRD), BET surface area measurements, and transmission electron microscope (TEM). The sorption capabilities of the synthesized materials have been quantified by using stable isotopes I and Re as analogs to {sup 129}I and {sup 99}Tc. The results have confirmed our original finding that nanoporous Al oxide and its derivatives have high I sorption capabilities due to the combined effects of surface chemistry and nanopore confinement. We have developed a suite of techniques for the fixation of radionuclides in metal oxide nanopores. The key to this fixation is to chemically convert a target radionuclide into a less volatile or soluble form. We have developed a technique to convert a radionuclide-loaded nanoporous material into a durable glass-ceramic waste form through calcination. We have shown that mixing a radionuclide-loaded getter material with a Na-silicate solution can effectively seal the nanopores in the material, thus enhancing radionuclide retention during waste form formation. Our leaching tests have demonstrated the existence of an optimal vitrification temperature for the enhancement of waste form durability. Our work also indicates that silver may not be needed for I immobilization and encapsulation.
Uncertainty quantification in climate models is challenged by the prohibitive cost of a large number of model evaluations for sampling. Another feature that often prevents classical uncertainty analysis from being readily applicable is the bifurcative behavior in the climate data with respect to certain parameters. A typical example is the Meridional Overturning Circulation in the Atlantic Ocean. The maximum overturning stream function exhibits a discontinuity across a curve in the space of two uncertain parameters, namely climate sensitivity and CO2 forcing. In order to propagate uncertainties from model parameters to model output we use polynomial chaos (PC) expansions to represent the maximum overturning stream function in terms of the uncertain climate sensitivity and CO2 forcing parameters. Since the spectral methodology assumes a certain degree of smoothness, the presence of discontinuities suggests that separate PC expansions on each side of the discontinuity will lead to more accurate descriptions of the climate model output compared to global PC expansions. We propose a methodology that first finds a probabilistic description of the discontinuity given a number of data points. Assuming the discontinuity curve is a polynomial, the algorithm is based on Bayesian inference of its coefficients. Markov chain Monte Carlo sampling is used to obtain joint distributions for the polynomial coefficients, effectively parameterizing the distribution over all possible discontinuity curves. Next, we apply the Rosenblatt transformation to the irregular parameter domains on each side of the discontinuity. This transformation maps a space of uncertain parameters with specific probability distributions to a space of i.i.d standard random variables where orthogonal projections can be used to obtain PC coefficients. In particular, we use uniform random variables that are compatible with PC expansions based on Legendre polynomials. The Rosenblatt transformation and the corresponding PC expansions for the model output on either side of the discontinuity are applied successively for several realizations of the discontinuity curve. The climate model output and its associated uncertainty at specific design points is then computed by taking a quadrature-based integration average over PC expansions corresponding to possible realizations of the discontinuity curve.
Conventional methods for uncertainty quantification are generally challenged in the 'tails' of probability distributions. This is specifically an issue for many climate observables since extensive sampling to obtain a reasonable accuracy in tail regions is especially costly in climate models. Moreover, the accuracy of spectral representations of uncertainty is weighted in favor of more probable ranges of the underlying basis variable, which, in conventional bases does not particularly target tail regions. Therefore, what is ideally desired is a methodology that requires only a limited number of full computational model evaluations while remaining accurate enough in the tail region. To develop such a methodology, we explore the use of surrogate models based on non-intrusive Polynomial Chaos expansions and Galerkin projection. We consider non-conventional and custom basis functions, orthogonal with respect to probability distributions that exhibit fat-tailed regions. We illustrate how the use of non-conventional basis functions, and surrogate model analysis, improves the accuracy of the spectral expansions in the tail regions. Finally, we also demonstrate these methodologies using precipitation data from CCSM simulations.
Research and development of advanced reprocessing plant designs can greatly benefit from the development of a reprocessing plant model capable of transient solvent extraction chemistry. This type of model can be used to optimize the operations of a plant as well as the designs for safeguards, security, and safety. Previous work has integrated a transient solvent extraction simulation module, based on the Solvent Extraction Process Having Interaction Solutes (SEPHIS) code developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM) developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The goal of this work was to strengthen the integration by linking more variables between the two codes. The results from this integrated model show expected operational performance through plant transients. Additionally, ORIGEN source term files were integrated into the SSPM to provide concentrations, radioactivity, neutron emission rate, and thermal power data for various spent fuels. This data was used to generate measurement blocks that can determine the radioactivity, neutron emission rate, or thermal power of any stream or vessel in the plant model. This work examined how the code could be expanded to integrate other separation steps and benchmark the results to other data. Recommendations for future work will be presented.
