Mitigating corrosion remains a daunting challenge due to localized, nanoscale corrosion events that are poorly understood but are known to cause unpredictable variations in material longevity. Here, the most recent advances in liquid-cell transmission electron microscopy were employed to capture the advent of localized aqueous corrosion in carbon steel at the nanoscale and in real time. Localized corrosion initiated at a triple junction formed by a solitary cementite grain and two ferrite grains and then continued at the electrochemically-active boundary between these two phases. With this analysis, we identified facetted pitting at the phase boundary, uniform corrosion rates from the steel surface, and data that suggest that a re-initiating galvanic corrosion mechanism is possible in this environment. These observations represent an important step toward atomically defining nanoscale corrosion mechanisms, enabling the informed development of next-generation inhibition technologies and the improvement of corrosion predictive models.
The competition between ductile rupture mechanisms in high-purity Cu and other metals is sensitive to the material composition and loading conditions, and subtle changes in the metal purity can lead to failure either by void coalescence or Orowan Alternating Slip (OAS). In situ X-ray computed tomography tensile tests on 99.999% purity Cu wires have revealed that the rupture process involves a sequence of damage events including shear localization; growth of micron-sized voids; and coalescence of microvoids into a central cavity prior to the catastrophic enlargement of the coalesced void via OAS. This analysis has shown that failure occurs in a collaborative rather than strictly competitive manner. In particular, strain localization along the shear band enhanced void nucleation and drove the primary coalescence event, and the size of the resulting cavity and consumption of voids ensured a transition to the OAS mechanism rather than continued void coalescence. Additionally, the tomograms identified examples of void coalescence and OAS growth of individual voids at all stages of the failure process, suggesting that the transition between the different mechanisms was sensitive to local damage features, and could be swayed by collaboration with other damage mechanisms. The competition between the different damage mechanisms is discussed in context of the material composition, the local damage history, and collaboration between the mechanisms.
Curwen, Christopher A.; Reno, J.L.; Williams, Benjamin S.
Changing the length of a laser cavity is a simple technique for continuously tuning the wavelength of a laser but is rarely used for broad fractional tuning, with a notable exception of the vertical-cavity surface-emitting laser (VCSEL)1,2. This is because, to avoid mode hopping, the cavity must be kept optically short to ensure a large free spectral range compared to the gain bandwidth of the amplifying material. Terahertz quantum-cascade lasers are ideal candidates for such a short cavity scheme as they demonstrate exceptional gain bandwidths (up to octave spanning)3 and can be integrated with broadband amplifying metasurfaces4. We present such a quantum-cascade metasurface-based vertical-external-cavity surface-emitting laser (VECSEL) that exhibits over 20% continuous fractional tuning of a single laser mode. Such tuning is possible because the metasurface has subwavelength thickness, which allows lasing on low-order Fabry–Pérot cavity modes. Good beam quality and high output power are simultaneously obtained.
Tetradymite-structured chalcogenides such as bismuth telluride (Bi 2 Te 3 ) are of significant interest for thermoelectric energy conversion and as topological insulators. Dislocations play a critical role during synthesis and processing of such materials and can strongly affect their functional properties. The dislocations between quintuple layers present special interest since their core structure is controlled by the van der Waals interactions between the layers. In this work, using atomic-resolution electron microscopy, we resolve the basal dislocation core structure in Bi 2 Te 3 , quantifying the disregistry of the atomic planes across the core. We show that, despite the existence of a stable stacking fault in the basal plane gamma surface, the dislocation core spreading is mainly due to the weak bonding between the layers, which leads to a small energy penalty for layer sliding parallel to the van der Waals gap. Calculations within a semidiscrete variational Peierls-Nabarro model informed by first-principles calculations support our experimental findings.
In a traditional data-processing pipeline, waveforms are acquired, a detector makes the signal detections (i.e., arrival times, slownesses, and azimuths) and passes them to an associator. The associator then links the detections to the fitting-event hypotheses to generate an event bulletin. Most of the time, this traditional pipeline requires substantial human-analyst involvement to improve the quality of the resulting event bulletin. For the year 2017, for example, International Data Center (IDC) analysts rejected about 40% of the events in the automatic bulletin and manually built 30% of the legitimate events. We propose an iterative processing framework (IPF) that includes a new data-processing module that incorporates automatic analyst behaviors (auto analyst [AA]) into the event-building pipeline. In the proposed framework, through an iterative process, the AA takes over many of the tasks traditionally performed by human analysts. These tasks can be grouped into two major processes: (1) evaluating small events with a low number of location-defining arrival phases to improve their formation; and (2) scanning for and exploiting unassociated arrivals to form potential events missed by previous association runs. To test the proposed framework, we processed a two-week period (15–28 May 2010) of the signal-detections dataset from the IDC. Comparison with an expert analyst-reviewed bulletin for the same time period suggests that IPF performs better than the traditional pipelines (IDC and baseline pipelines). Most of the additional events built by the AA are low-magnitude events that were missed by these traditional pipelines. The AA also adds additional signal detections to existing events, which saves analyst time, even if the event locations are not significantly affected.
The capability to discriminate low-magnitude earthquakes from low-yield anthropogenic sources, both detectable only at local distances, is of increasing interest to the event monitoring community. We used a dataset of seismic events in Utah recorded during a 14-day period (1–14 January 2011) by the University of Utah Seismic Stations network to perform a comparative study of event classification at local scale using amplitude ratio (AR) methods and a machine learning (ML) approach. The event catalog consists of 7377 events with magnitudes MC ranging from −2 and lower up to 5.8. Events were subdivided into six populations based on location and source type: tectonic earthquakes (TEs), mining-induced events (MIEs), and mining blasts from four known mines (WMB, SMB, LMB, and CQB). The AR approach jointly exploits Pg-to-Sg phase ARs and Rg-to-Sg spectral ARs in multivariate quadratic discriminant functions and was able to classify 370 events with high signal quality from the three groups with sufficient size (TE, MIE, and SMB). For that subset of the events, the method achieved success rates between about 80% and 90%. The ML approach used trained convolutional neural network (CNN) models to classify the populations. The CNN approach was able to classify the subset of events with accuracies between about 91% and 98%. Because the neural network approach does not have a minimum signal quality requirement, we applied it to the entire event catalog, including the abundant extremely low-magnitude events, and achieved accuracies of about 94%–100%. We compare the AR and ML methodologies using a broad set of criteria and conclude that a major advantage to ML methods is their robustness to low signal-to-noise ratio data, allowing them to classify significantly smaller events.
Kinesin motors and their associated filaments, microtubules, are essential to many biological processes. The motor and filament system can be reconstituted in vitro with the surface-adhered motors transporting the filaments along the surface. In this format, the system has been used to study active self-assembly and to power microdevices or perform analyte detection. However, fundamental properties of the system, such as the spacing of the kinesin motors bound to the microtubule and the dynamics of binding, remain poorly understood. We show that Fluorescence Interference Contrast (FLIC) microscopy can illuminate the exact height of the microtubule, which for a sufficiently low surface density of kinesin, reveals the locations of the bound motors. We examine the spacing of the kinesin motors on the microtubules at various kinesin surface densities and compare the results with theory. FLIC reveals that the system is highly dynamic, with kinesin binding and unbinding along the length of the microtubule as it is transported along the surface.
