Publications

Abstract not provided.

Abstract not provided.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 Emulytics^TM 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.

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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.

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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.

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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.

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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.

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Sandia National Laboratories has tested and evaluated an updated SMAD digitizer, developed by the French Alternative Energies and Atomic Energy Commission (CEA). The SMAD digitizers are intended to record sensor output for seismic and infrasound monitoring applications. The purpose of this digitizer evaluation is 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 SMAD digitizers have been updated since their last evaluation by Sandia to improve their performance when recording at a sample rate of 20 Hz for infrasound applications and 100 Hz for hydro-acoustic seismic stations. This evaluation focuses primarily on the 20 Hz and 100 Hz sample rates. The SMAD digitizers are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear Test- Ban-Treaty Organization (CTBTO).

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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. As a result, 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.

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The prevention of the migration of fluids is a field of study with high demand in both the private industry as well as in government research and development. More particularly, the prevention of carbon dioxide (CO₂) migration or return to the atmosphere. This, in turn, causes measurably significant atmospheric climate change that results in immense damage to the environment. In this study, the interaction between 0.5 molar sodium chloride (NaCl) brine solution and a cement interface over extended periods of time is computationally investigated, as well as the interaction of a 33 millimolar CO₂ dissolved in the afore-mentioned brine solution for the same period of time. A 2-meter-long saturated brine solution reacted with an 800-meter-long cement block in PFLOTRAN, an open-source reactive flow transport software whose output was later visualized in ParaView, a separate, open-source, visualization software.

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The Reference Model Project (RMP), sponsored by the U.S. Department of Energy’s (DOE) Wind and Water Power Technologies Program within the Office of Energy Efficiency & Renewable Energy (EERE), aims at expediting industry growth and efficiency by providing nonproprietary Reference Models (RM) of MHK technology designs as study objects for opensource research and development (Neary et al. 2014a,b). As part of this program, MHK turbine models were tested in a large open channel facility at the University of Minnesota’s St. Anthony Falls Laboratory (UMN-SAFL). Reference Model 1 (RM1) is a 1:40 geometric scale dual-rotor axial flow horizontal axis device with counter-rotating rotors, each with a rotor diameter dT = 0.5m. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADVs) aligned with each rotor and the midpoint for RM1. Flow conditions for each case were controlled such that depth, h = 1m, and volumetric flow rate, Qw = 2.425m3s-1, resulting in a hub height velocity of approximately Uhub = 1.05ms-1 and blade chord length Reynolds numbers of Rec ≈ 3.0x105. Vertical velocity profiles collected in the wake of each device from 1 to 10 rotor diameters are used to estimate the velocity recovery and turbulent characteristics in the wake, as well as the interaction of the counter-rotating rotor wakes. The development of this high resolution laboratory investigation provides a robust dataset that enables assessing turbulence performance models and their ability to accurately predict device performance metrics, including computational fluid dynamics (CFD) models that can be used to predict turbulent inflow environments, reproduce wake velocity deficit, recovery and higher order turbulent statistics, as well as device performance metrics.

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