The fluctuating kinetic energy spectrum in the region near the Richtmyer-Meshkov instability (RMI) is experimentally investigated using particle image velocimetry (PIV). The velocity field is measured at a high spatial resolution in the light gas to observe the effects of turbulence production and dissipation. It is found that the RMI acts as a source of turbulence production near the unstable interface, where energy is transferred from the scales of the perturbation to smaller scales until dissipation. The interface also has an effect on the kinetic energy spectrum farther away by means of the distorted reflected shock wave. The energy spectrum far from the interface initially has a higher energy content than that of similar experiments with a flat interface. These differences are quick to disappear as dissipation dominates the flow far from the interface.
Qubits demonstrated using GaAs double quantum dots (DQD). The qubit basis states are the (1) singlet and (2) triplet stationary states. Long spin decoherence times in silicon spurs translation of GaAs qubit in to silicon. In the near term the goals are: (1) Develop surface gate enhancement mode double quantum dots (MOS & strained-Si/SiGe) to demonstrate few electrons and spin read-out and to examine impurity doped quantum-dots as an alternative architecture; (2) Use mobility, C-V, ESR, quantum dot performance & modeling to feedback and improve upon processing, this includes development of atomic precision fabrication at SNL; (3) Examine integrated electronics approaches to RF-SET; (4) Use combinations of numerical packages for multi-scale simulation of quantum dot systems (NEMO3D, EMT, TCAD, SPICE); and (5) Continue micro-architecture evaluation for different device and transport architectures.
The fixed facilities control everything they can to drive down risk. They control the environment, work processes, work pace and workers. The transportation sector drive the State and US highways with high kinetic energy and less-controllable risks such as: (1) other drivers (beginners, impaired, distracted, etc.); (2) other vehicles (tankers, hazmat, super-heavies); (3) road environments (bridges/tunnels/abutments/construction); and (4) degraded weather.
With the goal of studying the conversion of optical energy to electrical energy at the nanoscale, we developed and tested devices based on single-walled carbon nanotubes functionalized with azobenzene chromophores, where the chromophores serve as photoabsorbers and the nanotube as the electronic read-out. By synthesizing chromophores with specific absorption windows in the visible spectrum and anchoring them to the nanotube surface, we demonstrated the controlled detection of visible light of low intensity in narrow ranges of wavelengths. Our measurements suggested that upon photoabsorption, the chromophores isomerize to give a large change in dipole moment, changing the electrostatic environment of the nanotube. All-electron ab initio calculations were used to study the chromophore-nanotube hybrids, and show that the chromophores bind strongly to the nanotubes without disturbing the electronic structure of either species. Calculated values of the dipole moments supported the notion of dipole changes as the optical detection mechanism.
In this work, we developed a self-organizing map (SOM) technique for using web-based text analysis to forecast when a group is undergoing a phase change. By 'phase change', we mean that an organization has fundamentally shifted attitudes or behaviors. For instance, when ice melts into water, the characteristics of the substance change. A formerly peaceful group may suddenly adopt violence, or a violent organization may unexpectedly agree to a ceasefire. SOM techniques were used to analyze text obtained from organization postings on the world-wide web. Results suggest it may be possible to forecast phase changes, and determine if an example of writing can be attributed to a group of interest.