The ultrawide bandgap (UWBG) (4.8 eV) and melt-grown substrate availability of β-Ga2O3 give promise to the development of next-generation power electronic devices with dramatically improved size, weight, power, and efficiency over current state-of-the-art WBG devices based on 4H-SiC and GaN. Also, with recent advancements made in gigahertz frequency radio frequency (RF) applications, the potential for monolithic or heterogenous integration of RF and power switches has attracted researchers' attention. However, it is expected that Ga2O3 devices will suffer from self-heating due to the poor thermal conductivity of the material. Thermoreflectance thermal imaging and infrared thermography were used to understand the thermal characteristics of a MOSFET fabricated via homoepitaxy. A 3-D coupled electrothermal model was constructed based on the electrical and thermal characterization results. The device model shows that a homoepitaxial device suffers from an unacceptable junction temperature rise of 1500 °C under a targeted power density of 10 W/mm, indicating the importance of employing device-level thermal managements to individual Ga2O3 transistors. The effectiveness of various active and passive cooling solutions was tested to achieve a goal of reducing the device operating temperature below 200 °C at a power density of 10 W/mm. Results show that flip-chip heterointegration is a viable option to enhance both the steady-state and transient thermal characteristics of Ga2O3 devices without sacrificing the intrinsic advantage of high-quality native substrates. Also, it is not an active thermal management solution that entails peripherals requiring additional size and cost implications.
High-fidelity single-shot readout of spin qubits requires distinguishing states much faster than the T1 time of the spin state. One approach to improving readout fidelity and bandwidth (BW) is cryogenic amplification, where the signal from the qubit is amplified before noise sources are introduced and room-temperature amplifiers can operate at lower gain and higher BW. We compare the performance of two cryogenic amplification circuits: a current-biased heterojunction bipolar transistor circuit (CB-HBT), and an AC-coupled HBT circuit (AC-HBT). Both circuits are mounted on the mixing-chamber stage of a dilution refrigerator and are connected to silicon metal oxide semiconductor (Si-MOS) quantum dot devices on a printed circuit board (PCB). The power dissipated by the CB-HBT ranges from 0.1 to 1 μW whereas the power of the AC-HBT ranges from 1 to 20 μW. Referred to the input, the noise spectral density is low for both circuits, in the 15 to 30 fA/Hz range. The charge sensitivity for the CB-HBT and AC-HBT is 330 μe/Hz and 400 μe/Hz, respectively. For the single-shot readout performed, less than 10 μs is required for both circuits to achieve bit error rates below 10−3, which is a putative threshold for quantum error correction.
Proceedings of the IEEE Conference on Decision and Control
Khaledyan, Milad; Vinod, Abraham P.; Oishi, Meeko; Richards, John R.
We address the problem of simultaneous coverage control and stochastic, multi-target tracking with a single pursuer. We presume linear dynamics for the pursuer and linear stochastic dynamics for the targets. The pursuer is equipped with two sensors of varying fidelity: broad-range and narrow-range. We seek the optimal trajectory for the pursuer, as well as optimal sensor selection, over a finite time horizon. We formulate the problem as a mixed-integer program with quadratic constraints, and exploit a convex relaxation method to enable fast solution of local minima. We demonstrate our approach on several simulated scenarios.
A key problem in social network analysis is to identify nonhuman interactions. State-of-the-art bot-detection systems like Botometer train machine-learning models on user-specific data. Unfortunately, these methods do not work on data sets in which only topological information is available. In this paper, we propose a new, purely topological approach. Our method removes edges that connect nodes exhibiting strong evidence of non-human activity from publicly available electronic-social-network datasets, including, for example, those in the Stanford Network Analysis Project repository (SNAP). Our methodology is inspired by classic work in evolutionary psychology by Dunbar that posits upper bounds on the total strength of the set of social connections in which a single human can be engaged. We model edge strength with Easley and Kleinberg's topological estimate; label nodes as “violators” if the sum of these edge strengths exceeds a Dunbar-inspired bound; and then remove the violator-to-violator edges. We run our algorithm on multiple social networks and show that our Dunbar-inspired bound appears to hold for social networks, but not for nonsocial networks. Our cleaning process classifies 0.04% of the nodes of the Twitter-2010 followers graph as violators, and we find that more than 80% of these violator nodes have Botometer scores of 0.5 or greater. Furthermore, after we remove the roughly 15 million violator-violator edges from the 1.2-billion-edge Twitter-2010 follower graph, 34% of the violator nodes experience a factor-of-two decrease in PageRank. PageRank is a key component of many graph algorithms such as node/edge ranking and graph sparsification. Thus, this artificial inflation would bias algorithmic output, and result in some incorrect decisions based on this output.
A persistent challenge present in inverse or parameter estimation problems with interior data is how to deal with uncertainty in the boundary conditions employed in the forward or state model. In this work we focus on a linear plane stress inverse elasticity problem with measured displacement data where one component of the measured displacement field is known with considerably greater precision than the other. This situation is commonly encountered when the displacement field is measured using ultrasound or optical coherence tomography. We present a novel computational formulation in which no displacement or traction boundary conditions are assumed. The formulation results in coupling the state and adjoint equations, that are typically uncoupled when a well-posed state model is available. Two variants of residual-based stabilization are added. Our approach is applied to a simulated data set and experimental data from an ultrasound phantom.
We show seasonal runoff from montane uplands is crucial for plant growth in agricultural communities of northern New Mexico. These communities typically employ traditional irrigation systems, called acequias, which rely mainly upon spring snowmelt runoff for irrigation. The trend of the past few decades is an increase in temperature, reduced snow pack, and earlier runoff from snowmelt across much of the western United States. In order to predict the potential impacts of changes in future climate a system dynamics model was constructed to simulate the surface water supplies in a montane upland watershed of a small irrigated community in northern New Mexico through the rest of the 21st century. End-term simulations of representative concentration pathways (RCP) 4.5 and 8.5 suggest that runoff during the months of April to August could be reduced by 22% and 56%, respectively. End-term simulations also displayed a shift in the beginning and peak of snowmelt runoff by up to one month earlier than current conditions. Results suggest that rising temperatures will drive reduced runoff in irrigation season and earlier snowmelt runoff in the dry season towards the end of the 21st century. Modeled results suggest that climate change leads to runoff scheme shift and increased frequency of drought; due to the uncontemporaneous of irrigation season and runoff scheme, water shortage will increase. Potential impacts of climate change scenarios and mitigation strategies should be further investigated to ensure the resilience of traditional agricultural communities in New Mexico and similar regions.
The predictions of scaling laws for the structure and properties of defect clusters are generally limited to small defect clusters in their ground-state configurations. We investigated the size and geometrical configuration dependence of nano-sized defect clusters in niobium (Nb) using molecular dynamics. We studied the structure and stability of large clusters of size up to fifty defects for vacancies and one hundred defects for interstitials, as well as the role of helium and metastable configurations on the stability of these clusters. We compared three different interatomic potentials in order to determine the relative stability of these clusters as a function of their size and geometrical configurations. Additionally, we conducted a statistical analysis to predict the formation and binding energies of interstitial clusters as a function of both their size and configuration. We find that the size dependence of vacancy and interstitial clusters can be approximated by functional forms that account for bulk and surface effects as well as some considerations of elastic interactions. We also find that helium and metastable configurations can make vacancy and interstitial clusters thermally stable depending on the configuration. Our parameterized functional forms for the formation and binding energies are valid for a very broad range of defect sizes and configurations making it possible to be used directly in a coarse-grained modeling strategy such as Monte Carlo, cluster dynamics or dislocation dynamics which look at defect accumulation and evolution in microstructures.
