Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Uncertainty quantificatio in climate models is challenged by the sparsity of the available climate data due to the high computational cost of the model runs. Another feature that prevents classical uncertainty analyses from being easily 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 discontinuity across a curve in the space of two uncertain parameters, namely climate sensitivity and CO{sub 2} forcing. We develop a methodology that performs uncertainty quantificatio in the presence of limited data that have discontinuous character. Our approach is two-fold. First we detect the discontinuity location with a Bayesian inference, thus obtaining a probabilistic representation of the discontinuity curve location in presence of arbitrarily distributed input parameter values. Furthermore, we developed a spectral approach that relies on Polynomial Chaos (PC) expansions on each sides of the discontinuity curve leading to an averaged-PC representation of the forward model that allows efficient uncertainty quantification and propagation. The methodology is tested on synthetic examples of discontinuous data with adjustable sharpness and structure.

The peridynamic model of solid mechanics is a mathematical theory designed to provide consistent mathematical treatment of deformations involving discontinuities, especially cracks. Unlike the partial differential equations (PDEs) of the standard theory, the fundamental equations of the peridynamic theory remain applicable on singularities such as crack surfaces and tips. These basic relations are integro-differential equations that do not require the existence of spatial derivatives of the deformation, or even continuity of the deformation. In the peridynamic theory, material points in a continuous body separated from each other by finite distances can interact directly through force densities. The interaction between each pair of points is called a bond. The dependence of the force density in a bond on the deformation provides the constitutive model for a material. By allowing the force density in a bond to depend on the deformation of other nearby bonds, as well as its own deformation, a wide spectrum of material response can be modelled. Damage is included in the constitutive model through the irreversible breakage of bonds according to some criterion. This criterion determines the critical energy release rate for a peridynamic material. In this talk, we present a general discussion of the peridynamic method and recent progress in its application to penetration and fracture in nonlinearly elastic solids. Constitutive models are presented for rubbery materials, including damage evolution laws. The deformation near a crack tip is discussed and compared with results from the standard theory. Examples demonstrating the spontaneous nucleation and growth of cracks are presented. It is also shown how the method can be applied to anisotropic media, including fiber reinforced composites. Examples show prediction of impact damage in composites and comparison against experimental measurements of damage and delamination.

Abstract not provided.

Abstract not provided.

Abstract not provided.

This work compares the sorption and swelling processes associated with CO2-coal and CO2-clay interactions. We investigated the mechanisms of interaction related to CO2 adsortion in micropores, intercalation into sub-micropores, dissolution in solid matrix, the role of water, and the associated changes in reservoir permeability, for applications in CO2 sequestration and enhanced coal bed methane recovery. The structural changes caused by CO2 have been investigated. A high-pressure micro-dilatometer was equipped to investigate the effect of CO2 pressure on the thermoplastic properties of coal. Using an identical dilatometer, Rashid Khan (1985) performed experiments with CO2 that revealed a dramatic reduction in the softening temperature of coal when exposed to high-pressure CO2. A set of experiments was designed for -20+45-mesh samples of Argonne Premium Pocahontas No.3 coal, which is similar in proximate and ultimate analysis to the Lower Kittanning seam coal that Khan used in his experiments. No dramatic decrease in coal softening temperature has been observed in high-pressure CO2 that would corroborate the prior work of Khan. Thus, conventional polymer (or 'geopolymer') theories may not be directly applicable to CO2 interaction with coals. Clays are similar to coals in that they represent abundant geomaterials with well-developed microporous structure. We evaluated the CO2 sequestration potential of clays relative to coals and investigated the factors that affect the sorption capacity, rates, and permanence of CO2 trapping. For the geomaterials comparison studies, we used source clay samples from The Clay Minerals Society. Preliminary results showed that expandable clays have CO2 sorption capacities comparable to those of coal. We analyzed sorption isotherms, XRD, DRIFTS (infrared reflectance spectra at non-ambient conditions), and TGA-MS (thermal gravimetric analysis) data to compare the effects of various factors on CO2 trapping. In montmorillonite, CO2 molecules may remain trapped for several months following several hours of exposure to high pressure (supercritical conditions), high temperature (above boiling point of water) or both. Such trapping is well preserved in either inert gas or the ambient environment and appears to eventually result in carbonate formation. We performed computer simulations of CO2 interaction with free cations (normal modes of CO2 and Na+CO2 were calculated using B3LYP / aug-cc-pVDZ and MP2 / aug-cc-pVDZ methods) and with clay structures containing interlayer cations (MD simulations with Clayff potentials for clay and a modified CO2 potential). Additionally, interaction of CO2 with hydrated Na-montmorillonite was studied using density functional theory with dispersion corrections. The sorption energies and the swelling behavior were investigated. Preliminary modeling results and experimental observations indicate that the presence of water molecules in the interlayer region is necessary for intercalation of CO2. Our preliminary conclusion is that CO2 molecules may intercalate into interlayer region of swelling clay and stay there via coordination to the interlayer cations.