Three salt compositions for potential use in trough-based solar collectors were tested to determine their mechanical properties as a function of temperature. The mechanical properties determined were unconfined compressive strength, Young's modulus, Poisson's ratio, and indirect tensile strength. Seventeen uniaxial compression and indirect tension tests were completed. It was found that as test temperature increases, unconfined compressive strength and Young's modulus decreased for all salt types. Empirical relationships were developed quantifying the aforementioned behaviors. Poisson's ratio tends to increase with increasing temperature except for one salt type where there is no obvious trend. The variability in measured indirect tensile strength is large, but not atypical for this index test. The average tensile strength for all salt types tested is substantially higher than the upper range of tensile strengths for naturally occurring rock salts. Interest in raising the operating temperature of concentrating solar technologies and the incorporation of thermal storage has motivated studies on the implementation of molten salt as the system working fluid. Recently, salt has been considered for use in trough-based solar collectors and has been shown to offer a reduction in levelized cost of energy as well as increasing availability (Kearney et al., 2003). Concerns regarding the use of molten salt are often related to issues with salt solidification and recovery from freeze events. Differences among salts used for convective heat transfer and storage are typically designated by a comparison of thermal properties. However, the potential for a freeze event necessitates an understanding of salt mechanical properties in order to characterize and mitigate possible detrimental effects. This includes stress imparted by the expanding salt. Samples of solar salt, HITEC salt (Coastal Chemical Co.), and a low melting point quaternary salt were cast for characterization tests to determine unconfined compressive strength, indirect tensile strength, coefficient of thermal expansion (CTE), Young's modulus, and Poisson's ratio. Experiments were conducted at multiple temperatures below the melting point to determine temperature dependence.
Two samples of jacketed Microtherm{reg_sign}HT were hydrostatically pressurized to maximum pressures of 29,000 psi to evaluate both pressure-volume response and change in bulk modulus as a function of density. During testing, each of the two samples exhibited large irreversible compactive volumetric strains with only small increases in pressure; however at volumetric strains of approximately 50%, the Microtherm{reg_sign}HT stiffened noticeably at ever increasing rates. At the maximum pressure of 29,000 psi, the volumetric strains for both samples were approximately 70%. Bulk modulus, as determined from hydrostatic unload/reload loops, increased by more than two-orders of magnitude (from about 4500 psi to over 500,000 psi) from an initial material density of {approx}0.3 g/cc to a final density of {approx}1.1 g/cc. An empirical fit to the density vs. bulk modulus data is K = 492769{rho}{sup 4.6548}, where K is the bulk modulus in psi, and {rho} is the material density in g/cm{sup 3}. The porosity decreased from 88% to {approx}20% indicating that much higher pressures would be required to compact the material fully.
An optical circulator is a multi-port, nonreciprocal device that routes light from one specific port to another. Optical circulators have at least 3 or 4 ports, up to 6 port possible (JDS Uniphase, Huihong Fiber) Circulators do not disregard backward propagating light, but direct it to another port. Optical circulators are commonly found in bi-directional transmission systems, WDM networks, fiber amplifiers, and optical time domain reflectometers (OTDRs). 3-Port optical circulators are commonly used in PDV systems. 1550 nm laser light is launched into Port 1 and will exit out of Port 2 to the target. Doppler-shifted light off the moving surface is reflected back into Port 2 and exits out of Port 3. Surprisingly, a circulator requires a large number of parts to operate efficiently. Transparent circulators offer higher isolation than those of the reflective style using PBSs. A lower PMD is obtained using birefringent crystals rather than PBSs due to the similar path lengths between e and o rays. Many various circulator designs exist, but all achieve the same non-reciprocal results.
Tracing system calls makes debugging easy and fast. On Plan 9, traditionally, system call tracing has been implemented with acid. New systems do not always implement all the capabilities needed for Acid, particularly the ability to rewrite the process code space to insert breakpoints. Architecture support libraries are not always available for Acid, or may not work even on a supported architecture. The requirement that Acid's libraries be available can be a problem on systems with a very small memory footprint, such as High Performance Computing systems where every Kbyte counts. Finally, Acid tracing is inconvenient in the presence of forks, which means tracing shell pipelines is particularly troublesome. The strace program available on most Unix systems is far more convenient to use and more capable than Acid for system call tracing. A similar system on Plan 9 can simplify troubleshooting. We have built a system calling tracing capability into the Plan 9 kernel. It has proven to be more convenient than strace in programming effort. One can write a shell script to implement tracing, and the C code to implement an strace equivalent is several orders of magnitude smaller.
