Publications

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Here, with recent outbreaks of MERS-Cov, Anthrax, Nipah, and Highly Pathogenic Avian Influenza, much emphasis has been placed on rapid identification of infectious agents globally. As a result, laboratories are building capacity, conducting more advanced and sophisticated research, increasing laboratory staff, and establishing collections of dangerous pathogens in an attempt to reduce the impact of infectious disease outbreaks and characterize disease causing agents. With this expansion, the global laboratory community has started to focus on laboratory biosafety and biosecurity to prevent the accidental and/or intent ional release o f these agents. Laboratory biosafety and biosecurity systems are used around the world to help mit igate the risks posed by dangerous pathogens in the laboratory. Veterinary laboratories carry unique responsibilities to workers and communities to safely and securely handle disease causing microorganisms. Many microorganisms studied in veterinary laboratories not only infect animals, but also have the potential to infect humans. This paper will discuss the fundamentals of laboratory biosafety and biosecurity.

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An important issue for present and future generations is the final disposal of spent nuclear fuel. Over the past over forty years, the development of technologies to isolate both spent nuclear fuel (SNF) and other high-level nuclear waste (HLW) generated at nuclear power plants and from production of defense materials, and low- and intermediate-level nuclear waste (LILW) in underground rock and sediments has been found to be a challenging undertaking. Finding an appropriate solution for the disposal of nuclear waste is an important issue for protection of the environment and public health, and it is a prerequisite for the future of nuclear power. The purpose of a deep geological repository for nuclear waste is to provide to future generations, protection against any harmful release of radioactive material, even after the memory of the repository may have been lost, and regardless of the technical knowledge of future generations. The results of a wide variety of investigations on the development of technology for radioactive waste isolation from 19 countries were published in the First Worldwide Review in 1991 (Witherspoon, 1991). The results of investigations from 26 countries were published in the Second Worldwide Review in 1996 (Witherspoon, 1996). The results from 32 countries were summarized in the Third Worldwide Review in 2001 (Witherspoon and Bodvarsson, 2001). The last compilation had results from 24 countries assembled in the Fourth Worldwide Review (WWR) on radioactive waste isolation (Witherspoon and Bodvarsson, 2006). Since publication of the last report in 2006, radioactive waste disposal approaches have continued to evolve, and there have been major developments in a number of national geological disposal programs. Significant experience has been obtained both in preparing and reviewing cases for the operational and long-term safety of proposed and operating repositories. Disposal of radioactive waste is a complex issue, not only because of the nature of the waste, but also because of the detailed regulatory structure for dealing with radioactive waste, the variety of stakeholders involved, and (in some cases) the number of regulatory entities involved.

The real H1514 Shipping and Storage Container is an environmentally sealed and desiccated aluminum drum-type container designed to transport the W88/Mk5 Reentry Body Assembly. The H1514 is cylindrical except for a portion of its base, which is 36" square and 3" high and contains the forklift openings. Our mock H1514 retains the dimensions and shape of the real H1514 in a lighter form that is not sealed and does not have ports for desiccation.

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Gamma-ray transport describes the way in which high-energy photons interact with matter. There are many well established, general purpose gamma transport calculation frameworks (such as GEANT4, MCNP, PARTISN, and GADRAS) that allow for complex generalized calculations, but they are typically not designed to be integrated into other multi-process, multi-platform applications, not designed for rapid computation, or their complexity leads to user errors. In this report, we introduce InterScatter: a deterministic simulation designed to quickly and easily calculate gamma-ray transport spectra for a 1D shielding geometry.

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This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledge gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?

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A wide-ranging analysis of water vulnerability across the Pacific — including the U.S., China, Russia and Japan — has identified hundreds of locations where energy production depends upon scarce water supplies. The Sandia National Laboratories study, Mapping Water Consumption for Energy Production Around the Pacific Rim, was published in Environmental Research Letters. Prepared for the Asia-Pacific Economic Corporation (APEC), the first-of-its-kind report maps out every power plant, refinery and mine in 21 Asian-Pacific economies that rely on fresh water for energy. Simultaneously, it shows the data in context to regions at high to extreme risk of drought and dwindling natural water supplies.

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The diffusion through shells consisting of either a single conducting or double conducting layers are examined. Exterior drives resulting from Electromagnetic Radiation (EMR), Electromagnetic Pulse (EMP), nearby (indirect) lightning, and DC (low frequency) magnetic fields are used. Both the interior field and the induced voltage from a maximally oriented and sized single turn loop are estimated. It is shown that the loop voltage with the empty cavity bounds the case where the center region is excluded by a conducting object. The cases of interior magnetic and electric fields from an exterior magnetic drive and the interior electric field from an exterior electric drive are both solved; the magnetic interior field from an exterior magnetic drive is the only case that results in a nonzero low frequency penetration.

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Use cases were reviewed with the IDC during trips in January, April and June 2016. In addition, reviews were conducted on the Thursday teleconferences between February and June 2016.

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We are interested in simulating a variety of problems in 3 dimensions (3D) featuring large electric currents. While 2D simulations have been quite informative, cylindrical symmetry may interfere with a problem’s relevant physics. Specifically, all objects in the domain behave as if they are extruded 360°—turning particles into hoops. In dealing with electrical current, this can have serious ramifications on the current pathways. In 3D (r, φ, z) currents can adjust their pathways anywhere along those 360 degrees given the right conditions; however, in 2D (r, z) those pathways can be completely choked off because an insulating hoop, rather than a particle, is present.