Reliability-Centered Maintenance (RCM) is a process used to determine what must be done to ensure that any physical asset continues to do whatever its users want it to do in its present operating context. There are 7 basic questions of RCM: (1) what are the functions of the asset; (2) in hwat ways does it fail to fulfill its functions; (3) what causes each functional failure; (4) what happens when each failure occurs; (5) in what way does each failure matter; (6) what can be done to predict or prevent each failure; and (7) what should be done if a suitable proactive task cannot be found. SNL's RCM experiences: (1) acid exhaust system - (a) reduced risk of system failure (safety and operational consequences), (b) reduced annual correctiv maintenance hours from 138 in FY06 to zero in FY07, FY08, FY09, FY10 and FY11 so far, (c) identified single point of failure, mitigated risk, and recommended a permanent solution; (2) fire alarm system - (a) reduced false alarms, which cause costly evacuations, (b) precented 1- to 2-day evacuation by identifying and obtaining a critical spare for a network card; (3) heating water system - (a) reduced PM hours on fire-tube boilers by 60%, (b) developed operator tasks and PM plan for modular boilers, which can be applied to many installations; and (4) GIF source elevator system - (a) reduced frequency of PM tasks from 6 months to 1 year, (b) established predictive maintenance task that identified overheating cabinet and prevented potential electrical failure or fire.

Abstract not provided.

In a (future) quantum computer a single logical quantum bit (qubit) will be made of multiple physical qubits. These extra physical qubits implement mandatory extensive error checking. The efficiency of error correction will fundamentally influence the performance of a future quantum computer, both in latency/speed and in error threshold (the worst error tolerated for an individual gate). Executing this quantum error correction requires scheduling the individual operations subject to architectural constraints. Since our last talk on this subject, a team of researchers at Sandia National Labortories has designed a logical qubit architecture that considers all relevant architectural issues including layout, the effects of supporting classical electronics, and the types of gates that the underlying physical qubit implementation supports most naturally. This is a two-dimensional system where 2-qubit operations occur locally, so there is no need to calculate more complex qubit/information transportation. Using integer programming, we found a schedule of qubit operations that obeys the hardware constraints, implements the local-check code in the native gate set, and minimizes qubit idle periods. Even with an optimal schedule, however, parallel Monte Carlo simulation shows that there is no finite error probability for the native gates such that the error-correction system would be benecial. However, by adding dynamic decoupling, a series of timed pulses that can reverse some errors, we found that there may be a threshold. Thus finding optimal schedules for increasingly-refined scheduling problems has proven critical for the overall design of the logical qubit system. We describe the evolving scheduling problems and the ideas behind the integer programming-based solution methods. This talk assumes no prior knowledge of quantum computing.

Abstract not provided.

Airworthiness Assurance NDI Validation Center (AANC) objectives are: (1) Enhance aircraft safety and reliability; (2) Aid developing advanced aircraft designs and maintenance techniques; (3) Provide our customers with comprehensive, independent, and quantitative/qualitative evaluations of new and enhanced inspection, maintenance, and repair techniques; (4) Facilitate transferring effective technologies into the aviation industry; (5) Support FAA rulemaking process by providing guidance on content & necessary tools to meet requirements or recommendations of FARs, ADs, ACs, SBs, SSIDs, CPCP, and WFD; and (6) Coordinate with and respond to Airworthiness Assurance Working Group (AAWG) in support of FAA Aviation Rulemaking Advisory Committee (ARAC).

