Bryan Mound 5 ( BM5 ) and West Hackberry 9 ( WH9 ) have the potential to create a significant amount of new storage space should the caverns be deemed "leach - ready". This study discusses the original drilling history of the caverns, surrounding geology, current stability, and, based on this culmination of data, makes a preliminary assessment of the leach potential for the cavern. The risks associated with leaching BM5 present substantial problems for the SPR . The odd shape and large amount of insoluble material make it difficult to de termine whether a targeted leach would have the desired effect and create useable ullage or further distort the shape with preferential leaching . T he likelihood of salt falls and damaged or severed casing string is significant . In addition, a targeted le ach would require the relocation of approximately 27 MMB of oil . Due to the abundance of unknown factors associated with this cavern, a targeted leach of BM5 is not recommended. A targeted leaching of the neck of WH 9 could potentially eliminate or diminis h the mid - cavern ledge result ing in a more stable cavern with a more favorable shape. A better understanding of the composition of the surrounding salt and a less complicated leaching history yields more confidence in the ability to successfully leach this region. A targeted leach of WH9 can be recommended upon the completion of a full leach plan with consideration of the impacts upon nearby caverns .
The current expansion of natural gas (NG) development in the United States requires an understanding of how this change will affect the natural gas industry, downstream consumers, and economic growth in order to promote effective planning and policy development. The impact of this expansion may propagate through the NG system and US economy via changes in manufacturing, electric power generation, transportation, commerce, and increased exports of liquefied natural gas. We conceptualize this problem as supply shock propagation that pushes the NG system and the economy away from its current state of infrastructure development and level of natural gas use. To illustrate this, the project developed two core modeling approaches. The first is an Agent-Based Modeling (ABM) approach which addresses shock propagation throughout the existing natural gas distribution system. The second approach uses a System Dynamics-based model to illustrate the feedback mechanisms related to finding new supplies of natural gas - notably shale gas - and how those mechanisms affect exploration investments in the natural gas market with respect to proven reserves. The ABM illustrates several stylized scenarios of large liquefied natural gas (LNG) exports from the U.S. The ABM preliminary results demonstrate that such scenario is likely to have substantial effects on NG prices and on pipeline capacity utilization. Our preliminary results indicate that the price of natural gas in the U.S. may rise by about 50% when the LNG exports represent 15% of the system-wide demand. The main findings of the System Dynamics model indicate that proven reserves for coalbed methane, conventional gas and now shale gas can be adequately modeled based on a combination of geologic, economic and technology-based variables. A base case scenario matches historical proven reserves data for these three types of natural gas. An environmental scenario, based on implementing a $50/tonne CO 2 tax results in less proven reserves being developed in the coming years while demand may decrease in the absence of acceptable substitutes, incentives or changes in consumer behavior. An increase in demand of 25% increases proven reserves being developed by a very small amount by the end of the forecast period of 2025.
Three-dimensional (3D) information in a physical security system is a highly useful dis- criminator. The two-dimensional data from an imaging systems fails to provide target dis- tance and three-dimensional motion vector, which can be used to reduce nuisance alarm rates and increase system effectiveness. However, 3D imaging devices designed primarily for use in physical security systems are uncommon. This report discusses an architecture favorable to physical security systems; an inexpensive snapshot 3D imaging system utilizing a simple illumination system. The method of acquiring 3D data, tests to understand illumination de- sign, and software modifications possible to maximize information gathering capability are discussed.
The objective of this work is to investigate the efficacy of using calibration strategies from Uncertainty Quantification (UQ) to determine model coefficients for LES. As the target methods are for engineering LES, uncertainty from numerical aspects of the model must also be quantified. 15 The ultimate goal of this research thread is to generate a cost versus accuracy curve for LES such that the cost could be minimized given an accuracy prescribed by an engineering need. Realization of this goal would enable LES to serve as a predictive simulation tool within the engineering design process.
In this project we developed t he atomistic models needed to predict how graphene grows when carbon is deposited on metal and semiconductor surfaces. We first calculated energies of many carbon configurations using first principles electronic structure calculations and then used these energies to construct an empirical bond order potentials that enable s comprehensive molecular dynamics simulation of growth. We validated our approach by comparing our predictions to experiments of graphene growth on Ir, Cu and Ge. The robustness of ou r understanding of graphene growth will enable high quality graphene to be grown on novel substrates which will expand the number of potential types of graphene electronic devices.
II-VI quantum dots, such as CdSe and CdTe, are attractive as downconversion materials for solid-state lighting, because of their narrow linewidth, tunable emission. However, for these materials to have acceptable quantum yields (QYs) requires that they be coated with a II-VI shell material whose valence band offset serves to confine the hole to the core. Confinement prevents the hole from accessing surface traps that lead to nonradiative decay of the exciton. Examples of such hole-confined core/shell QDs include CdTe/CdSe and CdSe/CdS. Unfortunately, the shell can also cause problems due to lattice mismatch, which ranges from 4-6% for systems of interest. This lattice mismatch can create significant interface energies at the heterojunction and places the core under radial compression and the shell under tangential tension. At elevated temperatures (~240°C) interfacial diffusion can relax these stresses, as can surface reconstruction, which can expose the core, creating hole traps. But such high temperatures favor the hexagonal Wurtzite structure, which has lower QY than the cubic zinc blende structure, which can be synthesized at lower temperatures, ~140°C. In the absence of alloying the core/shell structure can become metastable, or even unstable, if the shell is too thick. This can cause result in an irregular shell or even island growth. But if the shell is too thin thermallyactivated transport of the hole to surface traps can occur. In our LDRD we have developed a fundamental atomistic modeling capability, based on Stillinger-Weber and Bond-Order potentials we developed for the entire II-VI class. These pseudo-potentials have enabled us to conduct large-scale atomistic simulations that have led to the computation of phase diagrams of II-VI QDs. These phase diagrams demonstrate that at elevated temperatures the zinc blende phase of CdTe with CdSe grown on it epitaxially becomes thermodynamically unstable due to alloying. This is accompanied by a loss of hole confinement and a severe drop in the QY and emission lifetime, which is confirmed experimentally for the zinc blende core/shell QDs prepared at low temperatures. These QDs have QYs as high as 95%, which makes them very attractive for lighting. Finally, to address strain relaxation in these materials we developed a model for misfit dislocation formation that we have validated through atomistic simulations.