HfC has shown promise as a material for field emission due to the low work function of the (100) surface and a high melting point. Recently, HfC tips have exhibited unexpected failure after field emission at 2200 K. Characterization of the HfC tips identified faceting of the parabolic tip dominated by coexisting (100) and (111) surfaces. To investigate this phenomenon, we used density functional theory (DFT) simulations to identify the role of defects and impurities (Ta, N, O) on HfC surface properties. Carbon vacancies increased the surface energy of the (100) surface from 2.35 J/m2 to 4.75 J/m2 and decreased the surface energy of the carbon terminated (111) surface from 8.75 J/m2 to 3.48 J/m2. Once 60% of the carbon on the (100) surface have been removed the hafnium terminated (111) surface becomes the lowest energy surface, suggesting that carbon depletion may cause these surfaces to coexist. The addition of Ta and N impurities to the surface are energetically favorable and decrease the work function, making them candidate impurities for improving field emission at high temperatures. Overall, DFT simulations have demonstrated the importance of understanding the role of defects on the surface structure and properties of HfC.
Materials compatibility is a major concern for the design and operation of supercritical carbon dioxide (sCO2) power cycles. Two areas were recently identified for which very little prior knowledge was available. These were the behavior of polymer materials in low-temperature sCO2 environments as well as the high-temperature corrosion behavior for alloys that have been fabricated into compact heat exchangers. A critical need exists to increase understanding in both areas. As such, the Sandia sCO2 Materials Development program initiated a series of experiments for both areas in FY19. The progress that has been made in understanding the behavior of polymers in sCO2 was summarized in the Part I report, while this Part II report describes progress in the area of compact heat exchanger corrosion. For the compact heat exchangers being developed for use in supercritical CO2 power cycles, alloy corrosion is important to understand as it may lead to reduced flow path area, reduced heat transfer, and blocked flow channels. The fabrication of these heat exchangers involve thermal processes such as brazing or diffusion bonding, where the influence of these processes on the corrosion behavior of the alloys is unknown. Candidate alloys for these heat exchangers are typically evaluated for corrosion behavior as witness coupons, without being subjected to these thermal processes. To close this gap in understanding, a series of experiments were completed that utilized small heat exchanger samples subjected to flowing CO2 for 500 hours at 750°C. Small sections of the heat exchanger samples were characterized before and after the 500 hour exposure in order to characterize the oxide growth in the channels as well as the hardness of the alloys. Results are compared to witness coupons of the same alloys.
An investigation is reported of possible kinetic limitations to MgB2 hydrogenation. The role of H–H bond breaking, a necessary first step in the hydrogenation process, is assessed for bulk MgB2, ball-milled MgB2, as well as MgB2 mixed with Pd, Fe and TiF3 additives. The Pd and Fe additives in the MgB2 material exist as dispersed metallic particles in the size range ~5–40 nm diameter. In contrast, TiF3 reacts with MgB2 to form Ti metal, elemental B and MgF2, with the Ti and the MgF2 phases proximate to each other and coating the MgB2 particulates with a film of thickness ~3 nm. Sieverts studies of hydrogenation kinetics are reported and compared to the rate of H–H bond breaking as measured by H-D exchange studies. The results show that H–H bond dissociation does not limit the rate of hydrogenation of MgB2 because H–H bond cleavage occurs rapidly compared to the initial MgB2 hydrogenation. The results also show that surface diffusion of hydrogen atoms cannot be a limiting factor for MgB2 hydrogenation. Instead, it is speculated that it is the intrinsic stability of the B–B extended hexagonal ring structure in MgB2 that hinders the hydrogenation of this material. This supposition is supported by B K-edge x-ray absorption measurements of the materials, which showed spectroscopically that the B–B ring was intact in the material systems studied. The TiF3/MgB2 system was examined further theoretically with reaction thermodynamics and phase nucleation kinetic calculations to better understand the production of Ti metal when TiB2 is thermodynamically favored. The results show that there exist physically reasonable ranges for which nucleation kinetics supersede thermodynamics in determining the reactive pathway for the TiF3/MgB2 system and perhaps for other additive systems as well.
Hansen, Nils H.; Schmitt, Steffen; Wick, Maximilian; Wouters, Christian; Ruwe, Lena; Graf, Isabelle; Andert, Jakob; Pischinger, Stefan
In this work, the effect of H2O injection on the combustion process of iso-octane was investigated with the aim to better understand the suitability of water addition as a potential engine control parameter for homogeneous-charge compression ignition (HCCI) combustion. Several experiments were combined including premixed low-pressure flames, a jet-stirred reactor (JSR) and a plug-flow reactor (PFR), both at atmospheric pressure, and a single-cylinder research engine (SCRE) operated with either iso-octane or RON 98 gasoline. The thermal effect of H2O addition was determined in laminar premixed iso-octane/O2/Ar flames (equivalence ratio $Φ$=1.4, 40 mbar) with H2O mole fractions of 0 to 0.22, where water addition reduced the temperature measured by laser-induced fluorescence (LIF) by up to 110 K. Speciation data were obtained from these flames as well as in the JSR ($Φ$=0.65, 933 mbar) and PFR experiments ($Φ$=0.65, 970 mbar) with and without H2O addition in the low- to intermediate temperature regime from 700–1100 K. The chemical analysis in these flame and reactor experiments was performed using molecular-beam mass spectrometry (MBMS) employing either electron ionization (EI) in the PFR and premixed flame or single-photon ionization (PI) by tunable vacuum-ultraviolet radiation in the JSR. The effects on species mole fractions were small which is supported by predictions from chemical-kinetic simulations. Quantitative speciation data of the exhaust gas of the SCRE were obtained by using Fourier-transform infrared (FTIR) spectroscopy. A very similar species pool was detected in the laboratory-scale experiments and for the engine operation. It is thus assumed that these results could assist in guiding both the improvement of fundamental chemical-kinetic as well as HCCI engine control models.
Ice in the atmosphere affects Earth's radiative properties and initiates most precipitation. Growing ice often requires a solid surface, either to catalyze freezing of supercooled cloud droplets or to serve as a substrate for ice deposited from water vapor. There is evidence that this surface is typically provided by airborne mineral dust; but how chemistry, structure and morphology interrelate to determine the ice-nucleating ability of mineral surfaces remains elusive. Here, we combine optical microscopy with atomic force microscopy to explore the mechanisms of initial ice growth on alkali feldspar, a mineral proposed to dominate ice nucleation in Earth's atmosphere. When cold air becomes supersaturated with respect to water, we discovered that ice rapidly spreads along steps of a feldspar surface. By measuring how ice propagation depends on surface-step height we establish a scenario where supercooled liquid water condenses at steps without having to overcome a nucleation barrier, and subsequently freezes quickly. Our results imply that steps, which are common even on macroscopically flat feldspar surfaces, can accelerate water condensation followed by freezing, thus promoting glaciation and dehydration of mixed-phase clouds.