Gamma-ray transport describes the way in which high-energy photons (gamma rays and x-rays) interact with matter. There are many well established, general purpose gamma transport calculation frameworks (such as GEANT4, MCNP, PARTISN, and GADRAS [1] [2] [3] [4]) that allow for complex generalized calculations, but they are typically not designed to be integrated into other multi-process, multi-platform applications, not designed for rapid computation, or their complexity leads to user errors. In this report, we introduce InterScatter: a deterministic simulation designed to quickly and easily calculate gamma-ray transport spectra for a 1D shielding geometry.

Extensive study of photorefractive polymeric composites photosensitized with semiconductor nanocrystals has yielded data indicating that the inclusion of such nanocrystals enhances the charge-carrier mobility, and subsequently leads to a reduction in the photorefractive response time. Unfortunately, the included nanocrystals may also act as a source of deep traps, resulting in diminished diffraction efficiencies as well as reduced two beam coupling gain coefficients. Nonetheless, previous studies indicate that this problem is mitigated through the inclusion of semiconductor nanocrystals possessing a relatively narrow band-gap. Here, we fully exploit this property by doping PbS nanocrystals into a newly formulated photorefractive composite based on molecular triphenyldiamine photosensitized with C60. Through this approach, response times of 399 μs are observed, opening the door for video and other high-speed applications. It is further demonstrated that this improvement in response time occurs with little sacrifice in photorefractive efficiency, with internal diffraction efficiencies of 72% and two-beam-coupling gain coefficients of 500 cm-1 being measured. A thorough analysis of the experimental data is presented, supporting the hypothesized mechanism of enhanced charge mobility without the accompaniment of superfluous traps. It is anticipated that this approach can play a significant role in the eventual commercialization of this class of materials.

In this formation of nano-particles during coal char combustion, the vaporization of inorganic components in char and the subsequent homogeneous particle nucleation, heterogeneous condensation, coagulation, and coalescence play decisive roles. Furthermore, conventional measurements cannot provide detailed information on the dynamics of nano-particle formation and evolution, In this study, a sophisticated intrinsic char kinetics model that considers ash effects (including ash film formation, ash dilution, and ash vaporization acting in tandem), both oxidation and gasification by CO₂ and H₂O, homogeneous particle nucleation, heterogeneous vapor condensation, coagulation, and and coalescence mechanisms is developed and used to compare the temporal evolution of the number and size of nano-particles during coal char particle combustion as a function of char particle size, ash content, and oxygen content in O₂/N₂ and O₂/CO₂ atmospheres .

Active participation in international R&D is crucial for achieving the UFD long-term goals of conducting “experiments to fill data needs and confirm advanced modeling approaches” (by 2015) and of having a “robust modeling and experimental basis for evaluation of multiple disposal system options” (by 2020). DOE’s Office of Nuclear Energy (NE) and its Office of Used Fuel Disposition Research and Development (UFD) have developed a strategic plan to advance cooperation with international partners. The international collaboration on the evaluation of crystalline disposal media at Sandia National Laboratories (SNL) in FY16 focused on the following four activities: (1) thermal-hydrologic-mechanical-chemical modeling single fracture evolution; (2) simulations of flow and transport in Bedrichov Tunnel, Czech Republic, (3) completion of streaming potential testing at Korean Atomic Energy Research Institute (KAERI), and (4) technical data exchange with KAERI on thermal-hydrologic-mechanical (THM) properties and specifications of bentonite buffer materials. The first two activities are part of the Development of Coupled Models and their Validation against Experiments (DECOVALEX-2015) project.

Community energy planning is a vital component of successful energy resource development and project implementation. Planning can help tribes develop a shared vision and strategies to accomplish their energy goals. This paper explores the benefits of an asset-based approach to tribal community energy planning. While a framework for community energy planning and federal funding already exists, some areas of difficulty in the planning cycle have been identified. This paper focuses on developing a planning framework that offsets those challenges. The asset-based framework described here takes inventory of a tribe’s capital assets, such as: land capital, human capital, financial capital, and political capital. Such an analysis evaluates how being rich in a specific type of capital can offer a tribe unique advantages in implementing their energy vision. Finally, a tribal case study demonstrates the practical application of an asset-based framework.

Lignin valorization is viewed as a key for the development of a cost effective lignocellulosic biorefinery, and synthetic biology tools would play an important role in the construction of an efficient chassis towards this goal. In this study, we have employed a hybrid promoter engineering approach for the construction of higher strength phenolics inducible promoters.

This paper uses molecular dynamics simulations to study surface and interface properties of PdH_x that are relevant to hydrogen storage applications. In particular, surface energies, interfacial energies, surface diffusivities, and surface segregations are all determined as a function of temperature and composition. During the course of the calculations, we demonstrated robust molecular dynamics methods that can result in highly converged finite temperature properties. Challenging examples include accurate calculations of hydrogen surface diffusivities that account for all possible atomic jump mechanisms, and constructions of surface segregation composition profiles that have negligible statistical errors. Our robust calculations reveal that the Arrhenius plots of hydrogen surface diffusion is ideally linear at low compositions, and becomes nonlinear at high compositions. The fundamental cause for this behavior has been identified. This nonlinear surface diffusion behavioe is also in good agreement with available experimental data for bulk diffusion. The implication of our calculated properties on hydrogen storage application discussed.

We describe a very compact (0.9 m high, 0.4 m diameter, 40 kg) battery operable neutron scatter camera designed for field deployment. Unlike most other systems, the configuration of the sixteen liquid-scintillator detection cells are arranged to provide omnidirectional (4π) imaging with sensitivity comparable to a conventional two-plane system. Although designed primarily to operate as a neutron scatter camera for localizing energetic neutron sources, it also functions as a Compton camera for localizing gamma sources. In addition to describing the radionuclide source localization capabilities of this system, we demonstrate how it provides neutron spectra that can distinguish plutonium metal from plutonium oxide sources, in addition to the easier task of distinguishing AmBe from fission sources.

