In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor- ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.
The SIERRA Low Mach Module: Fuego along with the SIERRA Participating Media Radiation Module: Syrinx, henceforth referred to as Fuego and Syrinx, respectively, are the key elements of the ASCI fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Syrinx represents the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.
The SIERRA Low Mach Module: Fuego along with the SIERRA Participating Media Radiation Module: Syrinx, henceforth referred to as Fuego and Syrinx, respectively, are the key elements of the ASCI fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Syrinx represents the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.
Aria is a Galerkin fnite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process fows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( %3C 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.
The goal of this LDRD is to develop a quantum nanophotonics capability that will allow practical control over electron (hole) and photon confinement in more than one dimension. We plan to use quantum dots (QDs) to control electrons, and photonic crystals to control photons. InGaN QDs will be fabricated using quantum size control processes, and methods will be developed to add epitaxial layers for hole injection and surface passivation. We will also explore photonic crystal nanofabrication techniques using both additive and subtractive fabrication processes, which can tailor photonic crystal properties. These two efforts will be combined by incorporating the QDs into photonic crystal surface emitting lasers (PCSELs). Modeling will be performed using finite-different time-domain and gain analysis to optimize QD-PCSEL designs that balance laser performance with the ability to nano-fabricate structures. Finally, we will develop design rules for QD-PCSEL architectures, to understand their performance possibilities and limits.
Develop an understanding of the evolution of glassy polymer mechanical response during aging and the mechanisms associated with that evolution. That understanding will be used to develop constitutive models to assess the impact of stress evolution in encapsulants on NW designs.
This report documents the ASC/ATDM Kokkos deliverable "Production Portable Dy- namic Task DAG Capability." This capability enables applications to create and execute a dynamic task DAG ; a collection of heterogeneous computational tasks with a directed acyclic graph (DAG) of "execute after" dependencies where tasks and their dependencies are dynamically created and destroyed as tasks execute. The Kokkos task scheduler executes the dynamic task DAG on the target execution resource; e.g. a multicore CPU, a manycore CPU such as Intel's Knights Landing (KNL), or an NVIDIA GPU. Several major technical challenges had to be addressed during development of Kokkos' Task DAG capability: (1) portability to a GPU with it's simplified hardware and micro- runtime, (2) thread-scalable memory allocation and deallocation from a bounded pool of memory, (3) thread-scalable scheduler for dynamic task DAG, (4) usability by applications.
In this SAND report, we discuss various authorship attribution techniques for social media platforms to identify separate accounts controlled by one user. We look at three main categories of techniques: stylometric, semantic, and temporal, and we test several algorithms in each category. We then combine these techniques to increase predictive power, and perform cross-platform account verification on Twitter and Stack Exchange datasets. Additionally, we briefly examine graphical techniques, and analyze the predictive power of unsupervised approaches. Finally, we apply our techniques to unbalanced data sets. Our experiments reveal that normalized compression distance shows great promise in analyzing social media.
Sandia National Laboratories has tested and evaluated a new preamplifier, the Guralp Preamplifier for GS13, manufactured by Guralp. These preamplifiers are used to interface between Guralp digitizers and Geotech GS13 Seismometers. The purpose of the preamplifier evaluation was to measure the performance characteristics in such areas as power consumption, input impedance, sensitivity, full scale, self-noise, dynamic range, system noise, response, passband, and timing. The Guralp GS13 Preamplifiers are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO).
The energy-dependent probability density of tunneled carrier states for arbitrarily specified longitudinal potential-energy profiles in planar bipolar devices is numerically computed using the scattering method. Results agree accurately with a previous treatment based on solution of the localized eigenvalue problem, where computation times are much greater. These developments enable quantitative treatment of tunneling-assisted recombination in irradiated heterojunction bipolar transistors, where band offsets may enhance the tunneling effect by orders of magnitude. The calculations also reveal the density of non-tunneled carrier states in spatially varying potentials, and thereby test the common approximation of uniform- bulk values for such densities.
In 2017, four U.S. National Laboratories collaborated on behalf of DOE/NNSA to explore the safeguards knowledge retention problem, identify possible approaches, and develop a strategy to address it. The one-year effort consisted of four primary tasks. First, the project sought to identify critical safeguards information at risk of loss. Second, a survey and workshop were conducted to assess nine U.S. National Laboratories' efforts to determine current safeguards knowledge retention practices and challenges, and identify best practices. Third, specific tools were developed to identify and predict critical safeguards knowledge gaps and how best to recruit in order to fill those gaps. Finally, based on findings from the first three tasks and research on other organizational approaches to address similar issues, a strategy was developed on potential knowledge retention methods, customized HR policies, and best practices that could be implemented across the National Laboratory Complex.
Hydrodynamic instability growth is a fundamentally limiting process in many applications. In High Energy Density Physics (HEDP) systems such as inertial confinement fusion implosions and stellar explosions, hydro instabilities can dominate the evolution of the object and largely determine the final state achievable. Of particular interest is the process by which instabilities cause perturbations at a density or material interface to grow nonlinearly, introducing vorticity and eventually causing the two species to mix across the interface. Although quantifying instabilities has been the subject of many investigations in planar geometry, few have been done in converging geometry. During FY17, the team executed six convergent geometry instability experiments. Based on earlier results, the platform was redesigned and improved with respect to load centering at installation making the installation reproducible and development of a new 7.2 keV, Co He-a backlighter system to better penetrate the liner. Together, the improvements yielded significantly improved experimental results. The results in FY17 demonstrate the viability of using experiments on Z to quantify instability growth in cylindrically convergent geometry. Going forward, we will continue the partnership with staff and management at LANL to analyze the past experiments, compare to hydrodynamics growth models, and design future experiments.
This project was inspired by two needs. The first is a need for tools to help scientists and engineers to design effective data visualizations for communicating information, whether to the user of a system, an analyst who must make decisions based on complex data, or in the context of a technical report or publication. Most scientists and engineers are not trained in visualization design, and they could benefit from simple metrics to assess how well their visualization's design conveys the intended message. In other words, will the most important information draw the viewer's attention? The second is the need for cognition-based metrics for evaluating new types of visualizations created by researchers in the information visualization and visual analytics communities. Evaluating visualizations is difficult even for experts. However, all visualization methods and techniques are intended to exploit the properties of the human visual system to convey information efficiently to a viewer. Thus, developing evaluation methods that are rooted in the scientific knowledge of the human visual system could be a useful approach. In this project, we conducted fundamental research on how humans make sense of abstract data visualizations, and how this process is influenced by their goals and prior experience. We then used that research to develop a new model, the Data Visualization Saliency Model, that can make accurate predictions about which features in an abstract visualization will draw a viewer's attention. The model is an evaluation tool that can address both of the needs described above, supporting both visualization research and Sandia mission needs.
The thermal performance of commercial nuclear spent fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Carefully measured data sets generated from testing of full sized casks or smaller cask analogs are widely recognized as vital for validating these models. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask in part by increasing the efficiency of internal conduction pathways and by increasing the internal convection through greater canister helium pressure. These same canistered cask systems rely on ventilation between the canister and the overpack to convect heat away from the canister to the environment for both aboveground and belowground configurations. While several testing programs have been previously conducted, these earlier validation attempts did not capture the effects of elevated helium pressures or accurately portray the external convection of aboveground and belowground canistered dry cask systems. The purpose of this investigation was to produce validation-quality data that can be used to test the validity of the modeling presently used to determine cladding temperatures in modern vertical dry casks. These cladding temperatures are critical to evaluate cladding integrity throughout the storage cycle. To produce these data sets under well-controlled boundary conditions, the dry cask simulator (DCS) was built to study the thermal-hydraulic response of fuel under a variety of heat loads, internal vessel pressures, and external configurations. An existing electrically heated but otherwise prototypic BWR Incoloy-clad test assembly was deployed inside of a representative storage basket and cylindrical pressure vessel that represents a vertical canister system. The symmetric single assembly geometry with well-controlled boundary conditions simplified interpretation of results. Two different arrangements of ducting were used to mimic conditions for aboveground and belowground storage configurations for vertical, dry cask systems with canisters. Transverse and axial temperature profiles were measured throughout the test assembly. The induced air mass flow rate was measured for both the aboveground and belowground configurations. In addition, the impact of cross-wind conditions on the belowground configuration was quantified. Over 40 unique data sets were collected and analyzed for these efforts. Fourteen data sets for the aboveground configuration were recorded for powers and internal pressures ranging from 0.5 to 5.0 kW and 0.3 to 800 kPa absolute, respectively. Similarly, fourteen data sets were logged for the belowground configuration starting at ambient conditions and concluding with thermal-hydraulic steady state. Over thirteen tests were conducted using a custom-built wind machine. The results documented in this report highlight a small, but representative, subset of the available data from this test series. This addition to the dry cask experimental database signifies a substantial addition of first-of-a-kind, high-fidelity transient and steady-state thermal-hydraulic data sets suitable for CFD model validation.
The SPARC (Sandia Parallel Aerodynamics and Reentry Code) will provide nuclear weapon qualification evidence for the random vibration and thermal environments created by re-entry of a warhead into the earth’s atmosphere. SPARC incorporates the innovative approaches of ATDM projects on several fronts including: effective harnessing of heterogeneous compute nodes using Kokkos, exascale-ready parallel scalability through asynchronous multi-tasking, uncertainty quantification through Sacado integration, implementation of state-of-the-art reentry physics and multiscale models, use of advanced verification and validation methods, and enabling of improved workflows for users. SPARC is being developed primarily for the Department of Energy nuclear weapon program, with additional development and use of the code is being supported by the Department of Defense for conventional weapons programs.