Abstract not provided.

Arctic sea ice is an important component of the global climate system and due to feedback effects the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice to model physical parameters. A new sea ice model that has the potential to improve sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of the Los Alamos National Laboratory CICE code and the MPM sea ice code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness, and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution.

Abstract not provided.

A slight modification of a package to transport solid metal contents requires inclusion of a thin titanium liner to protect against possible eutectic formation in 10 CFR 71.74 regulatory fire accident conditions. Under severe transport regulatory impact conditions, the package contents could impart high localized loading of the liner, momentarily pinching it between the contents and the thick containment vessel, and inducing some plasticity near the contact point. Actuator and drop table testing of simulated contents impacts against liner/containment vessel structures nearly bounded the potential plastic strain and stress triaxiality conditions, without any ductile tearing of the eutectic barrier. Additional bounding was necessary in some cases beyond the capability of the actuator and drop table tests, and in these cases a stress-modified evolution integral over the plastic strain history was successfully used as a failure criterion to demonstrate that structural integrity was maintained. The Heaviside brackets only allow the evolution integral to accumulate value when the maximum principal stress is positive, since failure is never observed under pure hydrostatic pressure, where the maximum principal stress is negative. Detailed finite element analyses of myriad possible impact orientations and locations between package contents and the thin eutectic barrier under regulatory impact conditions have shown that not even the initiation of a ductile tear occurs. Although localized plasticity does occur in the eutectic barrier, it is not the primary containment boundary and is thus not subject to ASME stress allowables from NRC Regulatory Guide 7.6. These analyses were used to successfully demonstrate that structural integrity of the eutectic barrier was maintained in all 10 CFR 71.73 and 71.74 regulatory accident conditions. The NRC is currently reviewing the Safety Analysis Report.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The two primary objectives of this LDRD project were to create a lightweight kernel (LWK) operating system(OS) designed to take maximum advantage of multi-core processors, and to leverage the virtualization capabilities in modern multi-core processors to create a more flexible and adaptable LWK environment. The most significant technical accomplishments of this project were the development of the Kitten lightweight kernel, the co-development of the SMARTMAP intra-node memory mapping technique, and the development and demonstration of a scalable virtualization environment for HPC. Each of these topics is presented in this report by the inclusion of a published or submitted research paper. The results of this project are being leveraged by several ongoing and new research projects.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Critical infrastructure resilience has become a national priority for the U. S. Department of Homeland Security. System resilience has been studied for several decades in many different disciplines, but no standards or unifying methods exist for critical infrastructure resilience analysis. This report documents the results of a late-start Laboratory Directed Research and Development (LDRD) project that investigated the identification of optimal recovery strategies that maximize resilience. To this goal, we formulate a bi-level optimization problem for infrastructure network models. In the 'inner' problem, we solve for network flows, and we use the 'outer' problem to identify the optimal recovery modes and sequences. We draw from the literature of multi-mode project scheduling problems to create an effective solution strategy for the resilience optimization model. We demonstrate the application of this approach to a set of network models, including a national railroad model and a supply chain for Army munitions production.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The Smart Grid has come to describe a next-generation electrical power system that is typified by the increased use of communications and information technology in the generation, delivery and consumption of electrical energy. Much of the present Smart Grid analysis focuses on utility and consumer interaction. i.e. smart appliances, home automation systems, rate structures, consumer demand response, etc. An identified need is to assess the upstream and midstream operations of natural gas as a result of the smart grid. The nature of Smart Grid, including the demand response and role of information, may require changes in upstream and midstream natural gas operations to ensure availability and efficiency. Utility reliance on natural gas will continue and likely increase, given the backup requirements for intermittent renewable energy sources. Efficient generation and delivery of electricity on Smart Grid could affect how natural gas is utilized. Things that we already know about Smart Grid are: (1) The role of information and data integrity is increasingly important. (2) Smart Grid includes a fully distributed system with two-way communication. (3) Smart Grid, a complex network, may change the way energy is supplied, stored, and in demand. (4) Smart Grid has evolved through consumer driven decisions. (5) Smart Grid and the US critical infrastructure will include many intermittent renewables.