This report presents met-ocean data and wave energy characteristics at eight U.S. wave energy converter (WEC) test and potential deployment sites. Its purpose is to enable the comparison of wave resource characteristics among sites as well as the selection of test sites that are most suitable for a developer’s device and that best meet their testing needs and objectives. It also provides essential inputs for the design of WEC test devices and planning WEC tests, including the planning of deployment, and operations and maintenance. For each site, this report catalogues wave statistics recommended in the International Electrotechnical Commission Technical Specification (IEC 62600-101 TS) on Wave Energy Characterization, as well as the frequency of occurrence of weather windows and extreme sea states, and statistics on wind and ocean currents. It also provides useful information on test site infrastructure and services.
We present results from laser annealing experiments in Si using a passively Q-switched Nd:YAG microlaser. Exposure with laser at fluence values above the damage threshold of commercially available photodiodes results in electrical damage (as measured by an increase in photodiode dark current). We show that increasing the laser fluence to values in excess of the damage threshold can result in annealing of a damage site and a reduction in detector dark current by as much as 100x in some cases. A still further increase in fluence results in irreparable damage. Thus we demonstrate the presence of a laser annealing window over which performance of damaged detectors can be at least partially reconstituted. Moreover dark current reduction is observed over the entire operating range of the diode indicating that device performance has been improved for all values of reverse bias voltage. Additionally, we will present results of laser annealing in Si waveguides. By exposing a small (<10 um) length of a Si waveguide to an annealing laser pulse, the longitudinal phase of light acquired in propagating through the waveguide can be modified with high precision, <15 milliradian per laser pulse. Phase tuning by 180 degrees is exhibited with multiple exposures to one arm of a Mach-Zehnder interferometer at fluence values below the morphological damage threshold of an etched Si waveguide. No reduction in optical transmission at 1550 nm was found after 220 annealing laser shots. Modeling results for laser annealing in Si are also presented.
We present a detailed set of measurements from a piloted, sooting, turbulent C 2 H 4 - fueled diffusion flame. Hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (CARS) is used to monitor temperature and oxygen, while laser-induced incandescence (LII) is applied for imaging of the soot volume fraction in the challenging jet-flame environment at Reynolds number, Re = 20,000. Single-laser shot results are used to map the mean and rms statistics, as well as probability densities. LII data from the soot-growth region of the flame are used to benchmark the soot source term for one-dimensional turbulence (ODT) modeling of this turbulent flame. The ODT code is then used to predict temperature and oxygen fluctuations higher in the soot oxidation region higher in the flame.
The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.
This SAND report summarizes our work on the Sandia National Laboratory LDRD project titled "Efficient Probability of Failure Calculations for QMU using Computational Geometry" which was project #165617 and proposal #13-0144. This report merely summarizes our work. Those interested in the technical details are encouraged to read the full published results, and contact the report authors for the status of the software and follow-on projects.
A model for incorporating solid solutions into reactive transport equations is presented based on an end-member representation. Reactive transport equations are solved directly for the composition and bulk concentration of the solid solution. Reactions of a solid solution with an aqueous solution are formulated in terms of an overall stoichiometric reaction corresponding to a time-varying composition and exchange reactions, equivalent to reaction end-members. Reaction rates are treated kinetically using a transition state rate law for the overall reaction and a pseudo-kinetic rate law for exchange reactions. The composition of the solid solution at the onset of precipitation is assumed to correspond to the least soluble composition, equivalent to the composition at equilibrium. The stoichiometric saturation determines if the solid solution is super-saturated with respect to the aqueous solution. The method is implemented for a simple prototype batch reactor using Mathematica for a binary solid solution. Finally, the sensitivity of the results on the kinetic rate constant for a binary solid solution is investigated for reaction of an initially stoichiometric solid phase with an undersaturated aqueous solution.
Lithium-ion battery particle-scale (non-porous electrode) simulations applied to resolved electrode geometries predict localized phenomena and can lead to better informed decisions on electrode design and manufacturing. This work develops and implements a fully-coupled finite volume methodology for the simulation of the electrochemical equations in a lithium-ion battery cell. The model implementation is used to investigate 3D battery electrode architectures that offer potential energy density and power density improvements over traditional layer-by-layer particle bed battery geometries. Advancement of micro-scale additive manufacturing techniques has made it possible to fabricate these 3D electrode microarchitectures. A variety of 3D battery electrode geometries are simulated and compared across various battery discharge rates and length scales in order to quantify performance trends and investigate geometrical factors that improve battery performance. The energy density and power density of the 3D battery microstructures are compared in several ways, including a uniform surface area to volume ratio comparison as well as a comparison requiring a minimum manufacturable feature size. Significant performance improvements over traditional particle bed electrode designs are observed, and electrode microarchitectures derived from minimal surfaces are shown to be superior. A reduced-order volume-averaged porous electrode theory formulation for these unique 3D batteries is also developed, allowing simulations on the full-battery scale. Electrode concentration gradients are modeled using the diffusion length method, and results for plate and cylinder electrode geometries are compared to particle-scale simulation results. Additionally, effective diffusion lengths that minimize error with respect to particle-scale results for gyroid and Schwarz P electrode microstructures are determined.