Understanding the data structures employed by a program is important for reverse engineering activities and can improve the results of automated software analysis techniques. In a compiled binary, access to data structure fields and array indices defined in the source program are replaced by raw pointer arithmetic. We present a representation for capturing the essential details of how a program accesses memory regions, which we call a Memory Access Graph (MAG), and a static analysis for automatically extracting this information from a program binary. The static analysis to extract the MAGs from the program is straightforward and does not require sophisticated integer or pointer analysis. The MAGs are readily understood by reverse engineers; they are generally able to perceive the data structure definition corresponding to a MAG. We briefly discuss automatic extraction of structure definitions outlining some of the difficulties in doing so.
The Nuclear Security Enterprise, managed by the National Nuclear Security Administration - a semiautonomous agency within the Department of Energy - has been associated with numerous assessments with respect to the estimating, management capabilities, and practices pertaining to nuclear weapon modernization efforts. This report identifies challenges in estimating and analyzing the Nuclear Security Enterprise through an analysis of analogous timeframe conditions utilizing two types of nuclear weapon data - (1) a measure of effort and (2) a function of time. The analysis of analogous timeframe conditions that utilizes only two types of nuclear weapon data yields four summary observations that estimators and analysts of the Nuclear Security Enterprise will find useful.
The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. To resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. In this study, the authors demonstrate the use of concurrent multi- scale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled with a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J 2 plas- ticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. Beyond cases studies in concurrent multiscale, we explore progress in crystal plastic- ity through modular designs, solution methodologies, model verification, and extensions to Sierra/SM and manycore applications. Advances in conformal microstructures having both hexahedral and tetrahedral workflows in Sculpt and Cubit are highlighted. A structure-property case study in two-phase metallic composites applies the Materials Knowledge System to local metrics for void evolution. Discussion includes lessons learned, future work, and a summary of funded efforts and proposed work. Finally, an appendix illustrates the need for two-way coupling through a single degree of freedom.
A cryogenically cooled hardware platform has been developed and commissioned on the Z Facility at Sandia National Laboratories in support of the Magnetized Liner Inertial Fusion (MagLIF) Program. MagLIF is a magneto-inertial fusion concept that employs a magnetically imploded metallic tube (liner) to compress and inertially confine premagnetized and preheated fusion fuel. The fuel is preheated using a ∼2 kJ laser that must pass through a ∼1.5-3.5-μm-thick polyimide "window" at the target's laser entrance hole (LEH). As the terawatt-class laser interacts with the dense window, laser plasma instabilities (LPIs) can develop, which reduce the preheat energy delivered to the fuel, initiate fuel contamination, and degrade target performance. Cryogenically cooled targets increase the parameter space accessible to MagLIF target designs by allowing nearly 10 times thinner windows to be used for any accessible gas density. Thinner LEH windows reduce the deleterious effects of difficult to model LPIs. The Z Facility's cryogenic infrastructure has been significantly altered to enable compatibility with the premagnetization and fuel preheat stages of MagLIF. The MagLIF cryostat brings the liquid helium coolant directly to the target via an electrically resistive conduit. This design maximizes cooling power while allowing rapid diffusion of the axial magnetic field supplied by external Helmholtz-like coils. A variety of techniques have been developed to mitigate the accumulation of ice from vacuum chamber contaminants on the cooled LEH window, as even a few hundred nanometers of ice would impact laser energy coupling to the fuel region. The MagLIF cryostat has demonstrated compatibility with the premagnetization and preheat stages of MagLIF and the ability to cool targets to liquid deuterium temperatures in approximately 5 min.
This work reports the utilization of a recently developed film, ScAlN, as a silicon etch mask offering significant improvements in high etch selectivity to silicon. Utilization of ScAlN as a fluorine chemistry based deep reactive ion etch mask demonstrated etch selectivity at 23 550:1, four times better than AlN, 11 times better than Al2O3, and 148 times better than silicon dioxide with significantly less resputtering at high bias voltage than either Al2O3 or AlN. Ellipsometry film thickness measurements show less than 0.3 nm/min mask erosion rates for ScAlN. Micromasking of resputtered Al for Al2O3, AlN, and ScAlN etch masks is also reported here, utilizing cross-sectional scanning electron microscope and confocal microscope roughness measurements. With lower etch bias, the reduced etch rate can be optimized to achieve a trench bottom surface roughness that is comparable to SiO2 etch masks. Etch mask selectivity enabled by ScAlN is likely to make significant improvements in microelectromechanical systems, wafer level packaging, and plasma dicing of silicon.
The ability to simulate wireless networks at large-scale for meaningful amount of time is considerably lacking in today's network simulators. For this reason, many published work in this area often limit their simulation studies to less than a 1,000 nodes and either over-simplify channel characteristics or perform studies over time scales much less than a day. In this report, we show that one can overcome these limitations and study problems of high practical consequence. This work presents two key contributions to high fidelity simulation of large-scale wireless networks: (a) wireless simulations can be sped up by more than 100X in runtime using ideas from spatial indexing algorithms and clipping of negligible signals and (b) clustering and task-oriented programming paradigm can be used to reduce inter- process communication in a parallel discrete event simulation resulting in a better scaling efficiency.
Radiated power calculation approaches for practical scenarios of incomplete high- density interface characterization information and incomplete incident power information are presented. The suggested approaches build upon a method that characterizes power losses through the definition of power loss constant matrices. Potential radiated power estimates include using total power loss information, partial radiated power loss information, worst case analysis, and statistical bounding analysis. A method is also proposed to calculate radiated power when incident power information is not fully known for non-periodic signals at the interface. Incident data signals are modeled from a two-state Markov chain where bit state probabilities are derived. The total spectrum for windowed signals is postulated as the superposition of spectra from individual pulses in a data sequence. Statistical bounding methods are proposed as a basis for the radiated power calculation due to the statistical calculation complexity to find a radiated power probability density function.
The purpose of the scenarios workshop held for the Civilian Nuclear component of the Global Nuclear Assured Security Mission Integration Initiative was to identify sources of risk in the global civilian nuclear enterprise. The risks identified are inadequately addressed through current technical measures, regulatory frameworks and institutions and should be considered for further research. The workshop participants also developed four high level scenarios describing different sequences of events that could result in radiological releases, widespread loss of electric power, and loss of public confidence in segments of the nuclear industry. The scenarios are intended for further analysis and as the basis for simulation exercises.
IEEE Transactions on Microwave Theory and Techniques
Mincey, John; Silva-Martinez, Jose; Karsilayan, Aydin I.; Rodenbeck, Christopher T.
In this paper, a coherent subsampling digitizer for pulsed Doppler radar systems is proposed. Prior to transmission, the radar system modulates the RF pulse with a known pseudorandom binary phase shift keying (BPSK) sequence. Upon reception, the radar digitizer uses a programmable sample-and-hold circuit to multiply the received waveform by a properly time-delayed version of the known a priori BPSK sequence. This operation demodulates the desired echo signal while suppressing the spectrum of all in-band noncorrelated interferers, making them appear as noise in the frequency domain. The resulting demodulated narrowband Doppler waveform is then subsampled at the IF frequency by a delta-sigma modulator. Because the digitization bandwidth within the delta-sigma feedback loop is much less than the input bandwidth to the digitizer, the thermal noise outside of the Doppler bandwidth is effectively filtered prior to quantization, providing an increase in signal-to-noise ratio (SNR) at the digitizer's output compared with the input SNR. In this demonstration, a delta-sigma correlation digitizer is fabricated in a 0.18-μm CMOS technology. The digitizer has a power consumption of 1.12 mW with an IIP3 of 7.5 dBm. The digitizer is able to recover Doppler tones in the presence of blockers up to 40 dBm greater than the Doppler tone.
A distributed impedance 'field cage' structure is proposed and evaluated for electric field control in GaN-based, lateral high electron mobility transistors operating as kilovolt-range power devices. In this structure, a resistive voltage divider is used to control the electric field throughout the active region. The structure complements earlier proposals utilizing floating field plates that did not employ resistively connected elements. Transient results, not previously reported for field plate schemes using either floating or resistively connected field plates, are presented for ramps of dVds/dt = 100 V/ns. For both dc and transient results, the voltage between the gate and drain is laterally distributed, ensuring that the electric field profile between the gate and drain remains below the critical breakdown field as the source-to-drain voltage is increased. Our scheme indicates promise for achieving the breakdown voltage scalability to a few kilovolts.