Recent advances in nanotechnology have enabled researchers to control individual quantum mechanical objects with unprecedented accuracy, opening the door for both quantum and extreme-scale conventional computing applications. As these devices become larger and more complex, the ability to design them such that they can be simply controlled becomes a daunting and computationally infeasible task. Here, motivated by ideas from compressed sensing, we introduce a protocol for the Compressed Optimization of Device Architectures (CODA). It leads naturally to a metric for benchmarking device performance and optimizing device designs, and provides a scheme for automating the control of gate operations and reducing their complexity. Because CODA is computationally efficient, it is readily extensible to large systems. As a result, we demonstrate the CODA benchmarking and optimization protocols through simulations of up to eight quantum dots in devices that are currently being developed experimentally for quantum computation.

Radiocarbon in CO2 (14CO2) measurements can aid in discriminating between fast (<1 year) and slower (>5–10 years) cycling of C between the atmosphere and the terrestrial biosphere due to the 14C disequilibrium between atmospheric and terrestrial C. However, 14CO2 in the atmosphere is typically much more strongly impacted by fossil fuel emissions of CO2, and, thus, observations often provide little additional constraints on respiratory flux estimates at regional scales. Here we describe a data set of 14CO2 observations from a tall tower in northern Wisconsin (USA) where fossil fuel influence is far enough removed that during the summer months, the biospheric component of the 14CO2 budget dominates. We find that the terrestrial biosphere is responsible for a significant contribution to 14CO2 that is 2–3 times higher than predicted by the Carnegie-Ames-Stanford approach terrestrial ecosystem model for observations made in 2010. This likely includes a substantial contribution from the North American boreal ecoregion, but transported biospheric emissions from outside the model domain cannot be ruled out. The 14CO2 enhancement also appears somewhat decreased in observations made over subsequent years, suggesting that 2010 may be anomalous. With these caveats acknowledged, we discuss the implications of the observation/model comparison in terms of possible systematic biases in the model versus short-term anomalies in the observations. Going forward, this isotopic signal could be exploited as an important indicator to better constrain both the long-term carbon balance of terrestrial ecosystems and the short-term impact of disturbance-based loss of carbon to the atmosphere.

Four sets of nonreactive solute transport experiments were conducted with micromodels. Each set consisted of three experiments with one variable, i.e., flow velocity, grain diameter, pore-aspect ratio, and flow-focusing heterogeneity. The data sets were offered to pore-scale modeling groups to test their numerical simulators. Each set consisted of two learning experiments, for which all results were made available, and one challenge experiment, for which only the experimental description and base input parameters were provided. The experimental results showed a nonlinear dependence of the transverse dispersion coefficient on the Peclet number, a negligible effect of the pore-aspect ratio on transverse mixing, and considerably enhanced mixing due to flow focusing. Five pore-scale models and one continuum-scale model were used to simulate the experiments. Of the pore-scale models, two used a pore-network (PN) method, two others are based on a lattice Boltzmann (LB) approach, and one used a computational fluid dynamics (CFD) technique. The learning experiments were used by the PN models to modify the standard perfect mixing approach in pore bodies into approaches to simulate the observed incomplete mixing. The LB and CFD models used the learning experiments to appropriately discretize the spatial grid representations. For the continuum modeling, the required dispersivity input values were estimated based on published nonlinear relations between transverse dispersion coefficients and Peclet number. Comparisons between experimental and numerical results for the four challenge experiments show that all pore-scale models were all able to satisfactorily simulate the experiments. The continuum model underestimated the required dispersivity values, resulting in reduced dispersion. The PN models were able to complete the simulations in a few minutes, whereas the direct models, which account for the micromodel geometry and underlying flow and transport physics, needed up to several days on supercomputers to resolve the more complex problems.

A transportable fast neutron detection system has been designed and constructed for measuring neutron energy spectra and flux ranging from tens to hundreds of MeV. The transportability of the spectrometer reduces the detector-related systematic bias between different neutron spectra and flux measurements, which allows for the comparison of measurements above or below ground. The spectrometer will measure neutron fluxes that are of prohibitively low intensity compared to the site-specific background rates targeted by other transportable fast neutron detection systems. To measure low intensity high-energy neutron fluxes, a conventional capture-gating technique is used for measuring neutron energies above 20 MeV and a novel multiplicity technique is used for measuring neutron energies above 100 MeV. The spectrometer is composed of two Gd containing plastic scintillator detectors arranged around a lead spallation target. To calibrate and characterize the position dependent response of the spectrometer, a Monte Carlo model was developed and used in conjunction with experimental data from gamma ray sources. Multiplicity event identification algorithms were developed and used with a Cf-252 neutron multiplicity source to validate the Monte Carlo model Gd concentration and secondary neutron capture efficiency. The validated Monte Carlo model was used to predict an effective area for the multiplicity and capture gating analyses. For incident neutron energies between 100 MeV and 1000 MeV with an isotropic angular distribution, the multiplicity analysis predicted an effective area of 500 cm2 rising to 5000 cm2. For neutron energies above 20 MeV, the capture-gating analysis predicted an effective area between 1800 cm2 and 2500 cm2. The multiplicity mode was found to be sensitive to the incident neutron angular distribution.