The limiting performance of PDV is determined by power spectrum location resolution - The uncertainty principle overestimates error and peak fit confidences underestimates error. Simulations indicate that PDV is: (1) Inaccurate and imprecise at low frequencies; (2) Accurate and (potentially) precise otherwise; (3) Limiting performance can be tied to sampling rate, noise fraction, and analysis duration. Frequency conversion is a good thing. PDV is competitive with VISAR, despite wavelength difference.
Imported oil exacerabates our trade deficit and funds anti-American regimes. Nuclear Energy (NE) is a demonstrated technology with high efficiency. NE's two biggest political detriments are possible accidents and nuclear waste disposal. For NE policy, proliferation is the biggest obstacle. Nuclear waste can be reduced through reprocessing, where fuel rods are separated into various streams, some of which can be reused in reactors. Current process developed in the 1950s is dirty and expensive, U/Pu separation is the most critical. Fuel rods are sheared and dissolved in acid to extract fissile material in a centrifugal contactor. Plants have many contacts in series with other separations. We have taken a science and simulation-based approach to develop a modern reprocessing plant. Models of reprocessing plants are needed to support nuclear materials accountancy, nonproliferation, plant design, and plant scale-up.
The Building Restoration Operations Optimization Model (BROOM) is a software product developed to assist in the restoration of major transport facilities in the event of an attack involving chemical or biological materials. As shown in Figure 3-1, the objective of this work is to replace a manual, paper-based data entry and tracking system with an electronic system that should be much less error-prone. It will also manage the sampling data efficiently and produce contamination maps in a more timely manner.
Nano-imprinting is an increasingly popular method of creating structured, nanometer scale patterns on a variety of surfaces. Applications are numerous, including non-volatile memory devices, printed flexible circuits, light-management films for displays and sundry energy-conversion devices. While there have been many extensive studies of fluid transport through the individual features of a pattern template, computational models of the entire machine-scale process, where features may number in the trillions per square inch, are currently computationally intractable. In this presentation we discuss a multiscale model aimed at addressing machine-scale issues in a nano-imprinting process. Individual pattern features are coarse-grained and represented as a structured porous medium, and the entire process is modeled using lubrication theory in a two-dimensional finite element method simulation. Machine pressures, optimal initial liquid distributions, pattern fill fractions (shown in figure 1), and final coating distributions of a typical process are investigated. This model will be of interest to those wishing to understand and carefully design the mechanics of nano-imprinting processes.
Controlled assembly in soft-particle colloidal suspensions is a technology poised to advance manufacturing methods for nano-scale templating, coating, and bio-conjugate devices. Applications for soft-particle colloids include photovoltaics, nanoelectronics, functionalized thin-film coatings, and a wide range of bio-conjugate devices such as sensors, assays, and bio-fuel cells. This presentation covers the topics of modeling and simulation of soft-particle colloidal systems over dewetting, evaporation, and irradiation gradients, including deposition of particles to surfaces. By tuning particle/solvent and environmental parameters, we transition from the regime of self-assembly to that of controlled assembly, and enable finer resolution of features at both the nano-scale and meso-scale. We report models of interparticle potentials and order parametrization techniques including results from simulations of colloids utilizing soft-particle field potentials. Using LAMMPS (Large-Scale Atomic/Molecular Massively Parallel Simulator), we demonstrate effects of volume fraction, shear and drag profiles, adsorbed and bulk polymer parameters, solvent chi parameter, and deposition profiles. Results are compared to theoretical models and correlation to TEM images from soft-particle irradiation experiments.
Long chain alcohols possess major advantages over ethanol as bio-components for gasoline, including higher energy content, better engine compatibility, and less water solubility. Rapid developments in biofuel technology have made it possible to produce C{sub 4}-C{sub 5} alcohols efficiently. These higher alcohols could significantly expand the biofuel content and potentially replace ethanol in future gasoline mixtures. This study characterizes some fundamental properties of a C{sub 5} alcohol, isopentanol, as a fuel for homogeneous-charge compression-ignition (HCCI) engines. Wide ranges of engine speed, intake temperature, intake pressure, and equivalence ratio are investigated. The elementary autoignition reactions of isopentanol is investigated by analyzing product formation from laser-photolytic Cl-initiated isopentanol oxidation. Carbon-carbon bond-scission reactions in the low-temperature oxidation chemistry may provide an explanation for the intermediate-temperature heat release observed in the engine experiments. Overall, the results indicate that isopentanol has a good potential as a HCCI fuel, either in neat form or in blend with gasoline.