Peridynamics, a nonlocal extension of continuum mechanics, is unique in its ability to capture pervasive material failure. Its use in the majority of system-level analyses carried out at Sandia, however, is severely limited, due in large part to computational expense and the challenge posed by the imposition of nonlocal boundary conditions. Combined analyses in which peridynamics is em- ployed only in regions susceptible to material failure are therefore highly desirable, yet available coupling strategies have remained severely limited. This report is a summary of the Laboratory Directed Research and Development (LDRD) project "Strong Local-Nonlocal Coupling for Inte- grated Fracture Modeling," completed within the Computing and Information Sciences (CIS) In- vestment Area at Sandia National Laboratories. A number of challenges inherent to coupling local and nonlocal models are addressed. A primary result is the extension of peridynamics to facilitate a variable nonlocal length scale. This approach, termed the peridynamic partial stress, can greatly reduce the mathematical incompatibility between local and nonlocal equations through reduction of the peridynamic horizon in the vicinity of a model interface. A second result is the formulation of a blending-based coupling approach that may be applied either as the primary coupling strategy, or in combination with the peridynamic partial stress. This blending-based approach is distinct from general blending methods, such as the Arlequin approach, in that it is specific to the coupling of peridynamics and classical continuum mechanics. Facilitating the coupling of peridynamics and classical continuum mechanics has also required innovations aimed directly at peridynamic models. Specifically, the properties of peridynamic constitutive models near domain boundaries and shortcomings in available discretization strategies have been addressed. The results are a class of position-aware peridynamic constitutive laws for dramatically improved consistency at domain boundaries, and an enhancement to the meshfree discretization applied to peridynamic models that removes irregularities at the limit of the nonlocal length scale and dramatically improves conver- gence behavior. Finally, a novel approach for modeling ductile failure has been developed, moti- vated by the desire to apply coupled local-nonlocal models to a wide variety of materials, including ductile metals, which have received minimal attention in the peridynamic literature. Software im- plementation of the partial-stress coupling strategy, the position-aware peridynamic constitutive models, and the strategies for improving the convergence behavior of peridynamic models was completed within the Peridigm and Albany codes, developed at Sandia National Laboratories and made publicly available under the open-source 3-clause BSD license.
A multi-point microwave interferometer (MPMI) concept was developed for non-invasively tracking a shock, reaction, or detonation front in energetic media. Initially, a single-point, heterodyne microwave interferometry capability was established. The design, construction, and verification of the single-point interferometer provided a knowledge base for the creation of the MPMI concept. The MPMI concept uses an electro-optic (EO) crystal to impart a time-varying phase lag onto a laser at the microwave frequency. Polarization optics converts this phase lag into an amplitude modulation, which is analyzed in a heterodyne interfer- ometer to detect Doppler shifts in the microwave frequency. A version of the MPMI was constructed to experimentally measure the frequency of a microwave source through the EO modulation of a laser. The successful extraction of the microwave frequency proved the underlying physical concept of the MPMI design, and highlighted the challenges associated with the longer microwave wavelength. The frequency measurements made with the current equipment contained too much uncertainty for an accurate velocity measurement. Potential alterations to the current construction are presented to improve the quality of the measured signal and enable multiple accurate velocity measurements.
We report an analysis that compares global horizontal irradiance (GHI) estimates from version 3 of the National Solar Radiation Database (NSRDB v3) with surface measurements of GHI at a wide variety of locations over the period spanning from 2005 to 2012. The NSRDB v3 estimate of GHI are derived from the Physical Solar Model (PSM) which employs physics-based models to estimate GHI from measurements of reflected visible and infrared irradiance collected by Geostationary Operational Environment Satellites (GOES) and several other data sources. Because the ground measurements themselves are uncertain our analysis does not establish the absolute accuracy for PSM GHI. However by examining the comparison for trends and for consistency across a large number of sites, we may establish a level of confidence in PSM GHI and identify conditions which indicate opportunities to improve PSM. We focus our evaluation on annual and monthly insolation because these quantities directly relate to prediction of energy production from solar power systems. We find that generally, PSM GHI exhibits a bias towards overestimating insolation, on the order of 5% when all sky conditions are considered, and somewhat less (-3%) when only clear sky conditions are considered. The biases persist across multiple years and are evident at many locations. In our opinion the bias originates with PSM and we view as less credible that the bias stems from calibration drift or soiling of ground instruments. We observe that PSM GHI may significantly underestimate monthly insolation in locations subject to broad snow cover. We found examples of days where PSM GHI apparently misidentified snow cover as clouds, resulting in significant underestimates of GHI during these days and hence leading to substantial understatement of monthly insolation. Analysis of PSM GHI in adjacent pixels shows that the level of agreement between PSM GHI and ground data can vary substantially over distances on the order of 2 km. We conclude that the variance most likely originates from dramatic contrasts in the ground's appearance over these distances.