The floating oscillating surge wave energy converter (FOSWEC) is a wave energy converter that was designed, built, and tested to develop an open-access data set for the purpose of numerical model validation. Here, this paper details the experimental testing of the 1:33-scale FOSWEC in a directional wave basin, and compares experimental data to numerical simulations using the wave energy converter simulator (WEC-Sim) open-source code. The FOSWEC consists of a floating platform moving in heave, pitch, and surge, and two pitching flaps. Power is extracted through relative motion between each of the flaps and the platform. The device was designed to constrain different degrees of freedom so that it could be configured into a variety of operating conditions with varying dynamics. The FOSWEC was tested in a range of different conditions including: static offset, free decay, forced oscillation, wave excitation, and dynamic response to regular waves. In this paper, results from the range of experimental tests are presented and compared to numerical simulations using the WEC-Sim code.
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Xiao, T.P.; Bennett, Christopher H.; Hu, Xuan; Feinberg, Ben; Jacobs-Gedrim, Robin; Agarwal, Sapan; Brunhaver, John S.; Friedman, Joseph S.; Incorvia, Jean A.C.; Marinella, Matthew J.
The domain-wall (DW)-magnetic tunnel junction (MTJ) device implements universal Boolean logic in a manner that is naturally compact and cascadable. However, an evaluation of the energy efficiency of this emerging technology for standard logic applications is still lacking. In this article, we use a previously developed compact model to construct and benchmark a 32-bit adder entirely from DW-MTJ devices that communicates with DW-MTJ registers. The results of this large-scale design and simulation indicate that while the energy cost of systems driven by spin-transfer torque (STT) DW motion is significantly higher than previously predicted, the same concept using spin-orbit torque (SOT) switching benefits from an improvement in the energy per operation by multiple orders of magnitude, attaining competitive energy values relative to a comparable CMOS subprocessor component. Finally, this result clarifies the path toward practical implementations of an all-magnetic processor system.
Knowing when, why, and how materials evolve, degrade, or fail in radiation environments is pivotal to a wide range of fields from semiconductor processing to advanced nuclear reactor design. A variety of methods, including optical and electron microscopy, mechanical testing, and thermal techniques, have been used in the past to successfully monitor the microstructural and property evolution of materials exposed to extreme radiation environments. Acoustic techniques have also been used in the past for this purpose, although most methodologies have not achieved widespread adoption. However, with an increasing desire to understand microstructure and property evolution in situ, acoustic methods provide a promising pathway to uncover information not accessible to more traditional characterization techniques. This work highlights how two different classes of acoustic techniques may be used to monitor material evolution during in situ ion beam irradiation. The passive listening technique of acoustic emission is demonstrated on two model systems, quartz and palladium, and shown to be a useful tool in identifying the onset of damage events such as microcracking. An active acoustic technique in the form of transient grating spectroscopy is used to indirectly monitor the formation of small defect clusters in copper irradiated with self-ions at high temperature through the evolution of surface acoustic wave speeds. Here, these studies together demonstrate the large potential for using acoustic techniques as in situ diagnostics. Such tools could be used to optimize ion beam processing techniques or identify modes and kinetics of materials degradation in extreme radiation environments.
D'Elia, Marta D.; Suzuki, Jorge L.; Zhou, Yongtao; Zayernouri, Mohsen
We develop a thermodynamically consistent, fractional visco-elastoplastic model coupled with damage for anomalous materials. The model utilizes Scott-Blair rheological elements for both visco- elastic/plastic parts. The constitutive equations are obtained through Helmholtz free-energy potentials for Scott-Blair elements, together with a memory-dependent fractional yield function and dissipation inequalities. A memory-dependent Lemaitre-type damage is introduced through fractional damage energy release rates. For time-fractional integration of the resulting nonlinear system of equations, we develop a first-order semi-implicit fractional return-mapping algorithm. We also develop a finite-difference discretization for the fractional damage energy release rate, which results into Hankel-type matrix-vector operations for each time-step, allowing us to reduce the computational complexity from O(N3) to O(N2) through the use of Fast Fourier Transforms. Our numerical results demonstrate that the fractional orders for visco-elasto-plasticity play a crucial role in damage evolution, due to the competition between the anomalous plastic slip and bulk damage energy release rates.
Zubyuk, Varvara V.; Vabishchevich, Polina V.; Shcherbakov, Maxim R.; Shorokhov, Alexander S.; Fedotova, Anna N.; Liu, Sheng; Keeler, Gordon; Dolgova, Tatyana V.; Staude, Isabelle; Brener, Igal B.; Fedyanin, Andrey A.
Saturable optical elements lie at the cornerstone of many modern optical systems. Regularly patterned quasi-planar nanostructures - metasurfaces - are known to facilitate nonlinear optical processes. Such subwavelength semiconductor nanostructures can potentially serve as saturable components. Here we report on the intensity-dependent reflectance of femtosecond laser pulses from semiconductor metasurfaces with Mie-type modes, caused by the absorption saturation. Arrays of GaAs nanocylinders with magnetic dipole resonances in the spectral vicinity of the GaAs bandgap demonstrate a reduced saturation intensity and increased self-modulation efficiency, an order of magnitude higher than bulk GaAs or unstructured GaAs films. By contrast, the reflection modulation is shown to be negligible in the CW regime for the same average intensities, indicating that the process is not the result of temperature effects. Our work provides a novel idea for low-power saturable elements based on nonthermal nature of saturation. We conclude by devising a high-quality metasurface that can be used, in theory, to further reduce the saturation fluence below 50 nJ/cm2.
Laros, James H.; Saltonstall, Christopher B.; Gilbert, Tristan; Matson, Joseph; Ugwu, Fabian; Kasica, Richard; Bezares, Francisco J.; Valentine, Jason; Caldwell, Joshua D.
The field of nanophotonics has long sought to identify mechanisms to realize dynamical control of optical modes. In most approaches, the magnitude of tuning is dependent upon the degree to which the optical permittivity is malleable upon some material change, such as carrier concentration. Here, through a multiwavelength Raman spectroscopic examination of 4H-SiC nanopillars, momentum is identified as an alternative means to enhance spectral tunability of nanophotonic modes, owing to the spatial dispersion implicit in the infrared (IR) optical permittivity of polar semiconductors. Experimentally, this is deduced through the observation of a "forbidden" Raman mode at ≈780cm-1 and the emergence of the surface-optical phonon polariton at ≈950 cm-1, which evolved with intensities dependent upon the nanopillar diameter and the wavelength of the incident light. The evolution of these modes is accompanied by a redshift and spectral narrowing of the longitudinal-optical plasmon coupled (LOPC) mode exhibiting a similar wavelength and diameter dependence. Mie resonances, identified using ultraviolet-visible spectroscopy and excited by the visible laser excitation of the Raman experiment, acted to vary the momentum sampled during the Raman experiment leading to these spectral dependencies. This was deduced by fitting the Raman response accounting for both the presence of the surface phonon and the overdamped LOPC mode under the Lindhard-Mermin approximation. This fitting not only explains the Raman response, but also clearly exhibits the spatially disperse permittivity of the SiC, which is shown to have a momentum-dependent sensitivity to carrier concentration. Such sensitivity, in turn, highlights the potential of spatial dispersion as a means to accentuate the performance of active IR nanophotonic approaches employing phonon polaritons.