One of the most influential recent results in network analysis is that many natural networks exhibit a power-law or log-normal degree distribution. This has inspired numerous generative models that match this property. However, more recent work has shown that while these generative models do have the right degree distribution, they are not good models for real life networks due to their differences on other important metrics like conductance. We believe this is, in part, because many of these real-world networks have very different joint degree distributions, i.e. the probability that a randomly selected edge will be between nodes of degree k and l. Assortativity is a sufficient statistic of the joint degree distribution, and it has been previously noted that social networks tend to be assortative, while biological and technological networks tend to be disassortative. We suggest understanding the relationship between network structure and the joint degree distribution of graphs is an interesting avenue of further research. An important tool for such studies are algorithms that can generate random instances of graphs with the same joint degree distribution. This is the main topic of this paper and we study the problem from both a theoretical and practical perspective. We provide an algorithm for constructing simple graphs from a given joint degree distribution, and a Monte Carlo Markov Chain method for sampling them. We also show that the state space of simple graphs with a fixed degree distribution is connected via end point switches. We empirically evaluate the mixing time of this Markov Chain by using experiments based on the autocorrelation of each edge. These experiments show that our Markov Chain mixes quickly on real graphs, allowing for utilization of our techniques in practice.
We will present a study of the structure-property relations in Reststrahlen materials that possess a band of negative permittivities in the infrared. It will be shown that sub-micron defects strongly affect the optical response, resulting in significantly diminished permittivities. This work has implications on the use of ionic materials in IR-metamaterials.
The Plutonium Air Transportable Package, Model PAT-1, is certified under Title 10, Code of Federal Regulations Part 71 by the U.S. Nuclear Regulatory Commission (NRC) per Certificate of Compliance (CoC) USA/0361B(U)F-96 (currently Revision 9). The purpose of this SAR Addendum is to incorporate plutonium (Pu) metal as a new payload for the PAT-1 package. The Pu metal is packed in an inner container (designated the T-Ampoule) that replaces the PC-1 inner container. The documentation and results from analysis contained in this addendum demonstrate that the replacement of the PC-1 and associated packaging material with the T-Ampoule and associated packaging with the addition of the plutonium metal content are not significant with respect to the design, operating characteristics, or safe performance of the containment system and prevention of criticality when the package is subjected to the tests specified in 10 CFR 71.71, 71.73 and 71.74.
The Plutonium Air Transportable Package, Model PAT-1, is certified under Title 10, Code of Federal Regulations Part 71 by the U.S. Nuclear Regulatory Commission (NRC) per Certificate of Compliance (CoC) USA/0361B(U)F-96 (currently Revision 9). The National Nuclear Security Administration (NNSA) submitted SAND Report SAND2009-5822 to NRC that documented the incorporation of plutonium (Pu) metal as a new payload for the PAT-1 package. NRC responded with a Request for Additional Information (RAI), identifying information needed in connection with its review of the application. The purpose of this SAND report is to provide the authors responses to each RAI. SAND Report SAND2010-6106 containing the proposed changes to the Addendum is provided separately.
This report provides documentation for the completion of the Sandia portion of the ASC Level II Visualization on the platform milestone. This ASC Level II milestone is a joint milestone between Sandia National Laboratories and Los Alamos National Laboratories. This milestone contains functionality required for performing visualization directly on a supercomputing platform, which is necessary for peta-scale visualization. Sandia's contribution concerns in-situ visualization, running a visualization in tandem with a solver. Visualization and analysis of petascale data is limited by several factors which must be addressed as ACES delivers the Cielo platform. Two primary difficulties are: (1) Performance of interactive rendering, which is most computationally intensive portion of the visualization process. For terascale platforms, commodity clusters with graphics processors(GPUs) have been used for interactive rendering. For petascale platforms, visualization and rendering may be able to run efficiently on the supercomputer platform itself. (2) I/O bandwidth, which limits how much information can be written to disk. If we simply analyze the sparse information that is saved to disk we miss the opportunity to analyze the rich information produced every timestep by the simulation. For the first issue, we are pursuing in-situ analysis, in which simulations are coupled directly with analysis libraries at runtime. This milestone will evaluate the visualization and rendering performance of current and next generation supercomputers in contrast to GPU-based visualization clusters, and evaluate the performance of common analysis libraries coupled with the simulation that analyze and write data to disk during a running simulation. This milestone will explore, evaluate and advance the maturity level of these technologies and their applicability to problems of interest to the ASC program. Scientific simulation on parallel supercomputers is traditionally performed in four sequential steps: meshing, partitioning, solver, and visualization. Not all of these components are necessarily run on the supercomputer. In particular, the meshing and visualization typically happen on smaller but more interactive computing resources. However, the previous decade has seen a growth in both the need and ability to perform scalable parallel analysis, and this gives motivation for coupling the solver and visualization.