Biological organisms are potentially the most sensitive and selective biological detection systems known, yet we are currently severely limited in our ability to exploit biological interactions in sensory devices, due in part to the limited stability of biological systems and derived materials. This proposal addresses an important aspect of integrating biological sensory materials in a solid state device. If successful, such technology could enable entirely new classes of robust biosensors that could be miniaturized and deployed in the field. The critical aims of the proposed work were 1) the calibration of a more versatile approach to measuring pH, 2) the use of this method to monitor pH changes caused by the light-induced pumping of protons across vesicles with bacteriorhodopsin integrated into the membranes (either polymer or lipid); 3) the preparation of bilayer assemblies on platinum surfaces; 4) the enhanced detection of lightinduced pH changes driven by bR-loaded supported bilayers. I have developed a methodology that may enable that at interfaces and developed a methodology to characterize the functionality of bilayer membranes with reconstituted membrane proteins. The integrity of the supported bilayer films however must be optimized prior to the full realization of the work originally envisioned in the original proposal. Nevertheless, the work performed on this project and the encouraging results it has produced has demonstrated that these goals are challenging yet within reach.
QD-solids comprising self-assembled semiconductor nanocrystals such as CdSe are currently under investigation for use in a wide array of applications including light emitting diodes, solar cells, field effect transistors, photodetectors, and biosensors. The goal of this LDRD project was develop a fundamental understanding of the relationship between nanoparticle interactions and the different regimes of charge and energy transport in semiconductor quantum dot (QD) solids. Interparticle spacing was tuned through the application of hydrostatic pressure in a diamond anvil cell, and the impact on interparticle interactions was probed using x-ray scattering and a variety of static and transient optical spectroscopies. During the course of this LDRD, we discovered a new, previously unknown, route to synthesize semiconductor quantum wires using high pressure sintering of self-assembled quantum dot crystals. We believe that this new, pressure driven synthesis approach holds great potential as a new tool for nanomaterials synthesis and engineering.
Sandia National Laboratories has been engaged in hardware and software codesign activities for a number of years, indeed, it might be argued that prototyping of clusters as far back as the CPLANT machines and many large capability resources including ASCI Red and RedStorm were examples of codesigned solutions. As the research supporting our codesign activities has moved closer to investigating on-node runtime behavior a nature hunger has grown for detailed analysis of both hardware and algorithm performance from the perspective of low-level operations. The Application Characterization for Exascale (APEX) LDRD was a project concieved of addressing some of these concerns. Primarily the research was to intended to focus on generating accurate and reproducible low-level performance metrics using tools that could scale to production-class code bases. Along side this research was an advocacy and analysis role associated with evaluating tools for production use, working with leading industry vendors to develop and refine solutions required by our code teams and to directly engage with production code developers to form a context for the application analysis and a bridge to the research community within Sandia. On each of these accounts significant progress has been made, particularly, as this report will cover, in the low-level analysis of operations for important classes of algorithms. This report summarizes the development of a collection of tools under the APEX research program and leaves to other SAND and L2 milestone reports the description of codesign progress with Sandia’s production users/developers.
By means of the Antarctic Treaty, which all announced claimants have signed and ratified, no claims to territorial sovereignty shall be asserted while the Treaty is in force. The Treaty, which has been signed by 44 countries (May 2000), reserves the area south of 60 degrees south a zone for peaceful conduct of research.
An understanding of the behavior of hydrogen isotopes in materials is critical to predicting tritium transport in structural metals (at high pressure), estimating tritium losses during production (fission environment), and predicting in-vessel inventory for future fusion devices (plasma driven permeation). Current models often assume equilibrium diffusivity and solubility for a class of materials (e.g. stainless steels or aluminum alloys), neglecting trapping effects or, at best, considering a single population of trapping sites. Permeation and trapping studies of the particular castings and forgings enable greater confidence and reduced margins in the models. For FY15, we have continued our investigation of the role of ferrite in permeation for steels of interest to GTS, through measurements of the duplex steel 2507. We also initiated an investigation of the permeability in work hardened materials, to follow up on earlier observations of unusual permeability in a particular region of 304L forgings. Samples were prepared and characterized for ferrite content and coated with palladium to prevent oxidation. Issues with the poor reproducibility of measurements at low permeability were overcome, although the techniques in use are tedious. Funding through TPBAR and GTS were secured for a research grade quadrupole mass spectrometer (QMS) and replacement turbo pumps, which should improve the fidelity and throughput of measurements in FY16.
The performance and reliability of many mechanical and electrical components depend on the integrity of po lymer - to - solid interfaces . Such interfaces are found in adhesively bonded joints, encapsulated or underfilled electronic modules, protective coatings, and laminates. The work described herein was aimed at improving Sandia's finite element - based capability to predict interfacial crack growth by 1) using a high fidelity nonlinear viscoelastic material model for the adhesive in fracture simulations, and 2) developing and implementing a novel cohesive zone fracture model that generates a mode - mixity dependent toughness as a natural consequence of its formulation (i.e., generates the observed increase in interfacial toughness wi th increasing crack - tip interfacial shear). Furthermore, molecular dynamics simulations were used to study fundamental material/interfa cial physics so as to develop a fuller understanding of the connection between molecular structure and failure . Also reported are test results that quantify how joint strength and interfacial toughness vary with temperature.