Sandia National Laboratories/New Mexico (SNL/NM Atmospheric Sciences Department 8863 operates the ARM site at Utqiagvik, Alaska as part of the DOE Office of Science Atmospheric Radiation Measurement (ARM) research program. This TWD identifies the hazards, control measures, required training, and procedure for Hydrogen Generation at the Utqiagvik site.
Easterling, Charles P.; Xia, Yening; Zhao, Junpeng; Fanucci, Gail E.; Sumerlin, Brent S.
Block copolymers prepared by reversible addition-fragmentation chain transfer (RAFT) polymerization are often restricted to a specific comonomer blocking sequence that is dictated by intermediate radical stability and relative radical leaving group abilities. Techniques that provide alternative pathways for reinitiation of thiocarbonylthio-terminated polymers could allow access to block copolymer sequences currently unobtainable through the RAFT process. We report a method for preparing "inverted" block copolymers, whereby the traditional order of monomer addition has been reversed through the use of photoiniferter-mediated radical polymerization. Specifically, thiocarbonylthio photolysis of xanthate- A nd dithiocarbamate-functional macromolecular chain transfer agents (macro-CTAs) led to the direct formation of leaving group macroradicals otherwise unaffordable by an addition-fragmentation mechanism. We believe this method could provide a route to synthesize multiblock copolymers of synthetically challenging comonomer sequences.
Intense electron beams striking a high-atomic number target produce high-output pulsed photon fluxes for flash x-ray experiments. Without an external guide field, such beams are subject to the dynamics of high-current electron beam propagation, including changes to electron trajectories either from self-fields or from development of beam instabilities. The bremsstrahlung output (dose-rate) scales approximately as IVx, where I is the beam current, V the electron energy, and x is in the range 2.0–2.65 and depends upon the electron angle on the converter. Using experimental beam data (dose-rate, I and V), this equation can be solved for x, a process known as “inverting the radiographer’s equation.” Inversion methods that rely on thermoluminescent dosimeters, which are time-integrated, yield no information about evolution of the electron beam angle in time. We propose here an inversion method that uses several dose-rate monitors at different angles with respect to the beam axis. By measuring dose-rates at different angles, one can infer the time-dependent beam voltage and angle. Furthermore, this method compares well with estimates of corrected voltage and results in a self-consistent picture of beam dynamics. Techniques are demonstrated using data from self-magnetic pinch experiments at the RITS-6 facility at Sandia National Laboratories.
Mayes, R.L.; Ankers, Luke; Daborn, Phil; Moulder, Tony; Ind, Philip
For flight payloads or systems in free flight, Impedance Matched Multi-Axis Testing (IMMAT) can provide an accurate laboratory reproduction of the flight vibration environment at multiple response locations. IMMAT is performed by controlling multiple shakers attached to the system of interest, usually through slender rods so that the shakers impart negligible moments or shear forces at the attachment.
The Sandia National Laboratories (SNL) Large-Scale Computing Initiative (LSCI) milestone required running two parallel simulation codes at scale on the Trinity supercomputer at Los Alamos National Laboratory (LANL) to obtain presentation quality visualization results via in-situ methods. The two simulation codes used were Sandia Parallel Aerosciences Research Code (SPARC) and Nalu, both fluid dynamics codes developed at SNL. The codes were integrated with the ParaView Catalyst in-situ visualization library via the SNL developed Input Output SubSystem (IOSS). The LSCI milestone had a relatively short time-scale for completion of two months. During setup and execution of in-situ visualization for the milestone, there were several challenging issues in the areas of software builds, parallel startup-times, and in the a priori specification of visualizations. This paper will discuss the milestone activities and technical challenges encountered in its completion.
Community detection in graphs is a canonical social network analysis method. We consider the problem of generating suites of teras-cale synthetic social networks to compare the solution quality of parallel community-detection methods. The standard method, based on the graph generator of Lancichinetti, Fortunato, and Radicchi (LFR), has been used extensively for modest-scale graphs, but has inherent scalability limitations. We provide an alternative, based on the scalable Block Two-Level Erdos-Renyi (BTER) graph generator, that enables HPC-scale evaluation of solution quality in the style of LFR. Our approach varies community coherence, and retains other important properties. Our methods can scale real-world networks, e.g., to create a version of the Friendster network that is 512 times larger. With BTER's inherent scalability, we can generate a 15-terabyte graph (4.6B vertices, 925B edges) in just over one minute. We demonstrate our capability by showing that label-propagation community-detection algorithm can be strong-scaled with negligible solution-quality loss.
In memorium: This special issue is dedicated to Steve Attaway, who passed away on February 28, 2019. Steve Attaway worked at Sandia National Laboratories in Albuquerque, NM, for over 30 years making significant contributions in highperformance computing, shock physics, meshfree methods, the geosciences, concrete mechanics, and blast effects on structures.
Hypersonic vehicles hold great promise for a range of applications. However, they are subject to complex dynamics including high temperatures, thick boundary layers, and gas reaction effects. These coupled nonlinear dynamics make vehicle control and planning especially challenging. Specifically, it is very difficult to rapidly predict the vehicle response to control inputs and time-varying conditions. While reduced order models have shown great promise for predicting behavior in a more rapid manner, these techniques still require powerful computers and several simplifying assumptions. As a result, we currently lack the ability to rapidly plan (or re-plan) the trajectories of hypersonic vehicles.
A growing body of applied mathematics literature in recent years has focused on the application of fractional calculus to problems of anomalous transport. In these analyses, the anomalous transport (of charge, tracers, fluid, etc.) is presumed attributable to long–range correlations of material properties within an inherently complex, and in some cases self-similar, conducting medium. Rather than considering an exquisitely discretized (and computationally intractable) representation of the medium, the complex and spatially correlated heterogeneity is represented through reformulation of the governing equation for the relevant transport physics such that its coefficients are, instead, smooth but paired with fractional–order space derivatives. Here we apply these concepts to the scalar Helmholtz equation and its use in electromagnetic interrogation of Earth’s interior through the magnetotelluric method. We outline a practical algorithm for solving the Helmholtz equation using spectral methods coupled with finite element discretizations. Execution of this algorithm for the magnetotelluric problem reveals several interesting features observable in field data: long–range correlation of the predicted electromagnetic fields; a power–law relationship between the squared impedance amplitude and squared wavenumber whose slope is a function of the fractional exponent within the governing Helmholtz equation; and, a non–constant apparent resistivity spectrum whose variability arises solely from the fractional exponent. In geologic settings characterized by self–similarity (e.g. fracture systems; thick and richly–textured sedimentary sequences, etc.) we posit that these diagnostics are useful for geologic characterization of features far below the typical resolution limit of electromagnetic methods in geophysics.
The purpose of a Conceptual Location Analysis is to identify potential project/building sites in the planning phase of a project. The analysis includes review and comment on the potential sites by relevant disciplines. Site criteria encompasses DOE and NNSA requirements pertaining to real property and environmental stewardship and additionally addresses SNL site planning objectives such as sustainability and efficiency. This analysis is intended to be used as a tool to provide a comprehensive perspective on siting decisions, and is not intended to supersede previous siting decisions or agreements. This conceptual location analysis is for the siting of PV for power production. The goal of this Conceptual Location Analysis is to weigh different sites, and come to a consensus on preferred sites for potential solar arrays through an Energy Savings Performance Contract (ESPC) or a Utility Energy Service Contract (UESC).