This report documents research carried out by the author throughout his 3-years Truman fellowship. The overarching goal consisted of developing multiscale schemes which permit not only the predictive description but also the computational design of improved materials. Identifying new materials through changes in atomic composition and configuration requires the use of versatile first principles methods, such as density functional theory (DFT). Using DFT, its predictive reliability has been investigated with respect to pseudopotential construction, band-gap, van-der-Waals forces, and nuclear quantum effects. Continuous variation of chemical composition and derivation of accurate energy gradients in compound space has been developed within a DFT framework for free energies of solvation, reaction energetics, and frontier orbital eigenvalues. Similar variations have been leveraged within classical molecular dynamics in order to address thermal properties of molten salt candidates for heat transfer fluids used in solar thermal power facilities. Finally, a combination of DFT and statistical methods has been used to devise quantitative structure property relationships for the rapid prediction of charge mobilities in polyaromatic hydrocarbons.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

MPI is the dominant programming model for distributed memory parallel computers, and is often used as the intra-node programming model on multi-core compute nodes. However, application developers are increasingly turning to hybrid models that use threading within a node and MPI between nodes. In contrast to MPI, most current threaded models do not require application developers to deal explicitly with data locality. With increasing core counts and deeper NUMA hierarchies seen in the upcoming LANL/SNL 'Cielo' capability supercomputer, data distribution poses an upper boundary on intra-node scalability within threaded applications. Data locality therefore has to be identified at runtime using static memory allocation policies such as first-touch or next-touch, or specified by the application user at launch time. We evaluate several existing techniques for managing data distribution using micro-benchmarks on an AMD 'Magny-Cours' system with 24 cores among 4 NUMA domains and argue for the adoption of a dynamic runtime system implemented at the kernel level, employing a novel page table replication scheme to gather per-NUMA domain memory access traces.

Abstract not provided.

Changes in climate can lead to instabilities in physical and economic systems, particularly in regions with marginal resources. Global climate models indicate increasing global mean temperatures over the decades to come and uncertainty in the local to national impacts means perceived risks will drive planning decisions. Agent-based models provide one of the few ways to evaluate the potential changes in behavior in coupled social-physical systems and to quantify and compare risks. The current generation of climate impact analyses provides estimates of the economic cost of climate change for a limited set of climate scenarios that account for a small subset of the dynamics and uncertainties. To better understand the risk to national security, the next generation of risk assessment models must represent global stresses, population vulnerability to those stresses, and the uncertainty in population responses and outcomes that could have a significant impact on U.S. national security.

Abstract not provided.

This report is a summary of the accomplishments of the 'Scalable Solutions for Processing and Searching Very Large Document Collections' LDRD, which ran from FY08 through FY10. Our goal was to investigate scalable text analysis; specifically, methods for information retrieval and visualization that could scale to extremely large document collections. Towards that end, we designed, implemented, and demonstrated a scalable framework for text analysis - ParaText - as a major project deliverable. Further, we demonstrated the benefits of using visual analysis in text analysis algorithm development, improved performance of heterogeneous ensemble models in data classification problems, and the advantages of information theoretic methods in user analysis and interpretation in cross language information retrieval. The project involved 5 members of the technical staff and 3 summer interns (including one who worked two summers). It resulted in a total of 14 publications, 3 new software libraries (2 open source and 1 internal to Sandia), several new end-user software applications, and over 20 presentations. Several follow-on projects have already begun or will start in FY11, with additional projects currently in proposal.

Abstract not provided.

Abstract not provided.

Abstract not provided.