This report documents the results of a Laboratory Directed Research and Development (LDRD) effort enti tled "Classifier - Guided Sampling for Complex Energy System Optimization" that was conducted during FY 2014 and FY 2015. The goal of this proj ect was to develop, implement, and test major improvements to the classifier - guided sampling (CGS) algorithm. CGS is type of evolutionary algorithm for perform ing search and optimization over a set of discrete design variables in the face of one or more objective functions. E xisting evolutionary algorithms, such as genetic algorithms , may require a large number of o bjecti ve function evaluations to identify optimal or near - optimal solutions . Reducing the number of evaluations can result in significant time savings, especially if the objective function is computationally expensive. CGS reduce s the evaluation count by us ing a Bayesian network classifier to filter out non - promising candidate designs , prior to evaluation, based on their posterior probabilit ies . In this project, b oth the single - objective and multi - objective version s of the CGS are developed and tested on a set of benchm ark problems. As a domain - specific case study, CGS is used to design a microgrid for use in islanded mode during an extended bulk power grid outage.
Among glass-ceramic compositions modified with a variety of oxidants (AgO, FeO, NiO, PbO, SnO, CuO, CoO, MoO3 and WO3) only CuO and CoO doped glass-ceramics showed existence of bonding oxides through reduction-oxidation (redox) at the GC-SS interface. The CuO-modified glass-ceramics demonstrate the formation of a continuous layer of strong bonding Cr2O3 at the interface in low partial oxygen (PO2) atmosphere. However, in a local reducing atmosphere, the CuO is preferentially reduced at the surface of glass-ceramic rather than the GC-SS interface for redox. The CoO-modified glass-ceramics demonstrate improved GC-SS bonding. But the low mobility of Co++ ions in the GC limited the amount of CoO that can diffuse to and participate in redox at the interface.
Lithium silicate-based glass-ceramics with high coefficients of thermal expansion, designed to form matched hermetic seals in 304L stainless steel housing, show little evidence of interfacial chemical bonding, despite extensive inter-diffusion at the glass-ceramic-stainless steel (GC-SS) interface. A series of glass-ceramic compositions modified with a variety of oxidants, AgO, FeO, NiO, PbO, SnO, CuO, CoO, MoO3 and WO3, are examined for the feasibility of forming bonding oxides through reduction-oxidation (redox) at the GC-SS interface. The oxidants were selected according to their Gibbs free energy to allow for oxidation of Cr/Mn/Si from stainless steel, and yet to prevent a reduction of P2O5 in the glass-ceramic where the P2O5 is to form Li3PO4 nuclei for growth of high expansion crystalline SiO2 phases. Other than the CuO and CoO modified glass-ceramics, bonding from interfacial redox reactions were not achieved in the modified glass-ceramics, either because of poor wetting on the stainless steel or a reduction of the oxidants at the surface of glass-ceramic specimens rather than the GC-SS interface.
Sandia National Laboratories has tested and evaluated an infrasound sensor, the 5113/A manufactured by Hyperion. These infrasound sensors measure pressure output by a methodology developed by the University of Mississippi. The purpose of the infrasound sensor evaluation was to determine a measured sensitivity, transfer function, power, self-noise, and dynamic range. The 5113/A infrasound sensor is a new revision of the 5000 series intended to meet the infrasound application requirements for use in the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO).
This report summarizes preliminary research into uncertainty quantification for pattern ana- lytics within the context of the Pattern Analytics to Support High-Performance Exploitation and Reasoning (PANTHER) project. The primary focus of PANTHER was to make large quantities of remote sensing data searchable by analysts. The work described in this re- port adds nuance to both the initial data preparation steps and the search process. Search queries are transformed from does the specified pattern exist in the data? to how certain is the system that the returned results match the query? We show example results for both data processing and search, and discuss a number of possible improvements for each.
This progress report describes work being done at Sandia National Laboratories (SNL) to assess the localized corrosion performance of container/cask materials used in the interim storage of spent nuclear fuel (SNF). Of particular concern is stress corrosion cracking (SCC), by which a through-wall crack could potentially form in a canister outer wall over time intervals that are shorter than possible dry storage times. In order for SCC to occur, three criteria must be met. A corrosive environment must be present on the canister surface, the metal must susceptible to SCC, and sufficient tensile stress to support SCC must be present through the entire thickness of the canister wall. SNL is currently evaluating the potential for each of these criteria to be met.
The report focu ses on the modification of the optical properties of ice crystals due to atmospheric black car bon (BC) contamination : the objective is to advance the predictive capabilities of climate models through an improved understanding of the radiative properties of compound particles . The shape of the ice crystal (as commonly found in cirrus clouds and cont rails) , the volume fraction of the BC inclusion , and its location inside the crystal are the three factors examined in this study. In the multiscale description of this problem, where a small absorbing inclusion modifies the optical properties of a much la rger non - absorbing particle, state - of - the - art discretization techniques are combined to provide the best compromise of flexibility and accuracy over a broad range of sizes .
We want to organize a body of trajectories in order to identify, search for, classify and predict behavior among objects such as aircraft and ships. Existing compari- son functions such as the Fr'echet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as total distance traveled and distance be- tween start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generally be mapped easily to behaviors of interest to humans that are searching large databases. Most of these geometric features are invariant under rigid transformation. We demonstrate the use of different subsets of these features to iden- tify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories, predict destination and apply unsupervised machine learning algorithms.