In a common electric power plant, heat is used to boil water into steam which drives a turbine. The steam from the turbine outlet is condensed with cooling water. This is the common Rankine cycle and, even after decades of development is relatively inefficient and water intensive. Alternatively, a closed Brayton cycle recirculates the working fluid, and the turbine exhaust is used in a recuperating heat exchanger to heat the turbine feed. A "supercritical cycle' is a closed Brayton cycle in which the working fluid, such as supercritical carbon dioxide (sCO2), is maintained above the critical point during the compression phase of the cycle. The key property of the fluid near its critical point is its higher gas density, closer to that of a liquid than of a gas, allowing for the pumping power in the compressor to be significantly reduced resulting in improved efficiency. Other advantages include smaller component size and the reduced use of water, not only due to the increased efficiency, but also due sensible heat rejection which facilitates dry air cooling compared to air-cooled steam condensers. A Sandia National Laboratories commercialization review concluded that the technology has applicability across various power generation applications including fossil fuels, concentrated solar power and nuclear power. In 2006, Sandia National Laboratories (SNL), recognizing the potential advantages of a higher efficiency power cycle, used internal funds to establish a testing capability and began partnering with the U.S. Department of Energy Office of Nuclear Energy to develop a laboratory-scale test assembly to show the viability of the underlying science and demonstrate system performance. Since that time, SNL has generated power, verified cycle performance, and developed cycle controls and maintenance procedures. The test assembly has successfully operated in different configurations (simple Brayton, waste heat cycle, and recompression) and tested additives to the s-CO2 working fluid. Our current focus is to partner with industry and develop cycle components and control strategies sufficient to support a successful commercial offering. This paper has been developed for the Energy Policy Institute's (EPI's) 6th Annual Energy Policy Research Conference scheduled for 8 & 9 September 2016 in Santa Fe, NM. We describe the cycle in more detail and describe specific benefits and applications. The paper will also include current technology development activities and future plans.

Alaska oil fields provide an important, but diminishing, portion of the crude oil processed by Alaska and U.S. West Coast refineries. Production of crude oil in Alaska is being stressed by declining production in mature fields, high costs for developing and producing new fields, increasing competition from tight oil production in the Lower 48 states, and low global oil prices. The National Transportation Fuel Model is a network model of petroleum infrastructure in the Lower 48 states and portions of Canada developed at Sandia National Laboratories. It provides a simulation capability for analysis of system-wide responses to stressing events. Until now, however, this model did not explicitly include the petroleum infrastructure of Alaska and the transport of crude oil by marine shipments from Alaska to West Coast refineries. This paper describes the methods and information requirements for adding Alaska infrastructure to the National Transportation Fuel Model, provides an overview of the new Alaska portion of the model, and presents an example simulation of a closure of a large San Francisco refinery.

The purpose of this paper is to investigate the structural behavior of aluminum alloys used in the aerospace industry when exposed to conditions similar to those of an accident scenario, such as a fuel fire. This study focuses on the role that the aluminum oxide layer plays in the deformation and the strength of the alloy above melting temperature. To replicate some of the thermal and atmospheric conditions that the alloys might experience in an accident scenario, aluminum rod specimens were subjected to temperatures near to or above their melting temperature in air, nitrogen, and vacuum environments. The characteristics of their deformation, such as geometry and rate of deformation, were observed. Tests were conducted by suspending aluminum rods vertically from an enclosure. This type of experiment was performed in two different environments: air and nitrogen. The change in environments allowed the effects of the oxide layer on the material strength to be analyzed by inhibiting the growth of the oxide layer. Observations were reported from imaging taken during the experiment showing creep behavior of aluminum alloys at elevated temperatures and time to failure. In addition, an example of tensile load-displacement data obtained in air and vacuum was reported to understand the effect of oxide layer on aluminum deformation and strength.

We report the successful growth of high-quality SrO films on highly-ordered pyrolytic graphite (HOPG) and single-layer graphene by molecular beam epitaxy. The SrO layers have (001) orientation as confirmed by X-ray diffraction (XRD) while atomic force microscopy measurements show continuous pinhole-free films having rms surface roughness of <1.5 Å. Transport measurements of exfoliated graphene after SrO deposition show a strong dependence between the Dirac point and Sr oxidation. Subsequently, the SrO is leveraged as a buffer layer for more complex oxide integration via the demonstration of (001) oriented SrTiO3 grown atop a SrO/HOPG stack.

The slowing of Moore's law offers IEEE and its members the unique opportunity to influence research toward continued growth in computing performance.

Molecular dynamics simulations have been used to analyse microstructures of CdTe films grown on {112} surfaces of zinc-blende CdS. Interestingly, CdTe films grow in 331 orientations as opposed to 112 epitaxial orientations. At the CdTe-{331}/CdS-{112} interface, however, there exists an axis that is parallel to the 110 orientation of both CdS and CdTe. It is the direction orthogonal to this 110 that becomes different, being 116 for CdTe and 111 for CdS, respectively. Missing CdTe-{110} planes are found along the 110 axis, suggesting that the misfit strain is released by the conventional misfit dislocation mechanism along this axis. In the orthogonal axis, the misfit strain is found to be more effectively released by the new grain orientation mechanism. Our finding is supported by literature experimental observations of the change of growth direction when Cd0.96Zn0.04Te films are deposited on GaAs. Analyses of energetics clearly demonstrate the cause for the formation of the new orientation, and the insights gained from our studies can help understand the grain structures experimentally observed in lattice mismatched systems.