The current state-of-the-art in antineutrino detection is such that it is now possible to remotely monitor the operational status, power levels and fissile content of nuclear reactors in real-time. This non-invasive and incorruptible technique has been demonstrated at civilian power reactors in both Russia and the United States and has been of interest to the IAEA Novel Technologies Unit for several years. Expert's meetings were convened at IAEA headquarters in 2003 and again in 2008. The latter produced a report in which antineutrino detection was called a 'highly promising technology for safeguards applications' at nuclear reactors and several near-term goals and suggested developments were identified to facilitate wider applicability. Over the last few years, we have been working to achieve some of these goals and improvements. Specifically, we have already demonstrated the successful operation of non-toxic detectors and most recently, we are testing a transportable, above-ground detector system, which is fully contained within a standard 6 meter ISO container. If successful, such a system could allow easy deployment at any reactor facility around the world. As well, our previously demonstrated ability to remotely monitor the data and respond in real-time to reactor operational changes could allow the verification of operator declarations without the need for costly site-visits. As the global nuclear power industry expands around the world, the burden on maintaining operational histories and safeguarding inventories will increase greatly. Such a system for providing remote data to verify operator's declarations could greatly reduce the need for frequent site inspections while still providing a robust warning of anomalies requiring further investigation.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Statistical Latent Dirichlet Analysis produces mixture model data that are geometrically equivalent to points lying on a regular simplex in moderate to high dimensions. Numerous other statistical models and techniques also produce data in this geometric category, even though the meaning of the axes and coordinate values differs significantly. A distance function is used to further analyze these points, for example to cluster them. Several different distance functions are popular amongst statisticians; which distance function is chosen is usually driven by the historical preference of the application domain, information-theoretic considerations, or by the desirability of the clustering results. Relatively little consideration is usually given to how distance functions geometrically transform data, or the distances algebraic properties. Here we take a look at these issues, in the hope of providing complementary insight and inspiring further geometric thought. Several popular distances, {chi}{sup 2}, Jensen - Shannon divergence, and the square of the Hellinger distance, are shown to be nearly equivalent; in terms of functional forms after transformations, factorizations, and series expansions; and in terms of the shape and proximity of constant-value contours. This is somewhat surprising given that their original functional forms look quite different. Cosine similarity is the square of the Euclidean distance, and a similar geometric relationship is shown with Hellinger and another cosine. We suggest a geodesic variation of Hellinger. The square-root projection that arises in Hellinger distance is briefly compared to standard normalization for Euclidean distance. We include detailed derivations of some ratio and difference bounds for illustrative purposes. We provide some constructions that nearly achieve the worst-case ratios, relevant for contours.

Abstract not provided.

Abstract not provided.

This paper presents a mixed-potential integral-equation formulation for analyzing 1-D periodic leaky-wave antennas in layered media. The structures are periodic in one dimension and finite in the other two dimensions. The unit cell consists of an arbitrary-shaped metallic/dielectric structure. The formulation has been implemented in the EIGER{trademark} code in order to obtain the real and complex propagation wavenumbers of the bound and leaky modes of such structures. Validation results presented here include a 1-D periodic planar leaky-wave antenna and a fully 3-D waveguide test case.

Heightened interest in micro-scale and nano-scale patterning by imprinting, embossing, and nano-particulate suspension coating stems from a recent surge in development of higher-throughput manufacturing methods for integrated devices. Energy-applications addressing alternative, renewable energy sources offer many examples of the need for improved manufacturing technology for micro and nano-structured films. In this presentation we address one approach to micro- and nano-pattering coating using film deposition and differential wetting of nanoparticles suspensions. Rather than print nanoparticle or colloidal inks in discontinuous patches, which typically employs ink jet printing technology, patterns can be formed with controlled dewetting of a continuously coated film. Here we report the dynamics of a volatile organic solvent laden with nanoparticles dispensed on the surfaces of water droplets, whose contact angles (surface energy) and perimeters are defined by lithographic patterning of initially (super)hydrophobic surfaces.. The lubrication flow equation together with averaged particle transport equation are employed to predict the film thickness and particle average concentration profiles during subsequent drying of the organic and water solvents. The predictions are validated by contact angle measurements, in situ grazing incidence small angle x-ray scattering experiments, and TEM images of the final nanoparticle assemblies.

Abstract not provided.

External modifications can transform a conventional photonic doppler velocimetry (PDV) system to other useful configurations - Non-standard probes and Frequency-conversion measurements. This approach is easier than supporting every conceivable measurement in the core PDV design. Circulator specifications may be important - -30 dB isolation (common) probably not be enough, -50 dB isolation is available, and some bench testing may be needed.

Abstract not provided.

Abstract not provided.