Most spin qubit research to date has focused on manipulating single electron spins in quantum dots. However, hole spins are predicted to have some advantages over electron spins, such as reduced coupling to host semiconductor nuclear spins and the ability to control hole spins electrically using the large spin-orbit interaction. Building on recent advances in fabricating high-mobility 2D hole systems in GaAs/AlGaAs heterostructures at Sandia, we fabricate and characterize single hole transistors in GaAs. We demonstrate p-type double quantum dot devices with few-hole occupation, which could be used to study the physics of individual hole spins and control over coupling between hole spins, looking towards eventual applications in quantum computing. Intentionally left blank
Sandia journal manuscript; Not yet accepted for publication
Solaimani, Mohiuddin; Iftekhar, Mohammed; Khan, Latifur; Thuraisingham, Bhavani; Ingram, Joe B.
Anomaly detection refers to the identi cation of an irregular or unusual pat- tern which deviates from what is standard, normal, or expected. Such deviated patterns typically correspond to samples of interest and are assigned different labels in different domains, such as outliers, anomalies, exceptions, or malware. Detecting anomalies in fast, voluminous streams of data is a formidable chal- lenge. This paper presents a novel, generic, real-time distributed anomaly detection framework for heterogeneous streaming data where anomalies appear as a group. We have developed a distributed statistical approach to build a model and later use it to detect anomaly. As a case study, we investigate group anomaly de- tection for a VMware-based cloud data center, which maintains a large number of virtual machines (VMs). We have built our framework using Apache Spark to get higher throughput and lower data processing time on streaming data. We have developed a window-based statistical anomaly detection technique to detect anomalies that appear sporadically. We then relaxed this constraint with higher accuracy by implementing a cluster-based technique to detect sporadic and continuous anomalies. We conclude that our cluster-based technique out- performs other statistical techniques with higher accuracy and lower processing time.
Typically, transistors are modeled by the application of calibrated nominal and range models. These models consists of differing parameter values that describe the location and the upper and lower limits of a distribution of some transistor characteristic such as current capacity. Correspond- ingly, when using this approach, high degrees of accuracy of the transistor models are not expected since the set of models is a surrogate for a statistical description of the devices. The use of these types of models describes expected performances considering the extremes of process or transistor deviations. In contrast, circuits that have very stringent accuracy requirements require modeling techniques with higher accuracy. Since these accurate models have low error in transistor descriptions, these models can be used to describe part to part variations as well as an accurate description of a single circuit instance. Thus, models that meet these stipulations also enable the calculation of quantifi- cation of margins with respect to a functional threshold and uncertainties in these margins. Given this need, new model high accuracy calibration techniques for bipolar junction transis- tors have been developed and are described in this report.
In the field of archaeometry, it is not uncommon to be presented with art objects that contain inscriptions, signatures and other writings that are nearly impossible to read. Scanned microbeam PIXE offers an attractive approach to attack this problem, but even then the distribution of characteristic X-rays of the element(s) used in these writings can remain illegible. We show in this paper that two methods were used to reveal the inscription: first the use of a GUPIXWin, TRAUPIXE and AGLAEMap software suite enables to make quantitative analysis of each pixel, to visualize the results and to select X-ray peaks that could enable to distinguish letters. Then, the Automated eXpert Spectral Image Analysis (AXSIA) program developed at Sandia, which analyzes the x-ray intensity vs. Energy and (X, Y) position “datacubes”, was used to factor the datacube into 1) principle component spectral shapes and 2) the weighting images of these components. The specimen selected for this study was a silver plaque representing a scroll from the so-called “MerkelscheTafelaufsatz,” a centrepiece made by the Nuremberg goldsmith Wenzel Jamnitzer in 1549. X-ray radiography of the plaque shows lines of different silver thicknesses, meaning that a text has been removed. The PIXE analysis used a 3-MeV proton beam focused to 50μm and scanned across the sample on different areas of interest of several cm². This analysis showed major elements of Cu and Ag, and minor elements such as Pb, Au, Hg. X-ray intensity maps were then made by setting windows on the various x-ray peaks but the writing on the centrepiece was not revealed even if the map of Cu after data treatment at AGLAE enabled to distinguish some letters. The AXSIA program enabled to factor two main spectral shapes from the datacube that were quite similar and involved virtually all of the X-rays being generated. Nevertheless, small differences between these factors were observed for the Cu K X-rays, Pb, Bi and Au L X-rays. The plot of the factor with the highest Au signal gave also information on the shape of some letters. The comparison of the results obtained by the two methods shows that they both drastically improve the resolution and contrast of such writings and that each of the method can also bring different information on the composition and thus the techniques used for the writing.
We are studying PMDI polyurethane with a fast catalyst, such that filling and polymerization occur simultaneously. The foam is over-packed to tw ice or more of its free rise density to reach the density of interest. Our approach is to co mbine model development closely with experiments to discover new physics, to parameterize models and to validate the models once they have been developed. The model must be able to repres ent the expansion, filling, curing, and final foam properties. PMDI is chemically blown foam, wh ere carbon dioxide is pr oduced via the reaction of water and isocyanate. The isocyanate also re acts with polyol in a competing reaction, which produces the polymer. A new kinetic model is developed and implemented, which follows a simplified mathematical formalism that decouple s these two reactions. The model predicts the polymerization reaction via condensation chemis try, where vitrification and glass transition temperature evolution must be included to correctly predict this quantity. The foam gas generation kinetics are determined by tracking the molar concentration of both water and carbon dioxide. Understanding the therma l history and loads on the foam due to exothermicity and oven heating is very important to the results, since the kinetics and ma terial properties are all very sensitive to temperature. The conservation eq uations, including the e quations of motion, an energy balance, and thr ee rate equations are solved via a stabilized finite element method. We assume generalized-Newtonian rheology that is dependent on the cure, gas fraction, and temperature. The conservation equations are comb ined with a level set method to determine the location of the free surface over time. Results from the model are compared to experimental flow visualization data and post-te st CT data for the density. Seve ral geometries are investigated including a mock encapsulation part, two configur ations of a mock stru ctural part, and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Thoughts on m odel improvements are also discussed.