Residual stress is a common result of manufacturing processes, but it is one that is often overlooked in design and qualification activities. There are many reasons for this oversight, such as lack of observable indicators and difficulty in measurement. Traditional relaxation-based measurement methods use some type of material removal to cause surface displacements, which can then be used to solve for the residual stresses relieved by the removal. While widely used, these methods may offer only individual stress components or may be limited by part or cut geometry requirements. Diffraction-based methods, such as X-ray or neutron, offer non-destructive results but require access to a radiation source. With the goal of producing a more flexible solution, this LDRD developed a generalized residual stress inversion technique that can recover residual stresses released by all traction components on a cut surface, with much greater freedom in part geometry and cut location. The developed method has been successfully demonstrated on both synthetic and experimental data. The project also investigated dislocation density quantification using nonlinear ultrasound, residual stress measurement using Electronic Speckle Pattern Interferometry Hole Drilling, and validation of residual stress predictions in Additive Manufacturing process models.
A series of tests were executed to ensure complete UCV high explosive material consumption in the case of a system anomaly occurring — specifically a firing event where one or more RP-87 detonators do not function as a result of an arming and firing system problem or some other circumstance where a detonator does not function even though a firing signal is received at the bridgewire. A simplified linear array was utilized with 5 detonators per test firing only one detonator and maintaining the critical as-designed UCV dimensions and HE mass-to-volume ratios which can affect sympathetic initiation behavior. Tests were performed using both KTech Corporation's stated detonator gap of 0.060" as well as larger gaps to determine safety margin. The detonator's explosive contents were completely consumed in all cases where the gap was maintained within stated specifications. Only extreme gap conditions (0.30") indicated remaining explosive material. The mechanism by which the material is reacted does change with increasing gap however, transferring to a deflagration at larger gaps. All tests were performed at SNL/NM site 9930 in April 2013.
Large-eddy simulation (LES) of turbulence in complex geometries and domains is often conducted with high-aspect-ratio resolution cells of varying shapes and orientations. The effects of such anisotropic resolution are often simplified or neglected in subgrid model formulations. In this study, we examine resolution-induced anisotropy and demonstrate that even for isotropic turbulence, anisotropic resolution induces mild resolved Reynolds stress anisotropy and significant anisotropy in second-order resolved velocity gradient statistics. In large-eddy simulations of homogeneous isotropic turbulence with anisotropic resolution, it is shown that commonly used subgrid models, including those that consider resolution anisotropy in their formulation, perform poorly. The one exception is the anisotropic minimum dissipation model proposed by Rozema et al. [Phys. Fluids 27, 085107 (2015)]. A simple model is presented here that is an anisotropic eddy diffusivity extension of the “Kolmogorov expression” eddy viscosity of Carati et al. [A family of dynamic models for large-eddy simulation, in Annual Research Briefs, Center for Turbulence Research (Stanford University and NASA AMES, 1995), pp. 35–40] that depends explicitly on the anisotropy of the resolution. It also performs well and is remarkable because, unlike other LES subgrid models, the eddy diffusivity only depends on statistical characteristics of the turbulence (in this case, the dissipation rate), not on fluctuating quantities. In other subgrid modeling formulations, such as the dynamic procedure, limiting flow dependence to statistical quantities in this way could have advantages.
Holland, Austin A.; Walter, Jacob I.; Ogwari, Paul; Thiel, Andrew; Ferrer, Fernando; Woelfel, Isaac; Chang, Jefferson C.; Darold, Amberlee P.
The Oklahoma Geological Survey (OGS) monitors seismicity throughout the state of Oklahoma utilizing permanent and temporary seismometers installed by OGS and other agencies, while producing a real–time earthquake catalog. The OGS seismic network was recently added to the Advanced National Seismic System (ANSS) as a self–supporting regional seismic network, and earthquake locations and magnitudes are automatically reported through U.S. Geological Survey and are part of the ANSS Comprehensive Earthquake Catalog. In Oklahoma, before 2009, background seismicity rates were about 2 M 3.0+ earthquakes per year, which increased to 579 and 903 M 3.0+ earthquakes in 2014 and 2015, respectively. After seismicity peaked, the rate fell to 624, 304, and 194 M 3.0+ earthquakes in 2016, 2017, and 2018, respectively. The catalog is complete down to M 2.2 from mid–2014 to present, despite the significant workload for a primarily state–funded regional network. That astonishing uptick in seismicity has been largely attributed to wastewater injection practices. The OGS provides the Oklahoma Corporation Commission, the agency responsible for regulating oil and gas activities within the state, with technical guidance and earthquake products that inform their “traffic–light” mitigation protocol and other mitigating actions. We have initiated a citizen–scientist–driven, educational seismometer program by installing Raspberry Shake geophones throughout the state at local schools, museums, libraries, and state parks. The seismic hazard of the state portends a continued need for expansion and densification of seismic monitoring throughout Oklahoma.
Plasmonic antennas and metasurfaces can effectively control light-matter interactions, and this facilitates a deterministic design of optical materials properties, including structural color. However, these optical properties are generally fixed after synthesis and fabrication, while many modern-day optics applications require active, low-power, and nonvolatile tuning. These needs have spurred broad research activities aimed at identifying materials and resonant structures capable of achieving large, dynamic changes in optical properties, especially in the challenging visible spectral range. In this work, we demonstrate dynamic tuning of polarization-dependent gap plasmon resonators that contain the electrochromic oxide WO3. Its refractive index in the visible changes continuously from n = 2.1 to 1.9 upon electrochemical lithium insertion and removal in a solid-state device. By incorporating WO3 into a gap plasmon resonator, the resonant wavelength can be shifted continuously and reversibly by up to 58 nm with less than 2 V electrochemical bias voltage. The resonator can remain in a tuned state for tens of minutes under open circuit conditions.
Radio frequency (RF) devices are becoming more multi-band, increasing the number of filters and other front-end components while simultaneously pushing towards reduced cost, size, weight, and power (CSWaP). One approach to reducing CSWaP is to augment the achievable functionalities of electromechanical/acoustic filtering chips to include "active" and nonlinear functionalities, such as gain and mixing. The acoustoelectric (AE) effect could enable such active acoustic wave devices. We have examined the AE effect with a leaky surface acoustic wave (LSAW) in a monolithic structure of epitaxial indium gallium arsenide (In GaAs) on lithium niobate (LiNb0 3 ). This lead to experimentally demonstrated state-of-the-art SAW amplifier performance in terms of gain per acoustic wavelength, reduced power consumption, and increased power efficiency. We quantitatively compare the amplifier performance to previous notable works and discuss the outlook of active acoustic wave components using this material platform. Ultimately, this could lead to smaller, higher-performance RF signal processors for communications applications.
Supporting the latest hardware and compiler versions is important to leverage improvements in the software environment and new HPC platforms. We will provide certified support for the latest releases of vendor compilers from Intel, AMD, IBM, NVIDIA, ARM and Cray as well as of open source compilers GCC and Clang.
Engage the C++ standards committee to further the adoption of successful Kokkos concepts into the C++ standard, and provide feedback on proposed concurrency mechanisms such as the executors proposal.