This paper presents a method for improved auscultation with an electronic stethoscope by estimating and removing the effects of unknown disturbance inputs. By replacing the single transducer in a stethoscope with a dual piezo transducer assembly, it is shown that an inverse dynamic mapping can be used to relate the two measured signals to original directional inputs acting on the stethoscope. Specifically, model inversion is used to estimate and remove physician handling noise from chest sound signals. An experimental test platform which uses a vibration shaker to simulate the desired auscultation signal is used to experimentally demonstrate the feasibility of the dual-piezo stethoscope approach in improving auscultation.

This paper presents a method for improved auscultation with an electronic stethoscope by estimating and removing the effects of unknown disturbance inputs. By replacing the single transducer in a stethoscope with a dual piezo transducer assembly, it is shown that an inverse dynamic mapping can be used to relate the two measured signals to original directional inputs acting on the stethoscope. Specifically, model inversion is used to estimate and remove physician handling noise from chest sound signals. An experimental test platform which uses a vibration shaker to simulate the desired auscultation signal is used to experimentally demonstrate the feasibility of the dual-piezo stethoscope approach in improving auscultation.

We perform molecular dynamics simulations of a coarse-grained model of ionomer melts in an applied oscillating electric field. The frequency-dependent conductivity and susceptibility are calculated directly from the current density and polarization density, respectively. At high frequencies, we find a peak in the real part of the conductivity due to plasma oscillations of the ions. At lower frequencies, the dynamic response of the ionomers depends on the ionic aggregate morphology in the system, which consists of either percolated or isolated aggregates. We show that the dynamic response of the model ionomers to the applied oscillating field can be understood by comparison with relevant time scales in the systems, obtained from independent calculations.

Isotropic von Mises and anisotropic Hill yield surfaces for Al 7079 were fit using experimental data gathered from 12 dog-bone specimens that captured the highly variable microstructural texture of the aluminum alloy. Strain gauges or the digital image correlation technique were utilized to determine the strain histories in the specimen as they were subjected to uniaxial tension. The final yield surface fits displayed a high degree of variability that was dependent upon how the yield functions were calculated, i.e. which size and shape information was used. The findings display that a model with a higher number of anisotropic parameters is needed to better and more consistently capture the anisotropic properties of Al 7079, such as the Barlat, Yld2004-18, model that has 20 parameters.

A method for providing non-diffuse transport of material quantities in arbitrary Lagrangian-Eulerian (ALE) dynamic solid mechanics computations is presented. ALE computations are highly desirable for simulating dynamic problems that incorporate multiple materials and large deformations. Despite the advantages of using ALE for such problems, the method is associated with diffusion of material quantities due to the advection transport step of the computational cycle. This drawback poses great difficulty for applications of material failure for which discrete features are important, but are smeared out as a result of the diffusive advection operation. The focus of this work is an ALE method that incorporates transport of variables on discrete, massless points that move with the velocity field, referred to as Lagrangian material tracers (LMT), and consequently prevents diffusion of certain material quantities of interest. A detailed description of the algorithm is provided along with discussion of its computational aspects. Simulation results include a simple proof of concept, verification using a manufactured solution, and fragmentation of a uniformly loaded thin ring that clearly demonstrates the improvement offered by the ALE LMT method.

Methods for processing recorded data and efficiently screening experimental results from ducted fuel injection (DFI) experiments for soot mitigation in diesel engines are described. Specifically, a method for locating the spray tip in natural luminosity movies is detailed. DFI implementations are analyzed and are seen to significantly lower soot levels.

Open microalgae cultures host a myriad of bacteria, creating a complex system of interacting species that influence algal growth and health. Many algal microbiota studies have been conducted to determine the relative importance of bacterial taxa to algal culture health and physiological states, but these studies have not characterized the interspecies relationships in the microbial communities. We subjected Nanochroloropsis salina cultures to multiple chemical treatments (antibiotics and quorum sensing compounds) and obtained dense time-series data on changes to the microbial community using 16S gene amplicon metagenomic sequencing (21,029,577 reads for 23 samples) to measure microbial taxa-taxa abundance correlations. Short-term treatment with antibiotics resulted in substantially larger shifts in the microbiota structure compared to changes observed following treatment with signaling compounds and glucose. We also calculated operational taxonomic unit (OTU) associations and generated OTU correlation networks to provide an overview of possible bacterial OTU interactions. This analysis identified five major cohesive modules of microbiota with similar co-abundance profiles across different chemical treatments. The Eigengenes of OTU modules were examined for correlation with different external treatment factors. This correlation-based analysis revealed that culture age (time) and treatment types have primary effects on forming network modules and shaping the community structure. Additional network analysis detected Alteromonadeles and Alphaproteobacteria as having the highest centrality, suggesting these species are "keystone" OTUs in the microbial community. Furthermore, we illustrated that the chemical tropodithietic acid, which is secreted by several species in the Alphaproteobacteria taxon, is able to drastically change the structure of the microbiota within 3 h. Taken together, these results provide valuable insights into the structure of the microbiota associated with N. salina cultures and how these structures change in response to chemical perturbations.

Here, a liquid bi-propellant rocket engine and supporting infrastructure has been de-signed, constructed, and tested at New Mexico Institute of Mining and Technology ina cooperative effort with Sandia National Laboratories. The modular engine designconsists of a head-end fuel-oxidizer injector, gaseous H2/02 torch ignitor, combustionchamber, and nozzle modules. The robust modular design allows for rapid config-uration changes and component replacement if damaged in testing.

We calculated the force-extension curves for a flexible polyelectrolyte chain with varying charge separations by performing Monte Carlo simulations of a 5000 bead chain using a screened Coulomb interaction. At all charge separations, the force-extension curves exhibit a Pincus-like scaling regime at intermediate forces and a logarithmic regime at large forces. As the charge separation increases, the Pincus regime shifts to a larger range of forces and the logarithmic regime starts are larger forces. We also found that force-extension curve for the corresponding neutral chain has a logarithmic regime. Decreasing the diameter of bead in the neutral chain simulations removed the logarithmic regime, and the force-extension curve tends to the freely jointed chain limit. In conclusion, this result shows that only excluded volume is required for the high force logarithmic regime to occur.