Our study details the derivation of the nonlinear equations of motion for the axial, biaxial bending and torsional vibrations of an aeroelastic cantilever undergoing rigid body (pitch) rotation at the base. The primary attenstion is focussed on the geometric nonlinearities of the system, whereby the aeroelastic load is modeled by the theory of linear quasisteady aerodynamics. This modelling effort is intended to mimic the wind-tunnel experimental setup at the Royal Military College of Canada. While the derivation closely follows the work of Hodges and Dowell [1] for rotor blades, this aeroelastic system contains new inertial terms which stem from the fundamentally different kinematics than those exhibited by helicopter or wind turbine blades. Using the Hamilton’s principle, a set of coupled nonlinear partial differential equations (PDEs) and an ordinary differential equation (ODE) are derived which describes the coupled axial-bending-bending-torsion-pitch motion of the aeroelastic cantilever with the pitch rotation. The finite dimensional approximation of the coupled system of PDEs are obtained using the Galerkin projection, leading to a coupled system of ODEs. Subsequently, these nonlinear ODEs are solved numerically using the built-in MATLAB implicit ODE solver and the associated numerical results are compared with those obtained using Houbolt’s method. It is demonstrated that the system undergoes coalescence flutter, leading to a limit cycle oscillation (LCO) due to coupling between the rigid body pitching mode and teh flexible mode arising from the flapwise bending motion.
In this study, solubility measurements on tri-calcium di-citrate tetrahydrate [Ca3[C3H5O(COO)3]2•4H2O, abbreviated as Ca3[Citrate]2•4H2O] as a function of ionic strength are conducted in NaCl solutions up to I = 5.0 mol•kg–1 and in MgCl2 solutions up to I = 7.5 mol•kg–1, at room temperature (22.5 ± 0.5°C). The solubility constant (log K$0\atop{sp}$) for Ca3[Citrate]2•4H2O and formation constant (logβ$0\atop{1}$) for Ca[C3H5O(COO)3]–Ca3[C3H5O(COO)3]2•4H2O (earlandite) = 3Ca2+ + 2[C3H5O(COO)3]3– + 4H2O (1) Ca2+ + [C3H5O(COO)3]3– = Ca[C3H5O(COO)3]– (2) are determined as –18.11 ± 0.05 and 4.97 ± 0.05, respectively, based on the Pitzer model with a set of Pitzer parameters describing the specific interactions in NaCl and MgCl2 media.
For this study, the interactions of lead with citrate and ethylenediaminetetraacetate (EDTA) are investigated based on solubility measurements as a function of ionic strength at room temperature (22.5 ± 0.5°C) in NaCl and MgCl2 solutions. The formation constants (log β10 ) for Pb[C3H5O(COO)3]– (abbreviated as PbCitrate–) and Pb[(CH2COO)2N(CH2)2N(CH2COO)2)]2– (abbreviated as PbEDTA2–) Pb2+ + [C3H5O(COO)3]3– = Pb[C3H5O(COO)3]– (1) Pb2+ + (CH2COO)2N(CH2)2N(CH2COO)2)4- = Pb[(CH2COO)2N(CH2)2N(CH2COO)2)]2– (2) are evaluated as 7.28 ± 0.18 (2σ) and 20.00 ± 0.20 (2σ), respectively, with a set of Pitzer parameters describing the specific interactions in NaCl and MgCl2 media. Based on these parameters, the interactions of lead with citrate and EDTA in various low temperature environments can be accurately modelled.
Significant quantities of water are produced during enhanced oil recovery making these “produced water” streams attractive candidates for treatment and reuse. However, high concentrations of dissolved silica raise the propensity for fouling. In this paper, we report the design and economic analysis for a new ion exchange process using calcined hydrotalcite (HTC) to remove silica from water. This process improves upon known technologies by minimizing sludge product, reducing process fouling, and lowering energy use. Process modeling outputs included raw material requirements, energy use, and the minimum water treatment price (MWTP). Monte Carlo simulations quantified the impact of uncertainty and variability in process inputs on MWTP. These analyses showed that cost can be significantly reduced if the HTC materials are optimized. Specifically, R&D improving HTC reusability, silica binding capacity, and raw material price can reduce MWTP by 40%, 13%, and 20%, respectively. Optimizing geographic deployment further improves cost competitiveness.
The objective of the Crystalline Disposal R&D control account is to advance our understanding of long-term disposal of used fuel in crystalline rocks and to develop necessary experimental and computational capabilities to evaluate various disposal concepts in such media.
Current models for hydrogen embrittlement rely on adjustable parameters to correct for uncertainties in crack tip stress fields and subsequent H2-concentrations. Techniques are needed to quantify these concentrations ahead of crack tips in mechanically loaded materials, providing data for model calibration and validation. The goal of this work was to establish advanced analytical techniques to detect and quantitatively measure hydrogen ahead of cracks in stressed solids. Two advanced analytical techniques, kelvin probe force microscopy (KPFM) and nuclear reaction analysis (NRA), were explored to evaluate the feasibility to provide qualitative and quantitative H2-concentration fields in geometries designed to be 'loaded' while under observation. The feasibility of the KPFM technique at detecting hydrogen was evaluated using electrochemically precharged hydrogen as well as a mixed hydrogen gas atmosphere. The KPFM technique was able to detect the presence of elevated stress and hydrogen concentrations ahead of a tensile loaded crack tip. The results suggest that KPFM is a viable technique for qualitatively imaging changes in stress and hydrogen concentrations on the scale needed to inform predictive models. KPFM could be used to provide local stress and hydrogen variations associated with hydrogen traps or different phases which require sensitive measurements on the micron scale. NRA provided quantitative measurements of the hydrogen-isotope deuterium ahead of a tensile loaded notch, however, the vacancy formation due to the incident high energy He 3 beam overwhelmed stress-assisted enhancement of deuterium concentrations such that the effect of stress was overshadowed in this analysis. Modeling of the chemo- mechanical hydrogen concentration change was used to verify this observation.
The energy density of nonaqueous redox flow batteries is often limited by the concentration of the redox active species soluble in solution. A possible route to increasing the this energy density is through the use of energy-dense solid materials such as polyoxometalates, LiFePO4, or LixTi02. These solid materials can be contained in canisters through which an electrolyte with dissolved redox-active species is flowed. The redox potentials for the flowing species are chosen specifically such that they mediate the chemical reduction and oxidation of the solid components. This strategy is advantageous in that it allows for independent optimization of the flow electrolyte (e.g. for low viscosity, high charging rate) and the solid energy storing media (e.g. high energy density). This report summarizes results using a variety of redox active organic and metalorganic species to mediate the oxidation and reduction of polyoxometalate and Li-ion battery chemistries in a redox flow battery system.
Deep borehole disposal (DBD) has been suggested as an option for disposing spent nuclear fuel in a number of countries, including several countries that are subject to international safeguards. DBD presents some distinct challenges for safeguards compared to a conventional mined geological repository (MGR), including the ability to verify declared design information about the borehole. The ability to verify a borehole's design is crucial for assuring that spent fuel or other accountable nuclear materials are disposed as declared in a borehole of known and verifiable design. This study reviews existing commercial off-the-shelf (COTS) borehole inspection tools currently used by the drilling industry, and evaluates the capabilities of those COTS inspection tools against how well they can meet potential needs and requirements of Design Information Verification (DIV) inspections for international safeguards. The study provides recommendations for several promising COTS borehole inspection tools that might be used for DIV safeguards inspections and recommends possible modifications and future testing
Progress toward quantitative measurements and simulations of 3D, temporally resolved aerodynamic induced liquid atomization is reported. Columns of water and galinstan (liquid metal at room temperature) are subjected to a step change in relative gas velocity within a shock tube. Breakup morphologies are shown to closely resemble previous observations of spherical drops. The 3D position, size, and velocity of secondary fragments are quantified by a high-speed digital inline holography (DIH) system developed for this measurement campaign. For the first time, breakup dynamics are temporally resolved at 100 kHz close to the atomization zone where secondary drops are highly non-spherical. Experimental results are compared to interface capturing simulations using a combined level set moment of fluid approach (CLSMOF). Initial simulation results show good agreement with observed breakup morphologies and rates of deformation.
Graphs are widely used to model relationships in a wide variety of domains such as sociology, bioinformatics, infrastructure, the WWW, to name a few. One of the key observations is that while real-world graphs are often globally sparse, they are locally dense. In other words, the average degree is often quite small (say at most 10 in a million vertex graph), but vertex neighborhoods are often dense. Finding dense subgraphs is a critical aspect of graph mining It has been used for finding communities and spam link farms in web graphs, graph visualization, real-time story identification, DNA motif detection in biological networks, finding correlated genes, epilepsy prediction, finding price value motifs in financial data, graph compression, distance query indexing, and increasing the throughput of social networking site servers. However, most standard formulations of this problem (like clique, quasi-clique, k-densest subgraph) are NP-hard. Furthermore, current dense subgraph finding algorithms usually optimize some objective, and only find a few such subgraphs without providing any structural relations, whereas the goal is rarely to find the "true optimum," but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine relationships among them. In this project, we first aim to devise algorithms and provide 3 implementations with nice visualizations to find the hierarchy between dense subgraphs, and then understand the structure of the hierarchy to gain more insight on the hidden patterns in real-world networks. Another important aspects in graph analysis is the temporal nature of networks. Networks evolve over time and in many applications data arrives at a high velocity, and thus it is important to design algorithms that can process data efficiently. We report three main results towards identifying dense structures in large evolving graphs. First, we will show how the hierarchical connectedness structure can be maintained efficiently, where connectedness is defined by increasing levels of connectivity strength. Next, we present dense structure can be identified in bipartite graphs without building projection graphs. And finally, we present a new method for peeling algorithms This new approach avoids sequential nature of peeling algorithms and is amenable to parallelization, which is crucial for processing high velocity data.