The goal of this project was to develop compounds that kill biothreat bacteria by inhibiting the activity of bacterial acetyl CoA carboxylase (ACC) by blocking dimerization of one component of that enzyme complex, biotin carboxylase (BC). The ultimate goal is to combine a BC dimerization inhibitor with an existing active site inhibitor for carboxytransferase, another component of ACC, to form a new dual inhibitor therapy for this essential enzyme to avoid onset of resistance. Developing medical countermeasures to defeat antibiotic resistance in biothreat agents is of interest for national security for protecting both warfighters and the public.
There are multiple factors involved in successfully manufacturing ASICIVLSI chips, and ensuring operational specifications are maintained throughout the design and manufacturing process is often challenging. Dynamic timing analysis (DTA) is the principal method used to validate that a manufactured chip complies to its design specifications. In DTA functionality of both synchronous and asynchronous designs are verified by applying input signals and checking for correct output signals. In complex designs where the number of input signal permutations is extremely large, the computing resources required to properly verify the functionality of a chip is prohibitive. In this paper, a strategy using reinforcement learning (RL) for reducing DTA time and resources in such cases is discussed. RL assisted DTA holds much promise in ensuring that VLSI chip design and functionality are fully and optimally verified.
The corrosion of steel, when exposed to various compositions of brines is a complex, heterogeneous process involving dissolution and precipitation of multiple solids. The rate at which elements will be released from the corrosion process under these conditions will depend, in part, on effects associated with secondary alteration phases (passivating film) that may potentially form under these conditions. Understanding these processes has required the development of sophisticated methods to sample and quantitatively characterize the composition of the steel as it corrodes and releases elements. The determination of the concentrations of both brine and steel corrosion components in solutions sampled from these tests is required to fully understand the process that may eventually lead to dissolution of corrosion products.
The strain-rate sensitivity exponent m and activation volume υa - are often used to characterize the strain-rate sensitivity of strength behavior in metals and alloys. Complications can arise when the m and υa - values become indeterminate, due to factors such as an inherent scatter in the mechanical property data. The study of commercial Ti-alloy wires is considered wherein to overcome this limitation, the formulation of the Kocks-Mecking (K-M) model is modified to provide a parameter cb that characterizes the microstructural scale responsible for the observed plasticity and work hardening behavior. The softening factor cb is found to be independent of strain-rate for the Ti-alloy wires of this study. It is proposed that cb !can offer a versatile and complementary computation to the activation volume υa - since its formulation includes the yield and ultimate strength values along with the plastic strain. For the tensile testing of Ti-alloy wires, a low cb-value of 14 is calculated for Ti-6Al-4V that is consistent with >10as % plasticity during work hardening whereas a high cb-value of 135 for Ti-6Al-7Nb corresponds with <4as % plasticity.
Here, we report the construction of a new experimental apparatus for direct time-resolved probing of high-pressure gas-phase chemical reactions by photoionization mass spectrometry. The apparatus uses a laser photolysis slow-flow reactor, capable of operating at P = 0.3 — 100 bar and T = 300 — 1000 K. In this report, we initiate reactions in homogeneous gas mixtures by the photolysis of appropriate radical precursor using laser pulses at repetition rates of 1 — 10 Hz. The reacting mixture is continuously sampled into a vacuum chamber, ionized by VUV photons from laboratory-based discharge lamps or from a synchrotron beamline, and analyzed by a custom-designed mass spectrometer. Soft near-threshold ionization by tunable synchrotron radiation enables spectroscopic quantification of many key intermediates and products of chemical reactions. A novel ionization scheme in the high-density region of the sample gas jet increases the experimental sensitivity 100-fold, compared with existing instruments, without compromising mass resolution. A 40-kHz pulsed reflectron time-of-flight mass spectrometer in the orthogonal acceleration geometry achieves simultaneous detection of all ionized species with 25-μs time resolution. We show the power of this apparatus by investigating the ethyl radical oxidation reaction using very dilute (<1012 molecules • cm-3) ethyl concentrations at pressures up to 25 bar.
Kehayias, Pauli M.; Turner, M.J.; Trubko, R.; Schloss, J.M.; Hart, C.A.; Wesson, M.; Glenn, D.R.; Walsworth, R.L.
We present a micrometer-resolution and millimeter-field-of-view stress imaging method for diamonds containing a thin surface layer of nitrogen vacancy (NV) color centers. In this method, we reconstruct stress tensor elements over a two-dimensional field of view from NV optically-detected magnetic resonance (ODMR) spectra. We use this technique to study how stress inhomogeneity affects NV magnetometry performance, and show how NV stress imaging is a useful and direct way to assess these effects. This new tool for mapping stress in diamond will aid optimization of NV-diamond sensing, with wide-ranging applications in the physical and life sciences.
The growth of applications at the intersection between electromagnetic and quantum physics is necessitating the creation of novel computational electromagnetic solvers. Work in this paper presents a new set of time domain integral equations (TDIEs) formulated directly in terms of the magnetic vector and electric scalar potentials that can be used to meet many of the requirements of this emerging area. Stability for this new set of TDIEs is achieved by leveraging an existing rigorous functional framework that can be used to determine suitable discretization approaches to yield stable results in practice. The basics of this functional framework are reviewed before it is shown in detail how it may be applied in developing the TDIEs of this work. Numerical results are presented which validate the claims of stability and accuracy of this method over a wide range of frequencies where traditional methods would fail.
The purpose of this paper is to characterize the need for improved predictive capabilities in low-temperature plasma (LTP) science, and to identify possible means of accomplishing this. While these means may constitute an initiative of their own, we consider these ideas to have widespread importance to discovery plasma science. Therefore, it is our hope that these ideas are more generally incorporated in future work.
The ECP/VTK-m project is providing the core capabilities to perform scientific visualization on Exascale architectures. The ECP/VTK-m project fills the critical feature gap of performing visualization and analysis on processors like graphics-based processors. The results of this project will be delivered in tools like ParaView, Vislt, and Ascent as well as in stand-alone form. Moreover, these projects are depending on this ECP effort to be able to make effective use of ECP architectures.
The purpose of this document is to discuss the construction of two MELCOR Accident Consequence Code System (MACCS) dose conversion factor (DCF) files in some detail, an older file created in 2007 named FGR13DCF.inp and a newer file created in 2018 called FGR13GyEquiv_RevAinp. Very briefly, the difference between the two files is that the older file follows the standard conventions of assigning a radiation weighting factor of 20 for alpha radiation for all tissues and organs; whereas, the newer file complies with the Federal Guidance Report (FGR) 13 health effects modeling and uses modified radiation weighting factors (referred to as relative biological effectiveness (RBE) factors) for alpha radiation of 10 for breast and of 1 for red bone marrow. During an intermediate period, a file called FGR13GyEquiv.inp was created and used for the State-of-the-Art Reactor Consequence Analysis (SOARCA) calculations. This file was not released to the MACCS user community, but it is also discussed briefly in this document.
Remote Direct Memory Access (RDMA) over Converged Ethernet (RoCE) has the potential to provide performance that rivals traditional high performance fabrics. If this potential proves out, significant impacts on system procurement decisions could follow. This work provides a series of small scale performance results which are used to compare and contrast the performance of RoCE-enabled Ethernet with TCP-based Ethernet and an HPC network. Additionally, a discussion of the maturity of RoCE firmware/software stacks and documentation is provided along with useful approaches for probing performance. A detailed description of two experimental setups known to have good RoCE performance is given, including step-by-step configuration and the exact hardware and software revisions employed. At small scales, RoCE is found to have significant performance advantages over "out-of-the-box" TCP protocols and is competitive with state-of-the-art high performance networks. Further examination of RoCE using a wider array of benchmarks and at greater scale is warranted.