This report explores the behavior of nodal-based tetrahedral elements on six sample problems, and compares their solution to that of a corresponding hexahedral mesh. The problems demonstrate that while certain aspects of the solution field for the nodal-based tetrahedrons provide good quality results, the pressure field tends to be of poor quality. Results appear to be strongly affected by the connectivity of the tetrahedral elements. Simulations that rely on the pressure field, such as those which use material models that are dependent on the pressure (e.g. equation-of-state models), can generate erroneous results. Remeshing can also be strongly affected by these issues. The nodal-based test elements as they currently stand need to be used with caution to ensure that their numerical deficiencies do not adversely affect critical values of interest.

A new experimental technique to measure material shear strength at high pressures has been developed for use on magneto-hydrodynamic (MHD) drive pulsed power platforms. By applying an external static magnetic field to the sample region, the MHD drive directly induces a shear stress wave in addition to the usual longitudinal stress wave. Strength is probed by passing this shear wave through a sample material where the transmissible shear stress is limited to the sample strength. The magnitude of the transmitted shear wave is measured via a transverse VISAR system from which the sample strength is determined.

Abstract not provided.

While individual neurons function at relatively low firing rates, naturally-occurring nervous systems not only surpass manmade systems in computing power, but accomplish this feat using relatively little energy. It is asserted that the next major breakthrough in computing power will be achieved through application of neuromorphic approaches that mimic the mechanisms by which neural systems integrate and store massive quantities of data for real-time decision making. The proposed LDRD provides a conceptual foundation for SNL to make unique advances toward exascale computing. First, a team consisting of experts from the HPC, MESA, cognitive and biological sciences and nanotechnology domains will be coordinated to conduct an exercise with the outcome being a concept for applying neuromorphic computing to achieve exascale computing. It is anticipated that this concept will involve innovative extension and integration of SNL capabilities in MicroFab, material sciences, high-performance computing, and modeling and simulation of neural processes/systems.

Adagio is a Lagrangian, three-dimensional, implicit code for the analysis of solids and structures. It uses a multi-level iterative solver, which enables it to solve problems with large deformations, nonlinear material behavior, and contact. It also has a versatile library of continuum and structural elements, and an extensive library of material models. Adagio is written for parallel computing environments, and its solvers allow for scalable solutions of very large problems. Adagio uses the SIERRA Framework, which allows for coupling with other SIERRA mechanics codes. This document describes the functionality and input structure for Adagio.

Presto is a Lagrangian, three-dimensional explicit, transient dynamics code that is used to analyze solids subjected to large, suddenly applied loads. The code is designed for a parallel computing environment and for problems with large deformations, nonlinear material behavior, and contact. Presto also has a versatile element library that incorporates both continuum elements and structural elements. This user's guide describes the input for Presto that gives users access to all the current functionality in the code. The environment in which Presto is built allows it to be coupled with other engineering analysis codes. Using a concept called scope, the input structure reflects the fact that Presto can be used in a coupled environment. The user's guide describes how scope is implemented from the outermost to the innermost scopes. Within a given scope, the descriptions of input commands are grouped based on functionality of the code. For example, all material input command lines are described in a chapter of the user's guide for all the material models that can be used in Presto.

Statistical analysis is typically used to reduce the dimensionality of and infer meaning from data. A key challenge of any statistical analysis package aimed at large-scale, distributed data is to address the orthogonal issues of parallel scalability and numerical stability. Many statistical techniques, e.g., descriptive statistics or principal component analysis, are based on moments and co-moments and, using robust online update formulas, can be computed in an embarrassingly parallel manner, amenable to a map-reduce style implementation. In this paper we focus on contingency tables, through which numerous derived statistics such as joint and marginal probability, point-wise mutual information, information entropy, and {chi}{sup 2} independence statistics can be directly obtained. However, contingency tables can become large as data size increases, requiring a correspondingly large amount of communication between processors. This potential increase in communication prevents optimal parallel speedup and is the main difference with moment-based statistics where the amount of inter-processor communication is independent of data size. Here we present the design trade-offs which we made to implement the computation of contingency tables in parallel.We also study the parallel speedup and scalability properties of our open source implementation. In particular, we observe optimal speed-up and scalability when the contingency statistics are used in their appropriate context, namely, when the data input is not quasi-diffuse.