A three year LDRD was undertaken to look at the feasibility of using magnetic sensing to determine flows within sealed vessels at high temperatures and pressures. Uniqueness proofs were developed for tracking of single magnetic particles with multiple sensors. Experiments were shown to be able to track up to 3 dipole particles undergoing rigid-body rotational motion. Temperature was wirelessly monitored using magnetic particles in static and predictable motions. Finally high-speed vibrational motion was tracked using magnetic particles. Ideas for future work include using small particles for measuring vorticity and better calibration methods for tracking multiple particles.
The experimental breeder reactor (EBR-II) used fuel with a layer of sodium surrounding the uranium-zirconium fuel to improve heat transfer. Disposing of this EBR-II used fuel in a geologic repository without treatment is not prudent because of the potentially energetic reaction of the sodium with water. In 2000, the US Department of Energy decided to treat the EBR-II sodium-bonded used fuel in an electrorefiner (ER), which produces a metallic waste, mostly from the cladding. The salt remaining in the ER contains most of the actinides and fission products. Two baseline waste forms were proposed for disposal in a mined repository; the metallic waste, which was to be cast into ingots, and the ER salt waste, which was to be further treated to produce a ceramic waste form. However, alternative disposal pathways for metallic and salt waste streams are being investigated that may reduce the complexity. For example, performance assessments show that both mined repositories in salt and deep boreholes in basement crystalline rock can easily accommodate the ER salt waste without treating it to form a ceramic waste form. Hence the focus of a direct disposal option, as described herein, is now on the feasibility of packaging the ER salt waste in the near term such that it can be transported to a repository in the future without repackaging. A vessel for direct disposal of ER salt waste has been previously proposed, designed, and a prototype manufactured based on desirable features for use in the hot cell. The reported analysis focused on the feasibility of transporting this proposed vessel and whether any issues would suggest that a smaller or larger size is more appropriate. Specifically, three issues are addressed (1) shielding necessary to reduce doses to acceptable levels; (2) the criticality potential and the ease which it can be shown to be inconsequential, and (3) temperatures of the containers in relation to acceptable cask limits. The generally positive results demonstrate that direct disposal of ER in the proposed packaging is feasible without the need to secure funding to modify the facility.
This report is an outcome of the ASC ATDM Level 2 Milestone 6015: Asynchronous Many-Task Software Stack Demonstration. It comprises a summary and in depth analysis of DARMA and a DARMA-compliant Asynchronous Many-Task (AMT) runtime software stack. Herein performance and productivity of the over- all approach are assessed on benchmarks and proxy applications representative of the Sandia ATDM applications. As part of the effort to assess the perceived strengths and weaknesses of AMT models compared to more traditional methods, experiments were performed on ATS-1 (Advanced Technology Systems) test bed machines and Trinity. In addition to productivity and performance assessments, this report includes findings on the generality of DARMAs backend API as well as findings on interoperability with node- level and network-level system libraries. Together, this information provides a clear understanding of the strengths and limitations of the DARMA approach in the context of Sandias ATDM codes, to guide our future research and development in this area.
The quality of automatic detections from sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings, yet achieving superior automatic detection of events is closely related to these parameters. We present an automated sensor tuning (AST) system that tunes effective parameter settings for each sensor detector to the current state of the environment by leveraging cooperation within a neighborhood of sensors. After a stabilization period, the AST algorithm can adapt in near real-time to changing conditions and automatically self-tune a signal detector to identify (detect) only signals from events of interest. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Our current work focuses on reducing false signal detections early in the seismic signal processing pipeline, which leads to fewer false events and has a significant impact on reducing analyst time and effort. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections from a seismic sensor network monitoring the Mount Erebus Volcano in Antarctica, we show that AST increases the probability of detection while decreasing false alarms.
Razorback is a research reactor transient analysis computer code designed to simulate the operation of a research reactor (such as Sandia National Laboratories Annular Core Research Reactor (ACRR)). The code provides a coupled numerical solution of the point reactor kinetics equations, the energy conservation equation for fuel element heat transfer, the equation of motion for fuel element thermal expansion, and the mass, momentum, and energy conservation equations for the water cooling of the fuel elements. This input manual describes how an input file is composed, and facilitates an understanding of the various code input parameters. The makeup of the various code output files is also described. This manual also provides instructions for the installation and setup of the code, and how to report bugs and/or errors.
This report contains work completed by a group of student interns during the summer of 2017. Under the guidance of Ryan Coe, Aubrey Eckert-Gallup, and Nevin Martin, a series of interrelated projects were completed on topics relating to extreme response and survival analysis of wave energy converters (WECs). Jarred Canning studied long-term design response analysis methods for WECs. Sam Edwards studied how variation in the selection of an environmental contour affects the characterization of WEC response in extreme conditions. Sam also led the integration of various components of this report and overall editing. Tyler Esterly produced a catalog of analyses for different ocean sites. Bibiana Seng studied clustering analyses for comparing the wave environments of different ocean sites. Lori Smith performed a comparison between analyses conducted using spectral wave data and analyses using deterministic time-domain wave data. William ("Zach") Stuart studied the sensitivity and convergence of environmental contour methods.
This report describes a model of the displacement of one hydrogen isotope within a metal hydride tube by a different isotope in the gas phase that is blown through the tube. The model incorporates only the most basic parameters to make a clear connection to the theory of open-tube gas chromatography, and to provide a simple description of how the behavior of the system scales with controllable parameters such as gas velocity and tube radius. A single tube can be seen as a building block for more complex architectures that provide higher molar flow rates or other advanced design goals.
This simple Microgrid Design Toolkit ( MDT ) use case will provide you an example of a basic microgrid design. It will introduce basic principles of using the MDT islanded mode optimization by modifying a baseline microgrid design and performing an analysis of the results . Please reference the MDT User Guide (SAND201-9374) for detailed instructions on how to use the tool.
This simple Microgrid Design Toolkit (MDT) use case will provide you an example of performing microgrid sizing by identifying the types and quantities of technology to be purchased for use in a microgrid. It will introduce basic principles of using the MDT microgrid sizing capability by comparing the results of two microgrids in two different markets. Please reference the MDT User Guide (SAND2017-9374) for detailed instructions on how to use the tool.
This report presents multi-phase modeling approaches that are developed for simulating rubble fire scenarios similar to a large-scale rubble pool fire test at Sandia National Laboratories using composite materials and jet fuel. The rubble pool fire test burnt oddly shaped combustible solid objects submerged in liquid fuel. As an intermediate step toward a full scale rubble fire simulation, various model improvement tasks were performed. For modeling solid decomposition, a multi-step degradation model was used for canonical verification problems and the Chemical Percolation for Devolatilization (CPD) approach was implemented. Capabilities of Lagrangian particle approach has been extended such that a group of particles may represent a solid bulk. For gas-liquid interface, the volume of fluid (VOF) technique was implemented and relevant physics were added. The developed tools offer a potential for simulating three-phase (gas, liquid, and solid) combustion applications.
Our team has investigated a series of soluble coordination complexes for use as tags to monitor underground fluid flows in reservoirs. While most of the metal-ligand (M-L) complexes were based on the dianionic salen family of ligands, conceptually other ligands such as porphyrins or phthalocyanines could be used with similar success. Detection and identification of these species in solution were performed by inductively coupled plasma (ICP) or Raman/resonance Raman (rR) spectroscopy. The preparation of a large number of new M-L salen complexes was accomplished. Complexes were prepared that were soluble in either water or hydrocarbons to allow for flexibility in use. Unambiguous identification of these complexes allowed for meaningful molecular dynamics (MD) calculations to be performed, so that the attraction of the M-L complexes to either the rock formation or the liquid media could be evaluated. The use of soluble M-L species was found to avoid issues of rock deposition.
Imaging techniques for the analysis of porous structures have revolutionized our ability to quantitatively characterize geomaterials. Digital representations of rock from CT images and physics modeling based on these pore structures provide the opportunity to further advance our quantitative understanding of fluid flow, geomechanics, and geochemistry, and the emergence of coupled behaviors. Additive manufacturing, commonly known as 3D printing, has revolutionized production of custom parts with complex internal geometries. For the geosciences, recent advances in 3D printing technology may be co-opted to print reproducible porous structures derived from CT-imaging of actual rocks for experimental testing. The use of 3D printed microstructure allows us to surmount typical problems associated with sample-to-sample heterogeneity that plague rock physics testing and to test material response independent from pore-structure variability. Together, imaging, digital rocks and 3D printing potentially enables a new workflow for understanding coupled geophysical processes in a real, but well-defined setting circumventing typical issues associated with reproducibility, enabling full characterization and thus connection of physical phenomena to structure. Here we report on our research exploring the possibilities that these technologies can bring to geosciences for coupled multiscale experimental and numerical analysis using 3D printed fractured rock specimens.
Visual clutter metrics play an important role in both the design of information visualizations and in the continued theoretical development of visual search models. In visualization design, clutter metrics provide a mathematical prediction of the complexity of the display and the difficulty associated with locating and identifying key pieces of information. In visual search models, they offer a proxy to set size, which represents the number of objects in the search scene, but is difficult to estimate in real-world imagery. In this article, we first briefly review the literature on clutter metrics and then contribute our own results drawn from studies in two security-oriented visual search domains: airport X-ray imagery and radar imagery. We analyze our results with an eye toward bridging the gap between the scene features evaluated by current clutter metrics and the features that are relevant to our security tasks. The article concludes with a brief discussion of possible research steps to close this gap.