Aqueous dissolution of silicate glasses and minerals plays a critical role in global biogeochemical cycles and climate evolution. The reactivity of these materials is also important to numerous engineering applications including nuclear waste disposal. The dissolution process has long been considered to be controlled by a leached surface layer in which cations in the silicate framework are gradually leached out and replaced by protons from the solution. This view has recently been challenged by observations of extremely sharp corrosion fronts and oscillatory zonings in altered rims of the materials, suggesting that corrosion of these materials may proceed directly through congruent dissolution followed by secondary mineral precipitation. Here we show that complex silicate material dissolution behaviors can emerge from a simple positive feedback between dissolution-induced cation release and cation-enhanced dissolution kinetics. This self-accelerating mechanism enables a systematic prediction of the occurrence of sharp dissolution fronts (vs. leached surface layers), oscillatory dissolution behaviors and multiple stages of glass dissolution (in particular the alteration resumption at a late stage of a corrosion process). Our work provides a new perspective for predicting long-term silicate weathering rates in actual geochemical systems and developing durable silicate materials for various engineering applications.

An AlN barrier high electron mobility transistor (HEMT) based on the AlN/Al_0.85Ga_0.15N heterostructure was grown, fabricated, and electrically characterized, thereby extending the range of Al composition and bandgap for AlGaN channel HEMTs. An etch and regrowth procedure was implemented for source and drain contact formation. A breakdown voltage of 810 V was achieved without a gate insulator or field plate. Excellent gate leakage characteristics enabled a high I_on/I_off current ratio greater than 10⁷ and an excellent subthreshold slope of 75 mV/decade. A large Schottky barrier height of 1.74 eV contributed to these results. In conclusion, the room temperature voltage-dependent 3-terminal off-state drain current was adequately modeled with Frenkel-Poole emission.

Demonstration of Al0_0.3Ga_0.7N PN diodes grown with breakdown voltages in excess of 1600 V is reported. The total epilayer thickness is 9.1 μm and was grown by metal-organic vapour-phase epitaxy on 1.3-mm-thick sapphire in order to achieve crack-free structures. A junction termination edge structure was employed to control the lateral electric fields. A current density of 3.5 kA/cm² was achieved under DC forward bias and a reverse leakage current <3 nA was measured for voltages <1200 V. The differential on-resistance of 16 mΩ cm² is limited by the lateral conductivity of the n-type contact layer required by the front-surface contact geometry of the device. An effective critical electric field of 5.9 MV/cm was determined from the epilayer properties and the reverse current–voltage characteristics. To our knowledge, this is the first aluminium gallium nitride (AlGaN)-based PN diode exhibiting a breakdown voltage in excess of 1 kV. Finally, we note that a Baliga figure of merit (V_br²/R_spec,on) of 150 MW/cm² found is the highest reported for an AlGaN PN diode and illustrates the potential of larger-bandgap AlGaN alloys for high-voltage devices.

Rimmed grooves, lineations and elongate craters around Mare Imbrium shape much of the nearside Moon. This pattern was coined the Imbrium Sculpture, and it was originally argued that it must have been formed by a giant oblique (∼30°) impact, a conclusion echoed by later studies. Some investigators, however, noticed that many elements of the Imbrium Sculpture are not radial to Imbrium, thereby implicating an endogenic or structural origin. Here we use these non-radial trends to conclude that the Imbrium impactor was a proto-planet (half the diameter of Vesta), once part of a population of large proto-planets in the asteroid belt. Such independent constraints on the sizes of the Imbrium and other basin-forming impactors markedly increase estimates for the mass in the asteroid belt before depletion caused by the orbital migration of Jupiter and Saturn. Moreover, laboratory impact experiments, shock physics codes and the groove widths indicate that multiple fragments (up to 2% of the initial diameter) from each oblique basin-forming impactor, such as the one that formed Imbrium, should have survived planetary collisions and contributed to the heavy impact bombardment between 4.3 and 3.8 billion years ago.

Plasmonic lasers (spasers) generate coherent surface plasmon polaritons (SPPs) and could be realized at subwavelength dimensions in metallic cavities for applications in nanoscale optics. Plasmonic cavities are also utilized for terahertz quantum-cascade lasers (QCLs), which are the brightest available solid-state sources of terahertz radiation. A long standing challenge for spasers that are utilized as nanoscale sources of radiation, is their poor coupling to the far-field radiation. Unlike conventional lasers that could produce directional beams, spasers have highly divergent radiation patterns due to their subwavelength apertures. Here, we theoretically and experimentally demonstrate a new technique for implementing distributed feedback (DFB) that is distinct from any other previously utilized DFB schemes for semiconductor lasers. The so-termed antenna-feedback scheme leads to single-mode operation in plasmonic lasers, couples the resonant SPP mode to a highly directional far-field radiation pattern, and integrates hybrid SPPs in surrounding medium into the operation of the DFB lasers. Experimentally, the antenna-feedback method, which does not require the phase matching to a well-defined effective index, is implemented for terahertz QCLs, and single-mode terahertz QCLs with a beam divergence as small as 4° × 4° are demonstrated, which is the narrowest beam reported for any terahertz QCL to date. Moreover, in contrast to a negligible radiative field in conventional photonic band-edge lasers, in which the periodicity follows the integer multiple of half-wavelengths inside the active medium, antennafeedback breaks this integer limit for the first time and enhances the radiative field of the lasing mode. Terahertz lasers with narrow-beam emission will find applications for integrated as well as standoff terahertz spectroscopy and sensing. The antenna-feedback scheme is generally applicable to any plasmonic laser with a Fabry-Perot cavity irrespective of its operating wavelength and could bring plasmonic lasers closer to practical applications.