This report provides in-depth information and analysis to help create a technical road map for developing next-generation programming models and runtime systems that support Advanced Simulation and Computing (ASC) work- load requirements. The focus herein is on asynchronous many-task (AMT) model and runtime systems, which are of great interest in the context of "Oriascale7 computing, as they hold the promise to address key issues associated with future extreme-scale computer architectures. This report includes a thorough qualitative and quantitative examination of three best-of-class AIM] runtime systems – Charm-++, Legion, and Uintah, all of which are in use as part of the Centers. The studies focus on each of the runtimes' programmability, performance, and mutability. Through the experiments and analysis presented, several overarching Predictive Science Academic Alliance Program II (PSAAP-II) Asc findings emerge. From a performance perspective, AIV runtimes show tremendous potential for addressing extreme- scale challenges. Empirical studies show an AM runtime can mitigate performance heterogeneity inherent to the machine itself and that Message Passing Interface (MP1) and AM11runtimes perform comparably under balanced conditions. From a programmability and mutability perspective however, none of the runtimes in this study are currently ready for use in developing production-ready Sandia ASC applications. The report concludes by recommending a co- design path forward, wherein application, programming model, and runtime system developers work together to define requirements and solutions. Such a requirements-driven co-design approach benefits the community as a whole, with widespread community engagement mitigating risk for both application developers developers. and high-performance computing runtime systein
In the early stages of infection, patients develop non-specific or no symptoms at all. While waiting for identification of the infectious agent, precious window of opportunity for early intervention is lost. The standard diagnostics require affinity reagents and sufficient pathogen titers to reach the limit of detection. In the event of a disease outbreak, triaging the at-risk population rapidly and reliably for quarantine and countermeasure is more important than the identification of the pathogen by name. To expand Sandia's portfolio of Biological threat management capabilities, we will utilize Raman spectrometry to analyze immune subsets in whole blood to rapidly distinguish infected from non-infected, and bacterial from viral infection, for the purpose of triage during an emergency outbreak. The goal of this one year LDRD is to determine whether Raman spectroscopy can provide label-free detection of early disease signatures, and define a miniaturized Raman detection system meeting requirements for low- resource settings.
We have developed a new method to measure the composition of gaseous mixtures of any two hydrogen isotopes, as well as an inert gas component. When tritium is one of those hydrogen isotopes, there is usually some helium present, because the tritium decays to form helium at a rate of about 1% every 2 months. The usual way of measuring composition of these mixtures involves mass spectrometry, which involves bulky, energy-intensive, expensive instruments, including vacuum pumps that can quite undesirably disperse tritium. Our approach uses calorimetry of a small quantity of hydrogen-absorbing material to determine gas composition without consuming or dispersing the analytes. Our work was a proof of principle using a rather large and slow benchtop calorimeter. Incorporation of microfabricated calorimeters, such as those that have been developed in Sandia’s MicroChemLab program or that are now commercially available, would allow for faster measurements and a smaller instrument footprint.
Reactive multilayer foils have the potential to be used as local high intensity heat sources for a variety of applications. Much of the past research effort concerning these materials have focused on understanding the structure-property relationships of the foils that govern the energy released during a reaction. To enhance the ability of researchers to more rapidly develop technologies based on reactive multilayer foils, a deeper and more predictive understanding of the relationship between the heat released from the foil and microstructural evolution in the neighboring materials is needed. This work describes the development of a numerical model for the purpose of evaluating new foil-substrate combinations for screening and optimization. The model is experimentally validated using a commercially available Ni-Al multilayer foils and different alloys.
This report describes advances in electrolytes for lithium primary battery systems. Electrolytes were synthesized that utilize organosilane materials that include anion binding agent functionality. Numerous materials were synthesized and tested in lithium carbon monofluoride battery systems for conductivity, impedance, and capacity. Resulting electrolytes were shown to be completely non-flammable and showed promise as co-solvents for electrolyte systems, due to low dielectric strength.
Price, Laura L.; Gross, Mike; Prouty, Jeralyn; Rigali, Mark J.; Craig, Brian; Han, Zenghu; Lee, John H.; Liu, Yung; Pope, Ron; Connolly, Kevin; Feldman, Matt; Jarrell, Josh; Radulescu, Georgeta; Scaglione, John; Wells, Alan
The mission of the United States Department of Energy's Office of Environmental Management is to complete the safe cleanup of the environmental legacy brought about from five decades of nuclear weapons development and go vernment - sponsored nuclear energy re search. S ome of the waste s that that must be managed have be en identified as good candidates for disposal in a deep borehole in crystalline rock (SNL 2014 a). In particular, wastes that can be disposed of in a small package are good candidates for this disposal concept. A canister - based system that can be used for handling these wastes during the disposition process (i.e., storage, transfers, transportation, and disposal) could facilitate the eventual disposal of these wastes. This report provides information for a program plan for developing specifications regarding a canister - based system that facilitates small waste form packaging and disposal and that is integrated with the overall efforts of the DOE's Office of Nuclear Energy Used Fuel Dis position Camp aign's Deep Borehole Field Test . Groundwork for Universal Ca nister System Development September 2015 ii W astes to be considered as candidates for the universal canister system include capsules containing cesium and strontium currently stored in pools at the Hanford Site, cesium to be processed using elutable or nonelutable resins at the Hanford Site, and calcine waste from Idaho National Laboratory. The initial emphasis will be on disposal of the cesium and strontium capsules in a deep borehole that has been drilled into crystalline rock. Specifications for a universal canister system are derived from operational, performance, and regulatory requirements for storage, transfers, transportation, and disposal of radioactive waste. Agreements between the Department of Energy and the States of Washington and Idaho, as well as the Deep Borehole Field Test plan provide schedule requirements for development of the universal canister system . Future work includes collaboration with the Hanford Site to move the cesium and strontium capsules into dry storage, collaboration with the Deep Borehole Field Tes t to develop surface handling and emplacement techniques and to develop the waste package design requirements, developing universal canister system design options and concepts of operations, and developing system analysis tools. Areas in which f urther research and development are needed include material properties and structural integrity, in - package sorbents and fillers, waste form tolerance to heat and postweld stress relief, waste package impact limiters, sensors, cesium mobility under downhol e conditions, and the impact of high pressure and high temperature environment on seals design.