An experimental system we developed combines triaxial rock deformation and mass spectrometry to measure noble gas flow before, during, and after rock fracture. Geogenic noble gas is released during triaxial deformation (real time) and is related to volume strain and acoustic emissions. The noble gas release then represents a signal of deformation during its stages of development. Noble gases are contained in most crustal rock at inter and intra granular sites. Their release during natural and man-made stress and strain changes represents a signal of deformation in brittle and semi-brittle conditions. The noble gas composition depends on lithology, geologic history, age of the rock, and fluids present. Uranium, thorium and potassium-40 concentrations in the rocks also affect the production of radiogenic noble gases (4He, Ar). Noble gas emission and its relationship to crustal processes have been studied for many years in the geologic community including correlations to tectonic velocities and qualitative estimates of deep permeability from surface measurements, finger prints of nuclear weapon detonation, and as a potential precursory signal to earthquakes attributed to gas release due to pre-seismic stress, dilatancy and/or fracturing of the rock. Helium emission has been shown as a precursor of volcanic activity. We present empirical results/relationships of specimen strain, microstructural evolution, acoustic emissions, and noble gas release from laboratory triaxial experiments performed upon a granite and a young basalt, bedded salt, and a marine shale.
The Spent Fuel Waste Science and Technology (SFWST) campaign from the DOE Fuel Cycle and Technology (FCT) program has been engaging in international collaborations between repository R&D programs for nuclear waste disposal to leverage on the extensive research investigations and laboratory/field data of engineered barrier system (EBS) components (e.g., near-field) and characterization of transport phenomena in the host rock (e.g., far-field) processes from state-of-the-art underground research laboratories (URL) experiments. Thermal heating from radionuclide decay in the waste canisters will generate increases in temperature that will drive chemical and transport processes in the near- and far-field domains of the repository. URL sites provide the ideal setting to conduct heater test experiments to simulate the thermal effects of heat-generating nuclear waste in disposal galleries and surrounding host rock.
As an undergraduate researcher, I worked on a new technology called nanofluid-based direct absorption solar collectors (DASC) which is a type of solar water heater that has the potential to be more efficient than traditional solar water heaters. Because of my experience with this type of technology, I decided to look into other types of solar energy technologies which could be used on Native American tribal lands. Some types of solar energy technologies that I wanted to focus on are photovoltaic solar energy systems, passive solar design, and solar water heaters.
In this paper, a nonlocal convection-diffusion model is introduced for the master equation of Markov jump processes in bounded domains. With minimal assumptions on the model parameters, the nonlocal steady and unsteady state master equations are shown to be well-posed in a weak sense. Finally, then the nonlocal operator is shown to be the generator of finite-range nonsymmetric jump processes and, when certain conditions on the model parameters hold, the generators of finite and infinite activity Lévy and Lévy-type jump processes are shown to be special instances of the nonlocal operator.
Current practice for mitigating DRAM hardwarefaults is to simply discard the entire faulty DIMM. However, this becomes increasingly expensive and wasteful as the priceof memory hardware increases and moves physically closer toprocessing units. Accurately characterizing memory faults inreal-time in order to pre-empt future potentially catastrophicfailures is crucial to conserving resources by blacklisting smallaffected regions of memory rather than discarding an entirehardware component. We further evaluate and extend a machinelearning method for DRAM fault characterization introduced inprior work by Baseman et al. at Los Alamos National Laboratory. We report on the usefulness of a variety of training sets, usinga set of production-relevant metrics to evaluate the method ondata from a leadership-class supercomputing facility. We observean increase in percent of faults successfully mitigated as well asa decrease in percent of wasted blacklisted pages, regardless oftraining set, when using the learned algorithm as compared to ahuman-expert, deterministic, and rule-based approach.
The Structural Reliability Partnership Workshop was held in Albuquerque, NM on August 29-30, 2017 and was hosted by Sandia National Laboratories. Attendees were present from academia, industry and several other national laboratories. The workshop kicked off with an introduction to the SRP to familiarize potential members with what the purpose, structure and benefits would be to their organization. Technical overviews were given on several topics by attendees from each sector – national labs, universities and industry – to provide a snapshot of the type of work that is currently being conducted on structural reliability. Attendees were then given the opportunity to suggest and discuss potential Challenge Scenario topics. Three were ultimately decided upon as being the most important: Additive Manufacturing, Hydrogen Pipeline Steels, and Bolted Joined Structures. These were then analyzed using Quad Charts to determine What, How, Who, and Why these areas would be further investigated. Rather than restricting future research to only one area, the option was left open to investigate both the top two, depending on interest and cost associated with hosting such an event. More informal collaboration may be undertaken for the third topic if members have time and interest. Other items discussed pertained to the organization, structure and policies of the Partnership. Topics including Data Management, IP, and mechanisms of partnering/information sharing were touched upon but final decisions were not made. Further action is needed before this can be done. Action items were outlined and assigned, where possible. The next workshop is to be held in early August 2018 in Boulder, CO and is to be hosted by NIST. In the interim, quarterly updates are to take place via WebEx to maintain a line of communication and to ensure progress on both the administrative and technical tasks.
Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. One possibility for such a tool is a model of visual saliency for data visualizations. Visual saliency models are typically based on the properties of the human visual cortex and predict which areas of a scene have visual features (e.g. color, luminance, edges) that are likely to draw a viewer's attention. While these models can accurately predict where viewers will look in a natural scene, they typically do not perform well for abstract data visualizations. In this paper, we discuss the reasons for the poor performance of existing saliency models when applied to data visualizations. We introduce the Data Visualization Saliency (DVS) model, a saliency model tailored to address some of these weaknesses, and we test the performance of the DVS model and existing saliency models by comparing the saliency maps produced by the models to eye tracking data obtained from human viewers. In conclusion, we describe how modified saliency models could be used as general tools for assessing the effectiveness of visualizations, including the strengths and weaknesses of this approach.
Proceedings of SPIE - The International Society for Optical Engineering
Ampleford, David J.; Ames, Andrew; Bourdon, Christopher; Bruni, Ricardo; Kilaru, Kiranmayee; Kozioziemski, Bernard; Pivovaroff, Michael J.; Ramsey, Brian D.; Romaine, Suzanne E.; Vogel, Julia; Walton, Christopher; Wu, Ming
Here, we have developed a process for indirectly coating small diameter electroformed nickel replicated optics with multilayers to increase their response at high energy (i.e. >10 keV). The ability to fabricate small diameter multilayer-coated full-shell Wolter X-ray optics with narrow bandpass opens the door to several applications within astronomy and also provides a path for cross-fertilization to other fields. We report on the characterization and evaluation of the first two prototype X-ray Wolter optics to be delivered to the Z Pulsed Power Facility at Sandia National Laboratories. The intent is to develop and field several optics as part of an imaging system with targeted spectral ranges.
Volumetric imaging of focusing waveguide grating coupler emission with high spatial resolution in the visible (λ = 637.3 nm) is demonstrated using a scanning near-field optical microscope with long z-axis travel range. Stacks of 2-D images recorded at fixed distance from the device are compiled to yield 3-D visualization of the light emission pattern and enable extraction of parameters, such as spot size, angle of emission, and focal height. Measurements of such parameters are not prevalent in the literature yet are necessary for efficacious design and integration. As a result, it is observed that finite-difference time-domain simulations based on fabrication layout files do not perfectly predict in-hand device behavior, underscoring the merit of experimental validation, particularly for critical application.
Measurement of the window interface velocity is a common technique for investigating the dynamic response materials at high strain rates. However, these measurements are limited in pressure to the range where the window remains transparent. The most common window material for this application is lithium fluoride, which under single shock compression becomes opaque at ∼200 GPa. To date, no other window material has been identified for use at higher pressures. Here, we present a Lagrangian technique to calculate the interface velocity from a continuously measured shock velocity, with application to quartz. The quartz shock front becomes reflective upon melt, at ∼100 GPa, enabling the use of velocity interferometry to continuously measure the shock velocity. This technique overlaps with the range of pressures accessible with LiF windows and extends the region where wave profile measurements are possible to pressures in excess of 2000 GPa. We show through simulated data that the technique accurately reproduces the interface velocity within 20% of the initial state, and that the Lagrangian technique represents a significant improvement over a simple linear approximation.
Color centers in diamond provide a promising platform for quantum optics in the solid state, with coherent optical transitions and long-lived electron and nuclear spins. Building upon recent demonstrations of nanophotonic waveguides and optical cavities in single-crystal diamond, we now demonstrate on-chip diamond nanophotonics with a high-efficiency fiber-optical interface achieving >90% power coupling at visible wavelengths. We use this approach to demonstrate a bright source of narrow-band single photons based on a silicon-vacancy color center embedded within a waveguide-coupled diamond photonic crystal cavity. Our fiber-coupled diamond quantum nanophotonic interface results in a high flux (approximately 38 kHz) of coherent single photons (near Fourier limited at <1-GHz bandwidth) into a single-mode fiber, enabling possibilities for realizing quantum networks that interface multiple emitters, both on chip and separated by long distances.