This report summarizes activities undertaken during FY08-FY10 for the LDRD Peridynamics as a Rigorous Coarse-Graining of Atomistics for Multiscale Materials Design. The goal of our project was to develop a coarse-graining of finite temperature molecular dynamics (MD) that successfully transitions from statistical mechanics to continuum mechanics. The goal of our project is to develop a coarse-graining of finite temperature molecular dynamics (MD) that successfully transitions from statistical mechanics to continuum mechanics. Our coarse-graining overcomes the intrinsic limitation of coupling atomistics with classical continuum mechanics via the FEM (finite element method), SPH (smoothed particle hydrodynamics), or MPM (material point method); namely, that classical continuum mechanics assumes a local force interaction that is incompatible with the nonlocal force model of atomistic methods. Therefore FEM, SPH, and MPM inherit this limitation. This seemingly innocuous dichotomy has far reaching consequences; for example, classical continuum mechanics cannot resolve the short wavelength behavior associated with atomistics. Other consequences include spurious forces, invalid phonon dispersion relationships, and irreconcilable descriptions/treatments of temperature. We propose a statistically based coarse-graining of atomistics via peridynamics and so develop a first of a kind mesoscopic capability to enable consistent, thermodynamically sound, atomistic-to-continuum (AtC) multiscale material simulation. Peridynamics (PD) is a microcontinuum theory that assumes nonlocal forces for describing long-range material interaction. The force interactions occurring at finite distances are naturally accounted for in PD. Moreover, PDs nonlocal force model is entirely consistent with those used by atomistics methods, in stark contrast to classical continuum mechanics. Hence, PD can be employed for mesoscopic phenomena that are beyond the realms of classical continuum mechanics and atomistic simulations, e.g., molecular dynamics and density functional theory (DFT). The latter two atomistic techniques are handicapped by the onerous length and time scales associated with simulating mesoscopic materials. Simulating such mesoscopic materials is likely to require, and greatly benefit from multiscale simulations coupling DFT, MD, PD, and explicit transient dynamic finite element methods FEM (e.g., Presto). The proposed work fills the gap needed to enable multiscale materials simulations.

Abstract not provided.

Abstract not provided.

We present the results of a three year LDRD project that focused on understanding the impact of defects on the electrical, optical and thermal properties of GaN-based nanowires (NWs). We describe the development and application of a host of experimental techniques to quantify and understand the physics of defects and thermal transport in GaN NWs. We also present the development of analytical models and computational studies of thermal conductivity in GaN NWs. Finally, we present an atomistic model for GaN NW electrical breakdown supported with experimental evidence. GaN-based nanowires are attractive for applications requiring compact, high-current density devices such as ultraviolet laser arrays. Understanding GaN nanowire failure at high-current density is crucial to developing nanowire (NW) devices. Nanowire device failure is likely more complex than thin film due to the prominence of surface effects and enhanced interaction among point defects. Understanding the impact of surfaces and point defects on nanowire thermal and electrical transport is the first step toward rational control and mitigation of device failure mechanisms. However, investigating defects in GaN NWs is extremely challenging because conventional defect spectroscopy techniques are unsuitable for wide-bandgap nanostructures. To understand NW breakdown, the influence of pre-existing and emergent defects during high current stress on NW properties will be investigated. Acute sensitivity of NW thermal conductivity to point-defect density is expected due to the lack of threading dislocation (TD) gettering sites, and enhanced phonon-surface scattering further inhibits thermal transport. Excess defect creation during Joule heating could further degrade thermal conductivity, producing a viscous cycle culminating in catastrophic breakdown. To investigate these issues, a unique combination of electron microscopy, scanning luminescence and photoconductivity implemented at the nanoscale will be used in concert with sophisticated molecular-dynamics calculations of surface and defect-mediated NW thermal transport. This proposal seeks to elucidate long standing material science questions for GaN while addressing issues critical to realizing reliable GaN NW devices.

Abstract not provided.

Abstract not provided.