Pump-probe polarization anisotropy measurements with 15 fs pulses are employed to investigate the electronic structure of PbS quantum dots. Here, the initial anisotropy at the bandgap is anomalously low (<0.1) and suggests large electronic couplings.

Of the non-corrupted data collected by the Orbiting Experiment (forté) satellite’s Photo-Diode Detector during the year 2001, I estimate that 7.9% of 914 894 signals are noise. My result differs dramatically from Guillen’s estimate of 96%. To arrive at this estimate, I used Gaussian mixture model (GMM) clustering–unsupervised machine learning–to aggregate the wave forms into groups based on the absolute value of the lowest 25 positive frequency discrete Fourier transform coefficients. Then, I marked several of the groups as noise by inspecting a random sampling of wave forms from each group. Marking groups as either noise or non-noise is a supervised binary classification operation. After removing the signals in noise groups from further consideration, I clustered the remaining signals into families. Again, I used a GMM, but for the familial clustering I used a Non-Negative Matrix Factorization feature vector transform. The result was 9 distinct families of lightning signals, as well as a second stage of noise filtering. To efficiently represent the entirety of the signal space, I broke each family into deciles based on their distance from the family mean. In this case, distance means the log-likelihood based on the GMM. Signals in lower deciles are more similar in shape and amplitude to their family average. I took the top 200 samples from each decile of each group, resulting in 18 000 signals. These signal approximately represent the entirety of the forté observations. To represent outliers, I also kept a zoo of the 1000 signals furthest from any family’s average. All told, the resulting data set represents the forté data with a reduction of about 51:1. To allow synthesis of an arbitrarily large number of test signals, I also captured each family’s average signal and the time-sample covariance matrix over the signals in each family. Using these two pieces of information, I can synthesize new waveforms by using a Gaussian random realization from the family average and covariance matrix. I wrote a program to test the synthesis quality. The program shows me two signals on the screen, one synthesized and one randomly drawn from the data. I attempted to identify the synthesized signal. Although the synthesis is imperfect, in an A/B comparison I only correctly chose the synthesized signal 36% of the time.

Graph algorithms are challenging to parallelize on manycore architectures due to complex data dependencies and irregular memory access. We consider the well studied problem of coloring the vertices of a graph. In many applications it is important to compute a coloring with few colors in near-lineartime. In parallel, the optimistic (speculative) coloring method by Gebremedhin and Manne is the preferred approach but it needs to be modified for manycore architectures. We discuss a range of implementation issues for this vertex-based optimistic approach. We also propose a novel edge-based optimistic approach that has more parallelism and is better suited to GPUs. We study the performance empirically on two architectures(Xeon Phi and GPU) and across many data sets (from finite element problems to social networks). Our implementation uses the Kokkos library, so it is portable across platforms. We show that on GPUs, we significantly reduce the number of colors (geometric mean 4X, but up to 48X) as compared to the widely used cuSPARSE library. In addition, our edge-based algorithm is 1.5 times faster on average than cuSPARSE, where it hasspeedups up to 139X on a circuit problem. We also show the effect of the coloring on a conjugate gradient solver using multi-colored Symmetric Gauss-Seidel method as preconditioner, the higher coloring quality found by the proposed methods reduces the overall solve time up to 33% compared to cuSPARSE.

Application performance data accounting for resource contention and other external influences is highly coveted and extremely difficult to obtain. «Why did my application's performance change from the last time it ran?» is a question shared by application developers, program analysts, and system administrators. The answer to this question impacts nearly all programmatic and R&D efforts related to high-performance computing (HPC). Lightweight, right-fidelity monitoring infrastructures that can gather relevant application and resource performance data across the entire HPC platform can help address this research topic. This short technical paper will formally define an ongoing research effort to define the needed metrics and methods that distill the vast quantities of available data to a minimum set of actionable and interpretable quantities that can be used by application developers, system administrators, production analysts, and HPC platform designers for their respective production and R&D focus areas.

Issues of High Performance Computer (HPC) system diagnosis, automated system management, and resource-aware computing, are all dependent on high fidelity, system wide, persistent monitoring. Development and deployment of an effective persistent system wide monitoring service at large-scale presents a number of challenges, particularly when collecting data at the granularities needed to resolve features of interest and obtain early indication of significant events on the system. In this paper we provide experiences from our developments on and two-year deployment of our Lightweight Distributed Metric Service (LDMS) monitoring system on NCSA's 27,648 node Blue Waters system. We present monitoring related challenges and issues and their effects on the major functional components of general monitoring infrastructures and deployments: Data Sampling, Data Aggregation, Data Storage, Analysis Support, Operations, and Data Stewardship. Based on these experiences, we providerecommendations for effective development and deployment of HPC monitoring systems.

Over the past decade, platforms at Los AlamosNational Laboratory (LANL) have experienced large increases in complexity and scale to reach computational targets. The changes to the compute platforms have presented new challenges to the production monitoring systems in which they must not only cope with larger volumes of monitoring data, but also must provide new capabilities for the management, distribution, and analysis of this data. This schema must support both real-time analysis for alerting on urgent issues, as well as analysis of historical data for understanding performance issues and trends in systembehavior. This paper presents the design of our proposed next-generation monitoring system, as well as implementation details for an initial deployment. This design takes the form of a multi-stage data processing pipeline, including a scalable cluster for data aggregation and early analysis, a message broker for distribution of this data to varied consumers, and an initial selection of consumer services for alerting and analysis. We will also present estimates of the capabilities and scale required to monitor two upcoming compute platforms at LANL.