This memo addresses the calibration of anisotropic yield functions based on data obtained from a series of uniaxial tension specimens extracted from a tubular Al 7079 circular cylindrical extrusion. Achieving the calibrations completed an important step in the Experimentally Enhanced Computations (ExEC) project. The focus of the project is on novel calibration approaches that will be based on advanced diagnostics and numerical simulations with the intention of reducing the overall calibration effort. The test data used here resulted from traditional tensile tests on specimens cut at 12 orientations within the extrusion. Two anisotropic yield surfaces — Hill’s (1948) and Barlat’s (2005) — were calibrated based on the test data. The methods used to conduct the calibrations are described, and the results show that the material exhibited significant yield anisotropy. The larger number of parameters in Barlat’s yield function allowed it to fit the test data more accurately than Hill’s. Although work remains to assess the sensitivity of the calibrated model parameters to various factors, the methods implemented and the results obtained here provide bases for further work and useful benchmarks for future calibrations to be conducted using the novel approach.
Measured and calculated results are presented for the emission properties of a new class of emitters operating in the cavity quantum electrodynamics regime. The structures are based on high-finesse GaAs/AlAs micropillar cavities, each with an active medium consisting of a layer of InGaAs quantum dots (QDs) and the distinguishing feature of having a substantial fraction of spontaneous emission channeled into one cavity mode (high ß-factor). This paper demonstrates that the usual criterion for lasing with a conventional (low ß-factor) cavity, that is, a sharp non-linearity in the input-output curve accompanied by noticeable linewidth narrowing, has to be reinforced by the equal-time second-order photon autocorrelation function to confirm lasing. The paper also shows that the equal-time second-order photon autocorrelation function is useful for recognizing superradiance, a manifestation of the correlations possible in high-ß microcavities operating with QDs. In terms of consolidating the collected data and identifying the physics underlying laser action, both theory and experiment suggest a sole dependence on intracavity photon number. Evidence for this assertion comes from all our measured and calculated data on emission coherence and fluctuation, for devices ranging from light-emitting diodes (LEDs) and cavity-enhanced LEDs to lasers, lying on the same two curves: one for linewidth narrowing versus intracavity photon number and the other for g(2)(0) versus intracavity photon number.
Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energy management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.
Curry, John; Luftman, Henry S.; Sidebottom, Mark A.; Strandwitz, Nicholas C.; Argibay, Nicolas; Krick, Brandon A.
This work demonstrates the role of microstructure in the friction and oxidation behavior of the lamellar solid lubricant molybdenum disulfide (MoS2). We report on systematic investigations of oxidation and friction for two MoS2 films with distinctively different microstructures - amorphous and planar/highly-ordered - before and after exposure to atomic oxygen (AO) and high-temperature (250 °C) molecular oxygen. A combination of experimental tribology, molecular dynamics simulations, X-ray photoelectron spectroscopy (XPS), and high-sensitivity low-energy ion scattering (HS-LEIS) was used to reveal new insights about the links between structure and properties of these widely utilized low-friction materials. Initially, ordered MoS2 films showed a surprising resistance to both atomic and molecular oxygens (even at elevated temperature), retaining characteristic low friction after exposure to extreme oxidative environments. XPS shows comparable oxidation of both coatings via AO; however, monolayer resolved compositional depth profiles from HS-LEIS reveal that the microstructure of the ordered coatings limits oxidation to the first atomic layer.
Ab intio molecular dynamics simulations show that the electrical conductivity of liquid SiO2 is semimetallic at the conditions of the deep molten mantle of early Earth and super-Earths, raising the possibility of silicate dynamos in these bodies. Whereas the electrical conductivity increases uniformly with increasing temperature, it depends nonmonotonically on compression. At very high pressure, the electrical conductivity decreases on compression, opposite to the behavior of many materials. We show that this behavior is caused by a novel compression mechanism: the development of broken charge ordering, and its influence on the electronic band gap.
Raichev, O.E.; Hatke, A.T.; Zudov, M.A.; Reno, John L.
We report on nonlinear transport measurements in a two-dimensional electron gas hosted in GaAs/AlGaAs heterostructures. Upon application of direct current, the low-temperature differential resistivity acquires a positive correction, which exhibits a pronounced maximum followed by a plateau. With increasing temperature, the nonlinearity diminishes and disappears. These observations can be understood in terms of a crossover from the Bloch-Grüneisen regime to the quasielastic scattering regime as the electrons are heated by direct current. Calculations considering the interaction of electrons with acoustic phonons provide a reasonable description of our experimental findings.
The following summaries are provided as fulfillment of milestone M4SF-17SN080305022 and represent international coordination activities in disposal research funded by the US DOE Spent Fuel and Waste Storage and Technologies (SFWST) Campaign during Fiscal Year 2017: SFWST funded bi-lateral interactions with Taiwan, OECD-NEA Repository Metadata (RepMet) project, SFWST funded bi-lateral interactions with the Republic of Korea.
Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.
The recurring problem in electrical and electromagnetic modeling of anthropogenically impacted geologic settings is the need for efficient representation of strong, thin, arbitrarily oriented electrical conductors, such as metal pipes or conductive fractures. The difficulty arises from discretization with roughly equidimensional elements of the governing Maxwell equations over these volumetrically insignificant regions; which by virtue of conductors' thinness, can easily number in the 100's of millions for even simple models. To address this problem, a novel hierarchical electrical model is proposed for unstructured tetrahedral finite element meshes, where the usual volume-based conductivity in tetrahedra is augmented by facet- and edge-based conductivity on the infinitesimally thin regions between elements. This allows a slender borehole casing of arbitrary shape to be approximated by a set of connected edges within the mesh, and on which a conductivity-area product is explicitly defined. Benchmark testing of the direct current (DC) resistivity problem shows excellent agreement between the facet/edge representations and independent analytic solutions. As a practical case, the metallic infrastructure of a mature oilfield in the Kern River Formation is modeled. The oilfield comprises roughly 2 km of surface pipeline and 122 vertical, steel-cased wells, each extending to a depth of 300 m. Numerical results demonstrate strong coupling between surface and downhole conductors and reveal a complex circuit of current flow within the (finite conductivity) steel. This would be difficult to quantify using alternative, approximate methods for accommodating the approximately 30 km of steel casing and surface pipe combined.
A finite element formulation is developed for a poroelastic medium consisting of an incompressible hyperelastic skeleton saturated by an incompressible fluid. The governing equations stem from mixture theory and the application is motivated by the study of interstitial fluid flow in brain tissue. The formulation is based on the adoption of an arbitrary Lagrangian–Eulerian (ALE) perspective. We focus on a flow regime in which inertia forces are negligible. The stability and convergence of the formulation is discussed, and numerical results demonstrate agreement with the theory.
This report provides (1) an updated set of inputs (Sections 1 through 4) on various additional waste forms (WF) for the generic Defense Waste Repository (DWR) inventory represented in the generic disposal system analyses (GDSA); (2) summaries of evaluations initiated to refine particular characteristics of particular WF for future use (Section 5); and (3) status updates (Section 6) for the Online Waste Library (OWL) inventory content, data entry checking process, and external OWL BETA testing initiated in fiscal year 2017. As such, this report represents completion of both deliverables M3SF-17SNO10501022 (SFWD-SFWST-2017-000047 — this actual report) and M4SF-17SN010501012 (SFWD-SFWST-2017- 000112 — to be completed by reference to the first milestone report in the PICSNE system).
A three-dimensional direct numerical simulation is conducted for a temporally evolving planar jet of n-heptane at a pressure of 40 atmospheres and in a coflow of air at 1100 K. At these conditions, n-heptane exhibits a two-stage ignition due to low- and high-temperature chemistry, which is reproduced by the global chemical model used in this study. The results show that ignition occurs in several overlapping stages and multiple modes of combustion are present. Low-temperature chemistry precedes the formation of multiple spatially localised high-temperature chemistry autoignition events, referred to as 'kernels'. These kernels form within the shear layer and core of the jet at compositions with short homogeneous ignition delay times and in locations experiencing low scalar dissipation rates. An analysis of the kernel histories shows that the ignition delay time is correlated with the mixing rate history and that the ignition kernels tend to form in vortically dominated regions of the domain, as corroborated by an analysis of the topology of the velocity gradient tensor. Once ignited, the kernels grow rapidly and establish edge flames where they envelop the stoichiometric isosurface. A combination of kernel formation (autoignition) and the growth of existing burning surface (via edge-flame propagation) contributes to the overall ignition process. An analysis of propagation speeds evaluated on the burning surface suggests that although the edge-flame speed is promoted by the autoignitive conditions due to an increase in the local laminar flame speed, edge-flame propagation of existing burning surfaces (triggered initially by isolated autoignition kernels) is the dominant ignition mode in the present configuration.
We disclose a strategy for Ni-catalyzed dicarbofunctionalization of olefins in styrenes by intercepting Heck C(sp3)-NiX intermediates with arylzinc reagents. This approach utilizes a readily removable imine as a coordinating group that plays a dual role of intercepting oxidative addition species derived from aryl halides and triflates to promote Heck carbometalation and stabilizing the Heck C(sp3)-NiX intermediates as transient metallacycles to suppress β-hydride elimination and facilitate transmetalation/reductive elimination steps. This method affords diversely substituted 1,1,2-triarylethyl products that occur as structural motifs in various natural products.
The SWMPP describes the best management practices (BMPs) employed at SNL, measurable goals, and anticipated implementation dates for compliance with the Permit requirements to ensure that stormwater discharges from the SNL MS4 do not contribute pollutants to Waters of the United States (WOTUS), namely the Tijeras Arroyo and the Rio Grande. The SWMPP is updated annually, and as necessary, to include new information and/or document the development, implementation and assessment of program elements, as required in Part III.B of the Permit. Version 3 of the SWMPP documents compliance activities and program elements developed and implemented between July 1, 2016 and June 30, 2017; it is required to be submitted on or before December 1, 2017.