The analysis of spacecraft kinematics and dynamics requires an efficient scheme for spatial representation. While the representation of displacement in three dimensional Euclidean space is straightforward, orientation in three dimensions poses particular challenges. The unit quaternion provides an approach that mitigates many of the problems intrinsic in other representation approaches, including the ill-conditioning that arises from computing many successive rotations. This report focuses on the computational utility of unit quaternions and their application to the reconstruction of re-entry vehicle (RV) motion history from sensor data. To this end they will be used in conjunction with other kinematic and data processing techniques. We will present a numerical implementation for the reconstruction of RV motion solely from gyroscope and accelerometer data. This will make use of unit quaternions due to their numerical efficacy in dealing with the composition of many incremental rotations over a time series. In addition to signal processing and data conditioning procedures, algorithms for numerical quaternion-based integration of gyroscope data will be addressed, as well as accelerometer triangulation and integration to yield RV trajectory. Actual processed flight data will be presented to demonstrate the implementation of these methods.
Cost-effective implementation of microalgae as a solar-to-chemical energy conversion platform requires extensive system optimization; computer modeling can bring this to bear. This work uses modified versions of the U.S. Environmental Protection Agency's (EPA's) Environmental Fluid Dynamics Code (EFDC) in conjunction with the U.S. Army Corp of Engineers water-quality code (CE-QUAL) to simulate hydrodynamics coupled to growth kinetics of algae (Phaeodactylum tricornutum) in open-channel raceways. The model allows the flexibility to manipulate a host of variables associated with raceway-design, algal-growth, water-quality, hydrodynamic, and atmospheric conditions. The model provides realistic results wherein growth rates follow the diurnal fluctuation of solar irradiation and temperature. The greatest benefit that numerical simulation of the flow system offers is the ability to design the raceway before construction, saving considerable cost and time. Moreover, experiment operators can evaluate the impacts of various changes to system conditions (e.g., depth, temperature, flow speeds) without risking the algal biomass under study.
Erbium is known to effectively load with hydrogen when held at high temperature in a hydrogen atmosphere. To make the storage of hydrogen kinetically feasible, a thermal activation step is required. Activation is a routine practice, but very little is known about the physical, chemical, and/or electronic processes that occur during Activation. This work presents in situ characterization of erbium Activation using variable energy photoelectron spectroscopy at various stages of the Activation process. Modification of the passive surface oxide plays a significant role in Activation. The chemical and electronic changes observed from core-level and valence band spectra will be discussed along with corroborating ion scattering spectroscopy measurements.
As HPC systems grow in size and complexity, diagnosing problems and understanding system behavior, including failure modes, becomes increasingly difficult and time consuming. At Sandia National Laboratories we have developed a tool, OVIS, to facilitate large scale HPC system understanding. OVIS incorporates an intuitive graphical user interface, an extensive and extendable data analysis suite, and a 3-D visualization engine that allows visual inspection of both raw and derived data on a geometrically correct representation of a HPC system. This talk will cover system instrumentation, data collection (including log files and the complications of meaningful parsing), analysis, visualization of both raw and derived information, and how data can be combined to increase system understanding and efficiency.