Scalable sparse LU factorization is critical for efficient numerical simulation of circuits and electrical power grids. In this work, we present a new scalable sparse direct solver called Basker. Basker introduces a new algorithm to parallelize the Gilbert-Peierls algorithm for sparse LU factorization. As architectures evolve, there exists a need for algorithms that are hierarchical in nature to match the hierarchy in thread teams, individual threads, and vector level parallelism. Basker is designed to map well to this hierarchy in architectures. There is also a need for data layouts to match multiple levels of hierarchy in memory. Basker uses a two-dimensional hierarchical structure of sparse matrices that maps to the hierarchy in the memory architectures and to the hierarchy in parallelism. We present performance evaluations of Basker on the Intel SandyBridge and Xeon Phi platforms using circuit and power grid matrices taken from the University of Florida sparse matrix collection and from Xyce circuit simulations. Basker achieves a geometric mean speedup of 5.91× on CPU (16 cores) and 7.4× on Xeon Phi (32 cores) relative to KLU. Basker outperforms Intel MKL Pardiso (PMKL) by as much as 30× on CPU (16 cores) and 7.5× on Xeon Phi (32 cores) for low fill-in circuit matrices. Furthermore, Basker provides 5.4× speedup on a challenging matrix sequence taken from an actual Xyce simulation.

Ultrafast pure-rotational CARS is applied to an aluminized ammonium-perchlorate propellant flame. Background-free spectra were acquired in this challenging high-temperature, particle-laden environment and successfully fit for temperature and oxygen/nitrogen ratio using a simple theoretical model.

Aluminized propellants produce molten particulates of variable size and temperature. In this work, sizes and three-dimensional positions are determined using digital in-line holography with a pulsed laser. Simultaneously, particle temperatures are measured using two-color pyrometry.

Given the unique optical properties of LiF, it is often used as an observation window in high-temperature and -pressure experiments; hence, estimates of its transmission properties are necessary to interpret observations. Since direct measurements of the thermal conductivity of LiF at the appropriate conditions are difficult, we resort to molecular simulation methods. Using an empirical potential validated against ab initio phonon density of states, we estimate the thermal conductivity of LiF at high temperatures (1000-4000 K) and pressures (100-400 GPa) with the Green-Kubo method. We also compare these estimates to those derived directly from ab initio data. To ascertain the correct phase of LiF at these extreme conditions, we calculate the (relative) phase stability of the B1 and B2 structures using a quasiharmonic ab initio model of the free energy. We also estimate the thermal conductivity of LiF in an uniaxial loading state that emulates initial stages of compression in high-stress ramp loading experiments and show the degree of anisotropy induced in the conductivity due to deformation.

Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems - enabling asynchronous data transfers, so that applications may fully utilize all CPU resources while simultaneously sharing data amongst remote nodes. We examined this network-induced memory contention (NiMC), the interactions between RDMA and the memory subsystem when applications and out-of-band services compete for memory resources, and NiMC's resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantified NiMC and show that NiMC's impact grows with scale resulting in up to 3X performance degradation at scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. We also evaluated three potential techniques to reduce NiMC's performance impact, namely hardware offloading, core reservation and software-based network throttling. While all three of these solutions show promise, we provide guidelines that help select the best solution for a given environment.

All many-core systems require fine-grained shared memory parallelism, however the most efficient way to extract such parallelism is far from trivial. Fine-grained parallel algorithms face various performance trade-offs related to tasking, accesses to global data-structures, and use of shared cache. While programming models provide high level abstractions, such as data and task parallelism, algorithmic choices still remain open on how to best implement irregular algorithms, such as sparse factorizations, while taking into account the trade-offs mentioned above. In this paper, we compare these performance trade-offs for task and data parallelism on different hardware architectures such as Intel Sandy Bridge, Intel Xeon Phi, and IBM Power8. We do this by comparing the scaling of a new task-parallel incomplete sparse Cholesky factorization called Tacho and a new data-parallel incomplete sparse LU factorization called Basker. Both solvers utilize Kokkos programming model and were developed within the ShyLU package of Trilinos. Using these two codes we demonstrate how high-level programming changes affect performance and overhead costs on multiple multi/many-core systems. We find that Kokkos is able to provide comparable performance with both parallel-for and task/futures on traditional x86 multicores. However, the choice of which high-level abstraction to use on many-core systems depends on both the architectures and input matrices.

Aluminized propellants produce molten particulates of variable size and temperature. In this work, sizes and three-dimensional positions are determined using digital in-line holography with a pulsed laser. Simultaneously, particle temperatures are measured using two-color pyrometry.

Digital in-line holography (DIH) quantifies the fragments formed when a drop impacts a thin film. High-speed recording allows for quantification of transient dynamics. For the viscous liquids investigated here, a multimodal size distribution is observed.

The in-situ hydrolysis and subsequent condensation reaction of the chemical agent simulant diethyl chlorophosphate (DECP) was characterized by high-resolution 31P NMR spectroscopy following the addition of water in sub-equimolar concentrations. The identification and quantification of the multiple pyrophosphate and larger polyphosphate chemical species formed through a series of self-condensation reactions are reported. The DECP hydrolysis kinetics and distribution of breakdown species was strongly influenced by the water concentration and reaction temperature.