Metal organic frameworks (MOFs) have recently attracted great attentions for the thermoelectric (TE) applications, owing to their intrinsic low thermal conductivity, but their TE efficiencies are still low due to the poor electronic transport properties. Here, various synthetic strategies have been designed to optimize the electronic properties of MOFs. Using a series of first principle calculations and band theory, we explore the effect of structural topology and redox matching between the metal and coordinated atoms on the TE transport properties. In conclusion, the presented results provide a fundamental guidance for optimizing electronic charge transport of existing MOFs, and for designing yet to be discovered conductive MOFs for thermoelectric applications.
Here, we have developed a novel specimen for studying crack paths in glass. Under certain conditions, the specimen reaches a state where the crack must select between multiple paths satisfying the K II = 0 condition. This path selection is a simple but challenging benchmark case for both analytical and numerical methods of predicting crack propagation. We document the development of the specimen, using an uncracked and instrumented test case to study the effect of adhesive choice and validate the accuracy of both a simple beam theory model and a finite element model. In addition, we present preliminary fracture test results and provide a comparison to the path predicted by two numerical methods (mesh restructuring and XFEM). The directional stability of the crack path and differences in kink angle predicted by various crack kinking criteria is analyzed with a finite element model.
Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bézier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. The model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.
lon accelerator based techniques provide unique tools to gain insight into the phenomena underlying the formation of defects induced by energetic particles in semiconductor materials and their effects on the electronic features of the device. In recognition of the potential of these techniques, with the aim of enhancing the understanding of the mechanisms underlying the degradation of the performances of semiconductor devices induced by ionizing radiation, the IAEA established a Research Project, coordinated by the Physics Section (CRP F11016) entitled "Utilization of ion accelerators for studying and modelling of radiation induced defects in semiconductors and insulators" at the end of 2011. The objective of this IAEA Coordinated Research Project (CRP) was to enhance the capabilities of the interested Member States by facilitating their collective efforts to use accelerator-based ion irradiation of electronic materials in conjunction with available advanced characterization techniques to gain a deeper understanding of how different types of radiation influences the electronic properties of materials and devices, leading to an improved radiation hardness. A dynamic and productive research was stimulated by this CRP among collaborating partners, resulting in publications in scientific journals [CRP2016], educational and scientific software packages [W8, Forneris2014], and a number of collaborations among the participating research groups. Two of the most significant outcomes of this project are i) the experimental protocol, which rationalizes the use of the many existing characterization techniques adopted to investigate radiation effects in semiconductor devices and ii) the relevant theoretical approach to interpret the experimental data [Vittone2016 and references therein]. This publication integrates output of research articles published by the partners of the CRP and is aimed to provide an exhaustive description of the experimental protocol, the theoretical model with the relevant limits of application, the data analysis procedure, and the physical observables which can be effectively measured and which can be used for assessment of the radiation hardness of semiconductor devices. The intended audience of this report includes all those professionals and technologists working in ion beam functional analysis of semiconductor materials, solid-state physicists and engineers involved in the design of electronic devices working in radiation harsh environments.
The complexation of toxic and/or radioactive ions on to mineral surfaces is an important topic in geochemistry. We apply periodic-boundary-conditions density functional theory (DFT) molecular dynamics simulations to examine the coordination of Pb(II), SeO2-3, and their contact ion pairs to goethite (1 0 1) and (2 1 0) surfaces. The multitude of Pb(II) adsorption sites and possibility of Pb(II)-induced FeOH deprotonation make this a complex problem. At surface sites where Pb(II) is coordinated to three FeO and/or FeOH groups, and with judicious choices of FeOH surface group protonation states, the predicted Fe-Pb distances are in good agreement with EXAFS measurements. Trajectories where Pb(II) is in part coordinated to only two surface Fe-O groups exhibit larger fluctuations in Pb-O distances. Pb(II)/ SeO2-3 contact ion pairs are at least metastable on goethite (2 1 0) surfaces if the SeO2-3has a monodentate Se-O-Fe bond. Our DFT-based molecular dynamics calculations are a prerequisite for calculations of finite temperature equilibrium binding constants of Pb(II) and Pb(II)/ ion pairs to goethite adsorption sites.
Thermal mechanical stresses of glass-ceramic to stainless steel (GCtSS) seals are analyzed using finite element modeling over a temperature cycle from a set temperature (Tset) 500°C to −55°C, and then back to 600°C. Two glass-ceramics having an identical coefficient of thermal expansion (CTE) at ~16 ppm/°C but very different linearity of thermal strains, designated as near-linear NL16 and step-like SL16, were formed from the same parent glass using different crystallization processes. Stress modeling reveals much higher plastic strain in the stainless steel using SL16 glass-ceramic when the GCtSS seal cools from Tset. Upon heating tensile stresses start to develop at the GC-SS interface before the temperature reaches Tset. On the other hand, the much lower plastic deformation in stainless steel accumulated during cooling using NL16 glass-ceramic allows for radially compressive stress at the GC-SS interface to remain present when the seal is heated back to Tset. The qualitative stress comparison suggests that with a better match of thermal strain rate to that of stainless steel, the NL16 glass-ceramic not only improves the hermeticity of the GCtSS seals, but would also improve the reliability of the seals exposed to high-temperature and/or high-pressure abnormal environments.
Radiation responses of high-voltage, vertical gallium-nitride (GaN) diodes were investigated using Sandia National Laboratories’ nuclear microprobe. Effects of the ionization and the displacement damage were studied using various ion beams. We found that the devices show avalanche effect for heavy ions operated under bias well below the breakdown voltage. The displacement damage experiments showed a surprising effect for moderate damage: the charge collection efficiency demonstrated an increase instead of a decrease for higher bias voltages.
One of the major challenges in deciding where to build new transmission lines is that there is uncertainty regarding future loads, renewal generation output and equipment failures. We propose a robust optimization model whose transmission expansion solutions ensure that demand can be met over a wide range of conditions. Specifically, we require feasible operation for all loads and renewable generation levels within given ranges, and for all single transmission line failures. Furthermore, we consider transmission switching as an allowable recovery action. This relatively inexpensive method of redirecting power flows improves resiliency, but introduces computational challenges. We present a novel algorithm to solve this model. Computational results are discussed.
The matched filtering technique that uses the cross correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this study, we introduce an approximate nearest neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation. Our method begins with a projection into a reduced dimensionality space, based on correlation with a randomized subset of the full template archive. Searching for a specified number of nearest neighbors for a query waveform is accomplished by iteratively comparing it with the neighbors of its immediate neighbors. We used the approach to search for matches to each of ∼2300 analyst-reviewed signal detections reported in May 2010 for the International Monitoring System station MKAR. The template library in this case consists of a data set of more than 200,000 analyst-reviewed signal detections for the same station from February 2002 to July 2016 (excluding May 2010). Of these signal detections, 73% are teleseismic first P and 17% regional phases (Pn, Pg, Sn, and Lg). The analyses performed on a standard desktop computer show that the proposed ANN approach performs a search of the large template libraries about 25 times faster than the standard full linear search and achieves recall rates greater than 80%, with the recall rate increasing for higher correlation thresholds.
The evaluation of optical system performance in fog conditions typically requires field testing. This can be challenging due to the unpredictable nature of fog generation and the temporal and spatial nonuniformity of the phenomenon itself. We describe the Sandia National Laboratories fog chamber, a new test facility that enables the repeatable generation of fog within a 55m×3m×3m (L×W×H) environment, and demonstrate the fog chamber through a series of optical tests. These tests are performed to evaluate system image quality, determine meteorological optical range (MOR), and measure the number of particles in the atmosphere. Relationships between typical optical quality metrics, MOR values, and total number of fog particles are described using the data obtained from the fog chamber and repeated over a series of three tests.
Additive manufacturing enables the rapid, cost effective production of customized structural components. To fully capitalize on the agility of additive manufacturing, it is necessary to develop complementary high-throughput materials evaluation techniques. In this study, over 1000 nominally identical tensile tests are used to explore the effect of process variability on the mechanical property distributions of a precipitation hardened stainless steel produced by a laser powder bed fusion process, also known as direct metal laser sintering or selective laser melting. With this large dataset, rare defects are revealed that affect only ≈2% of the population, stemming from a single build lot of material. The rare defects cause a substantial loss in ductility and are associated with an interconnected network of porosity. The adoption of streamlined test methods will be paramount to diagnosing and mitigating such dangerous anomalies in future structural components.
Hu, Yalin; Tso, Dustin; Kapai, Sarina; Feldman, Marc
The digital design discussed in the following document is inspired by the digital dual mixer time difference circuit and based on the white paper, Digital femtosecond time difference circuit for CERN's timing system. DMTD is originally an analog technique that measures the time difference between two events with high precision using a commercial time interval counter. Our project applies this analog concept to a digital system programmed onto a Microsemi ProASIC3E FPGA (Field- Programmable Gate Array). D-DMTD is a digital system theoretically capable of measuring the time difference between two digital clock signals with very fine resolution (sub-picosecond) using a relatively low frequency counter. The system essentially acts as a digital phase detector with femtosecond time resolution. The main concern with this processing technique is its feasibility and accuracy when implemented on an FPGA. Another concern is the environmentally-induced, horizontal phase noise in the digital signals; this 'litter" jeopardizes the fidelity of the clocks and generates glitches in the signals. Thus, the majority of the work was focused on determining under what conditions the digital design performs optimally and generates the most accurate estimations for the phase shift.