This report examines the current policy, legal, and regulatory framework pertaining to used nuclear fuel and high level waste management in the United States. The goal is to identify potential changes that if made could add flexibility and possibly improve the chances of successfully implementing technical aspects of a nuclear waste policy. Experience suggests that the regulatory framework should be established prior to initiating future repository development. Concerning specifics of the regulatory framework, reasonable expectation as the standard of proof was successfully implemented and could be retained in the future; yet, the current classification system for radioactive waste, including hazardous constituents, warrants reexamination. Whether or not consideration of multiple sites are considered simultaneously in the future, inclusion of mechanisms such as deliberate use of performance assessment to manage site characterization would be wise. Because of experience gained here and abroad, diversity of geologic media is not particularly necessary as a criterion in site selection guidelines for multiple sites. Stepwise development of the repository program that includes flexibility also warrants serious consideration. Furthermore, integration of the waste management system from storage, transportation, and disposition, should be examined and would be facilitated by integration of the legal and regulatory framework. Finally, in order to enhance acceptability of future repository development, the national policy should be cognizant of those policy and technical attributes that enhance initial acceptance, and those policy and technical attributes that maintain and broaden credibility.

Abstract not provided.

This report summarizes a 3-year LDRD program at Sandia National Laboratories exploring mutual injection locking of composite-cavity lasers for enhanced modulation responses. The program focused on developing a fundamental understanding of the frequency enhancement previously demonstrated for optically injection locked lasers. This was then applied to the development of a theoretical description of strongly coupled laser microsystems. This understanding was validated experimentally with a novel 'photonic lab bench on a chip'.

This report contains documentation from an interoperability study conducted under the Late Start LDRD 149630, Exploration of Cloud Computing. A small late-start LDRD from last year resulted in a study (Raincoat) on using Virtual Private Networks (VPNs) to enhance security in a hybrid cloud environment. Raincoat initially explored the use of OpenVPN on IPv4 and demonstrates that it is possible to secure the communication channel between two small 'test' clouds (a few nodes each) at New Mexico Tech and Sandia. We extended the Raincoat study to add IPSec support via Vyatta routers, to interface with a public cloud (Amazon Elastic Compute Cloud (EC2)), and to be significantly more scalable than the previous iteration. The study contributed to our understanding of interoperability in a hybrid cloud.

Abstract not provided.

Abstract not provided.

Abstract not provided.

This LDRD Senior's Council Project is focused on the development, implementation and evaluation of Reduced Order Models (ROM) for application in the thermal analysis of complex engineering problems. Two basic approaches to developing a ROM for combined thermal conduction and enclosure radiation problems are considered. As a prerequisite to a ROM a fully coupled solution method for conduction/radiation models is required; a parallel implementation is explored for this class of problems. High-fidelity models of large, complex systems are now used routinely to verify design and performance. However, there are applications where the high-fidelity model is too large to be used repetitively in a design mode. One such application is the design of a control system that oversees the functioning of the complex, high-fidelity model. Examples include control systems for manufacturing processes such as brazing and annealing furnaces as well as control systems for the thermal management of optical systems. A reduced order model (ROM) seeks to reduce the number of degrees of freedom needed to represent the overall behavior of the large system without a significant loss in accuracy. The reduction in the number of degrees of freedom of the ROM leads to immediate increases in computational efficiency and allows many design parameters and perturbations to be quickly and effectively evaluated. Reduced order models are routinely used in solid mechanics where techniques such as modal analysis have reached a high state of refinement. Similar techniques have recently been applied in standard thermal conduction problems e.g. though the general use of ROM for heat transfer is not yet widespread. One major difficulty with the development of ROM for general thermal analysis is the need to include the very nonlinear effects of enclosure radiation in many applications. Many ROM methods have considered only linear or mildly nonlinear problems. In the present study a reduced order model is considered for application to the combined problem of thermal conduction and enclosure radiation. The main objective is to develop a procedure that can be implemented in an existing thermal analysis code. The main analysis objective is to allow thermal controller software to be used in the design of a control system for a large optical system that resides with a complex radiation dominated enclosure. In the remainder of this section a brief outline of ROM methods is provided. The following chapter describes the fully coupled conduction/radiation method that is required prior to considering a ROM approach. Considerable effort was expended to implement and test the combined solution method; the ROM project ended shortly after the completion of this milestone and thus the ROM results are incomplete. The report concludes with some observations and recommendations.