One of the tenets of nanotechnology is that the electrical/optical/chemical/biological properties of a material may be changed profoundly when the material is reduced to sufficiently small dimensions - and we can exploit these new properties to achieve novel or greatly improved material's performance. However, there may be mechanical or thermodynamic driving forces that hinder the synthesis of the structure, impair the stability of the structure, or reduce the intended performance of the structure. Examples of these phenomena include de-wetting of films due to high surface tension, thermally-driven instability of nano-grain structure, and defect-related internal dissipation. If we have fundamental knowledge of the mechanical processes at small length scales, we can exploit these new properties to achieve robust nanodevices. To state it simply, the goal of this program is the fundamental understanding of the mechanical properties of materials at small length scales. The research embodied by this program lies at the heart of modern materials science with a guiding focus on structure-property relationships. We have divided this program into three Tasks, which are summarized: (1) Mechanics of Nanostructured Materials (PI Blythe Clark). This task aims to develop a fundamental understanding of the mechanical properties and thermal stability of nanostructured metals, and of the relationship between nano/microstructure and bulk mechanical behavior through a combination of special materials synthesis methods, nanoindentation coupled with finite-element modeling, detailed electron microscopic characterization, and in-situ transmission electron microscopy experiments. (2) Theory of Microstructures and Ensemble Controlled Deformation (PI Elizabeth A. Holm). The goal of this Task is to combine experiment, modeling, and simulation to construct, analyze, and utilize three-dimensional (3D) polycrystalline nanostructures. These full 3D models are critical for elucidating the complete structural geometry, topology, and arrangements that control experimentally-observed phenomena, such as abnormal grain growth, grain rotation, and internal dissipation measured in nanocrystalline metal. (3) Mechanics and Dynamics of Nanostructured and Nanoscale Materials (PI John P. Sullivan). The objective of this Task is to develop atomic-scale understanding of dynamic processes including internal dissipation in nanoscale and nanostructured metals, and phonon transport and boundary scattering in nanoscale structures via internal friction measurements.
Carbon capture and sequestration (CCS) is an option to mitigate impacts of atmospheric carbon emission. Numerous factors are important in determining the overall effectiveness of long-term geologic storage of carbon, including leakage rates, volume of storage available, and system costs. Recent efforts have been made to apply an existing probabilistic performance assessment (PA) methodology developed for deep nuclear waste geologic repositories to evaluate the effectiveness of subsurface carbon storage (Viswanathan et al., 2008; Stauffer et al., 2009). However, to address the most pressing management, regulatory, and scientific concerns with subsurface carbon storage (CS), the existing PA methodology and tools must be enhanced and upgraded. For example, in the evaluation of a nuclear waste repository, a PA model is essentially a forward model that samples input parameters and runs multiple realizations to estimate future consequences and determine important parameters driving the system performance. In the CS evaluation, however, a PA model must be able to run both forward and inverse calculations to support optimization of CO{sub 2} injection and real-time site monitoring as an integral part of the system design and operation. The monitoring data must be continually fused into the PA model through model inversion and parameter estimation. Model calculations will in turn guide the design of optimal monitoring and carbon-injection strategies (e.g., in terms of monitoring techniques, locations, and time intervals). Under the support of Laboratory-Directed Research & Development (LDRD), a late-start LDRD project was initiated in June of Fiscal Year 2010 to explore the concept of an enhanced performance assessment system (EPAS) for carbon sequestration and storage. In spite of the tight time constraints, significant progress has been made on the project: (1) Following the general PA methodology, a preliminary Feature, Event, and Process (FEP) analysis was performed for a hypothetical CS system. Through this FEP analysis, relevant scenarios for CO{sub 2} release were defined. (2) A prototype of EPAS was developed by wrapping an existing multi-phase, multi-component reservoir simulator (TOUGH2) with an uncertainty quantification and optimization code (DAKOTA). (3) For demonstration, a probabilistic PA analysis was successfully performed for a hypothetical CS system based on an existing project in a brine-bearing sandstone. The work lays the foundation for the development of a new generation of PA tools for effective management of CS activities. At a top-level, the work supports energy security and climate change/adaptation by furthering the capability to effectively manage proposed carbon capture and sequestration activities (both research and development as well as operational), and it greatly enhances the technical capability to address this national problem. The next phase of the work will include (1) full capability demonstration of the EPAS, especially for data fusion, carbon storage system optimization, and process optimization of CO{sub 2} injection, and (2) application of the EPAS to actual carbon storage systems.