We calculated the optical nonlinearities of the atomically thin monolayer transition metal dichalcogenide material (particularly MoS2), particularly for those linear and nonlinear transition processes that utilize the bound exciton states. We adopted the bound and the unbound exciton states as the basis for the Hilbert space, and derived all the dynamical density matrices that provides the induced current density, from which the nonlinear susceptibilities can be drawn order-by-order via perturbative calculations. We provide the nonlinear susceptibilities for the linear, the second-harmonic, the third-harmonic, and the kerr-type two-photon processes.
Emulation-based models of distributed computing systems are collections of virtual ma- chines, virtual networks, and other emulation components configured to stand in for oper- ational systems when performing experimental science, training, analysis of design alterna- tives, test and evaluation, or idea generation. As with any tool, we should carefully evaluate whether our uses of emulation-based models are appropriate and justified. Otherwise, we run the risk of using a model incorrectly and creating meaningless results. The variety of uses of emulation-based models each have their own goals and deserve thoughtful evaluation. In this paper, we enumerate some of these uses and describe approaches that one can take to build an evidence-based case that a use of an emulation-based model is credible. Predictive uses of emulation-based models, where we expect a model to tell us something true about the real world, set the bar especially high and the principal evaluation method, called validation , is comensurately rigorous. We spend the majority of our time describing and demonstrating the validation of a simple predictive model using a well-established methodology inherited from decades of development in the compuational science and engineering community.
In this document we describe a reference architecture developed for EmulyticsTM clusters at Sandia National Laboratories. Taking into consideration the constraints of our Emulytics software and the requirements for integration with the larger computing facilities at Sandia, we developed a cluster platform suitable for use by Sandia's several Emulytics toolsets and also useful for more general large-scale computing tasks.
This document details the milestone approach to define the true operating limitations (margins) of the Terry turbopump systems used in the nuclear industry for Milestone 3 (full-scale component experiments) and Milestone 4 (Terry turbopump basic science experiments) efforts. The overall multinational-sponsored program creates the technical basis to: (1) reduce and defer additional utility costs, (2) simplify plant operations, and (3) provide a better understanding of the true margin which could reduce overall risk of operations.
A new method is introduced for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorous assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. The method is seen to be particularly effective for relatively small training samples.
The migration and trapping of supercritical CO2 (scCO2) in geologic carbon storage is strongly dependent on the geometry and wettability of the pore network in the reservoir rock. During displacement, resident fluids may become trapped in the pits of a rough pore surface forming an immiscible two-phase fluid interface with the invading fluid, allowing apparent slip flow at this interface. We present a two-phase fluid dynamics model, including interfacial tension, to characterize the impact of mineral surface roughness on this slip flow. We show that the slip flow can be cast in more familiar terms as a contact-angle (wettability)-dependent effective permeability to the invading fluid, a nondimensional measurement which relates the interfacial slip to the pore geometry. The analysis shows the surface roughness-induced slip flow can effectively increase or decrease this effective permeability, depending on the wettability and roughness of the mineral surfaces. Configurations of the pore geometry where interfacial slip has a tangible influence on permeability have been identified. The results suggest that for large roughness features, permeability to CO2 may be enhanced by approximately 30% during drainage, while the permeability to brine during reimbibition may be enhanced or diminished by 60%, depending on the contact angle with the mineral surfaces and degrees of roughness. For smaller roughness features, the changes in permeability through interfacial slip are small. A much larger range of effective permeabilities are suggested for general fluid pairs and contact angles, including occlusion of the pore by the trapped phase.
Emerging ultrawide bandgap semiconductor materials are logical candidates for applications that exploit the large critical electric field (EC) associated with these devices. For semiconductor devices, EC scales approximately as Eg2 5 [1]. With a 25% larger bandgap and an approximately 73% larger EC than GaN, Al0.3Ga0.7N-channel high election mobility transistors (HEMTs) might be viable candidates for harsh environment electronics or short wavelength photo-transistors. In either case, transistor quality factors such as minimal off-state leakage currents and subthreshold slope factor are important metrics.
The differential absorption hard X-ray (DAHX) spectrometer is a diagnostic developed to measure time-resolved radiation between 60 keV and 2 MeV at the Z Facility. It consists of an array of seven Si PIN diodes in a tungsten housing that provides collimation and coarse spectral resolution through differential filters. DAHX is a revitalization of the hard X-ray spectrometer that was fielded on Z prior to refurbishment in 2006. DAHX has been tailored to the present radiation environment in Z to provide information on the power, spectral shape, and time profile of the hard emission by plasma radiation sources driven by the Z machine.
The Operational Area Environmental Evaluation update provides a description of activities that have the potential to adversely affect natural and cultural resources, including soil, air, water, biological, ecological, and historical resources. The environmental sensitivity of an area is evaluated and summarized, which may facilitate informed management decisions as to where development may be prohibited, restricted, or subject to additional requirements.
CTH is an Eulerian hydrocode developed by Sandia National Laboratories (SNL) to solve a wide range of shock wave propagation and material deformation problems. Adaptive mesh refinement is also used to improve efficiency for problems with a wide range of spatial scales. The code has a history of running on a variety of computing platforms ranging from desktops to massively parallel distributed-data systems. For the Trinity Phase 2 Open Science campaign, CTH was used to study mesoscale simulations of the hypervelocity penetration of granular SiC powders. The simulations were compared to experimental data. A scaling study of CTH up to 8192 KNL nodes was also performed, and several improvements were made to the code to improve the scalability.
This report documents work performed using ALCC computing resources granted under a proposal submitted in February 2016, with the resource allocation period spanning the period July 2016 through June 2017. The award allocation was 10.7 million processor-hours at the National Energy Research Scientific Computing Center. The simulations performed were in support of two projects: the Atmosphere to Electrons (A2e) project, supported by the DOE EERE office; and the Exascale Computing Project (ECP), supported by the DOE Office of Science. The project team for both efforts consists of staff scientists and postdocs from Sandia National Laboratories and the National Renewable Energy Laboratory. At the heart of these projects is the open-source computational-fluid-dynamics (CFD) code, Nalu. Nalu solves the low-Mach-number Navier-Stokes equations using an unstructured- grid discretization. Nalu leverages the open-source Trilinos solver library and the Sierra Toolkit (STK) for parallelization and I/O. This report documents baseline computational performance of the Nalu code on problems of direct relevance to the wind plant physics application - namely, Large Eddy Simulation (LES) of an atmospheric boundary layer (ABL) flow and wall-modeled LES of a flow past a static wind turbine rotor blade. Parallel performance of Nalu and its constituent solver routines residing in the Trilinos library has been assessed previously under various campaigns. However, both Nalu and Trilinos have been, and remain, in active development and resources have not been available previously to rigorously track code performance over time. With the initiation of the ECP, it is important to establish and document baseline code performance on the problems of interest. This will allow the project team to identify and target any deficiencies in performance, as well as highlight any performance bottlenecks as we exercise the code on a greater variety of platforms and at larger scales. The current study is rather modest in scale, examining performance on problem sizes of O(100 million) elements and core counts up to 8k cores. This will be expanded as more computational resources become available to the projects.
The Sandia S-CO2 Recompression Closed Brayton Cycle (RCBC) utilizes a series of gas foil bearings in its turbine-alternator-compressors. At high shaft rotational speed these bearings allow the shaft to ride on a cushion of air. Conversely, during startup and shutdown, the shaft rides along the foil bearing surface. Low-friction coatings are used on bearing surfaces in order to facilitate rotation during these periods. An experimental program was initiated to elucidate the behavior of coated bearing foils in the harsh environments of this system. A test configuration was developed enabling long duration exposure tests, followed by a range of analyses relevant to their performance in a bearing. This report provides a detailed overview of this work. The results contained herein provide valuable information in selecting appropriate coatings for more advanced future bearing-rig tests at the newly established test facility in Sandia-NM.
The supercritical carbon dioxide (S-CO2) Brayton Cycle has gained significant attention in the last decade as an advanced power cycle capable of achieving high efficiency power conversion. Sandia National Laboratories, with support from the U.S. Department of Energy Office of Nuclear Energy (US DOE-NE), has been conducting research and development in order to deliver a technology that is ready for commercialization. Root cause analysis has been performed on the Recompression Loop at Sandia National Laboratories. It was found that particles throughout the loop are stainless steel, likely alloy 316 based upon the elemental composition. Deployment of a filter scheme is underway to both protect the turbomachinery and also for purposes of determining the specific cause for the particulate. Shake down tests of electric resistance (ER) as a potential in-situ monitoring scheme shows promise in high temperature systems. A modified instrument was purchased and held at 650°C for more than 1.5 months to date without issue. Quantitative measurements of this instrument will be benchmarked against witness samples in the future, but all qualitative trends to date are as to be expected. ER is a robust method for corrosion monitoring, but very slow at responding and can take several weeks under conditions to see obvious changes in behavior. Electrochemical noise was identified as an advanced technique that should be pursued for the ability to identify transients that would lead to poor material performance.