This report describes the work and results of the initial verification and validation (V&V) of the beta release of the Razorback code. Razorback is a computer code designed to simulate the operation of a research reactor (such as the Annular Core Research Reactor (ACRR)) by a coupled numerical solution of the point reactor kinetics equations, the energy conservation equation for fuel element heat transfer, and the mass, momentum, and energy conservation equations for the water cooling of the fuel elements. This initial V&V effort was intended to confirm that the code work to-date shows good agreement between simulation and actual ACRR operations, indicating that the subsequent V&V effort for the official release of the code will be successful.
This report presents efforts to develop the use of in situ naturally-occurring noble gas tracers to evaluate transport mechanisms and deformation in shale hydrocarbon reservoirs. Noble gases are promising as shale reservoir diagnostic tools due to their sensitivity of transport to: shale pore structure; phase partitioning between groundwater, liquid, and gaseous hydrocarbons; and deformation from hydraulic fracturing. Approximately 1.5-year time-series of wellhead fluid samples were collected from two hydraulically-fractured wells. The noble gas compositions and isotopes suggest a strong signature of atmospheric contribution to the noble gases that mix with deep, old reservoir fluids. Complex mixing and transport of fracturing fluid and reservoir fluids occurs during production. Real-time laboratory measurements were performed on triaxially-deforming shale samples to link deformation behavior, transport, and gas tracer signatures. Finally, we present improved methods for production forecasts that borrow statistical strength from production data of nearby wells to reduce uncertainty in the forecasts.
Two of the central challenges in the mechanical design of components in nuclear systems are the dissipation of energy from external shocks and the localization of energy in energetic materials. This research seeks to address these problems by developing a patterned granular microstructure that can be optimized to direct or impede the transfer of energy carried by stress waves. Such structures require the development of a manufacturing technique that can yield perfectly ordered lattices. Two branches of research are detailed here: the development of a sphere-by-sphere additive manufacturing technique, and the development of a framework for modeling the technique in order to guide future improvements. Proof of concept of the method is demonstrated, and recommendations for future work are made.
The reproducing kernel particle method (RKPM) is a meshless method used to solve general boundary value problems using the principle of virtual work. RKPM corrects the kernel approximation by introducing reproducing conditions which force the method to be complete to arbritrary order polynomials selected by the user. Effort in recent years has led to the implementation of RKPM within the Sierra/SM physics software framework. The purpose of this report is to investigate convergence of RKPM for verification and validation purposes as well as to demonstrate the large deformation capability of RKPM in problems where the finite element method is known to experience difficulty. Results from analyses using RKPM are compared against finite element analysis. A host of issues associated with RKPM are identified and a number of potential improvements are discussed for future work.
Finite-element thermal stress modeling at the glass-ceramic to metal (GCtM) interface was conducted assuming heterogeneous glass-ceramic microstructure. The glass-ceramics were treated as composites consisting of high expansion silica crystalline phases dispersed in a uniform residual glass. Interfacial stresses were examined for two types of glass-ceramics. One was designated as SL16 glass -ceramic, owing to its step-like thermal strain curve with an overall coefficient of thermal expansion (CTE) at 16 ppm/ºC. Clustered Cristobalite is the dominant silica phase in SL16 glass-ceramic. The other, designated as NL16 glass-ceramic, exhibited clusters of mixed Cristobalite and Quartz and showed a near-linear thermal strain curve with a same CTE value.
Synthesis of ditopic imidazoliums was achieved using a modular step-wise procedure. The procedure itself is amenable to a wide array of functional groups that can be incorporated into the imidazolium architecture. The resulting compounds range from ditopic zwitterions to highly-soluble dicationic aromatics
This work investigated the effects of Al2O3 ALD coatings on the performance and thermal abuse tolerance of graphite based anodes and Li(NixMnyCoz)O2 (NMC) based cathodes. It was found that 5 cycles of Al2O3 ALD on the graphite anode increased the onset temperature of thermal runaway by approximately 20 °C and drastically reduced the anode’s contribution to the overall amount of heat released during thermal runaway. Although Al2O3 ALD improves the cycling stability of NMC based cathodes, the thermal abuse tolerance was not greatly improved. A series of conductive aluminum oxide/carbon composites were created and characterized as potential thicker protective coatings for use on NMC based cathode materials. A series of electrodes were coated with manganese monoxide ALD to test the efficacy of an oxygen scavenging coating on NMC based cathodes.