Prime, Michael B.; Buttler, William T.; Fensin, Saryu J.; Jones, David R.; King, Robert S.; Manzanares, Ruben; Martinez, Daniel T.; Martinez, John I.; Payton, Jeremy R.; Schmidt, Derek W.; Brown, Justin L.
Recently, Richtmyer-Meshkov instability (RMI) experiments driven by high explosives and fielded with perturbations on a free surface have been used to study strength at extreme strain rates and near zero pressure. The RMI experiments reported here used impact loading, which is experimentally simpler, more accurate to analyze, and which also allows the exploration of a wider range of conditions. Three experiments were performed on tantalum at shock stresses from 20 to 34 GPa, with six different perturbation sizes at each shock level, making this the most comprehensive set of strength-focused RMI experiments reported to date on any material. The resulting estimated average strengths of 1200-1400 MPa at strain rates of 107/s exceeded, by 40% or more, a common power law extrapolation from data at strain rates below 104/s. Taken together with other data in the literature that show much higher strength at simultaneous high rates and high pressure, these RMI data isolated effects and indicated that, in the range of conditions examined, the pressure effects are more significant than rate effects.
In this project, resonance enhanced multi-photon ionization followed by spatial mode ion imaging (REMPI-SMII) has been developed as a new tool for in-situ monitoring of local catalytic activity near a chemically active surface. A prototype experimental setup was developed for the demonstration, and initial results indicate this approach is feasible as a new diagnostic for online monitoring of catalytic reactions. The catalytic conversion of H2 and D2 to form HD over a Pt surface was carried out using a dual-molecular beam arrangement with reactant beams impinging on a structured Pt surface. The catalytic production of HD was successfully detected through the REMPI-SMII approach, and next steps were identified to improve the experimental design for better spatial resolution and mapping of catalytic surface activity.
Rosenberg, Samantha G.; Tomko, John A.; Boris, David R.; Walton, Scott G.; Hopkins, Patrick E.
Here, the thermal properties of plasma-generated aluminum oxyfluoride passivation layers at the surface of aluminum thin films are measured. The oxyfluoride layers are generated using plasmas produced in mixtures of NH3 and SF6 to simultaneously remove oxygen and add fluorine to the aluminum surface, an alternative approach to the more conventional two-step methods that utilize HF treatments to remove the native oxide followed by metal-fluoride (e.g., MgF2, LiF, and AlF3) thin film deposition that serves to protect the aluminum surface from further oxidation. Here, the change in thermal properties of the layers as a function of plasma processing time is determined. A significant reduction in thermal boundary conductance is measured with the increasing treatment time, which can be related to the increasing fluorine content in the layers. Acoustic reflection measurements suggest this reduced thermal boundary conductance is related to lower bonding strength to aluminum with increasing fluorine.
In this paper we report preliminary results from the novel coupling of cyber-physical emulation and interdiction optimization to better understand the impact of a CrashOverride malware attack on a notional electric system. We conduct cyber experiments where CrashOverride issues commands to remote terminal units (RTUs) that are controlling substations within a power control area. We identify worst-case loss of load outcomes with cyber interdiction optimization; the proposed approach is a bilevel formulation that incorporates RTU mappings to controllable loads, transmission lines, and generators in the upper-level (attacker model), and a DC optimal power flow (DCOPF) in the lower-level (defender model). Overall, our preliminary results indicate that the interdiction optimization can guide the design of experiments instead of performing a 'full factorial' approach. Likewise, for systems where there are important dependencies between SCADA/ICS controls and power grid operations, the cyber-physical emulations should drive improved parameterization and surrogate models that are applied in scalable optimization techniques.
Celina, Mathias C.; Park, Jong R.; Van Guyse, Joachim F.R.; Podevyn, Annelore; Bolle, Eleonore C.L.; Bock, Nathalie; Linde, Carl E.; Hoogenboom, Richard; Dargaville, Tim R.
Four drug-conjugated poly(2-alkyl-2-oxazoline) (PAOx) networks with different hydrophobicity were synthesized via copolymerization of either 2-methyl-, 2-ethyl-, 2-propyl- or 2-butyl-2-oxazoline with the functional monomer, 2-dec-9-enyl-2-oxazoline. The incorporation of a labile ester linkage between the polymer and the drug benazepril allowed for sustained drug release over periods of months with the release rates strongly depending on the hydrophobicity of the polymer pendant groups. Drug loading of 13 ± 2 wt% was used with 10 mol% crosslinking sites simply by tuning the thiol-ene stoichiometry. The networks exhibited negligible cell toxicity but cell repulsion was observed for hydrogels based on poly(2-methyl-2-oxazoline) and poly(2-ethyl-2-oxazoline) while those based on poly(2-n-propyl-2-oxazoline) and poly(2-n-butyl-2-oxaoline) showed cell adhesion. These results suggest that PAOx networks have great potential as drug delivery devices for long-lasting drug release applications.
Proceedings of CANOPIE-HPC 2019: 1st International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis
Containerized computing is quickly changing the landscape for the development and deployment of many HPC applications. Containers are able to lower the barrier of entry for emerging workloads to leverage supercomputing resources. However, containers are no silver bullet for deploying HPC software and there are several challenges ahead in which the community must address to ensure container workloads can be reproducible and inter-operable. In this paper, we discuss several challenges in utilizing containers for HPC applications and the current approaches used in many HPC container runtimes. These approaches have been proven to enable high-performance execution of containers at scale with the appropriate runtimes. However, the use of these techniques are still ad hoc, test the limits of container workload portability, and several gaps likely remain. We discuss those remaining gaps and propose several potential solutions, including custom container label tagging and runtime hooks as a first step in managing HPC system library complexity.
Proceedings of CANOPIE-HPC 2019: 1st International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis
Containers offer a broad array of benefits, including a consistent lightweight runtime environment through OS-level virtualization, as well as low overhead to maintain and scale applications with high efficiency. Moreover, containers are known to package and deploy applications consistently across varying infrastructures. Container orchestrators manage a large number of containers for microservices based cloud applications. However, the use of such service orchestration frameworks towards HPC workloads remains relatively unexplored. In this paper we study the potential use of Kubernetes on HPC infrastructure for use by the scientific community. We directly compare both its features and performance against Docker Swarm and bare metal execution of HPC applications. Herein, we detail the configurations required for Kubernetes to operate with containerized MPI applications, specifically accounting for operations such as (1) underlying device access, (2) inter-container communication across different hosts, and (3) configuration limitations. This evaluation quantifies the performance difference between representative MPI workloads running both on bare metal and containerized orchestration frameworks with Kubernetes, operating over both Ethernet and InfiniBand interconnects. Our results show that Kubernetes and Docker Swarm can achieve near bare metal performance over RDMA communication when high performance transports are enabled. Our results also show that Kubernetes presents overheads for several HPC applications over TCP/IP protocol. However, Docker Swarm's throughput is near bare metal performance for the same applications.
Securing cyber systems is of paramount importance, but rigorous, evidence-based techniques to support decision makers for high-consequence decisions have been missing. The need for bringing rigor into cybersecurity is well-recognized, but little progress has been made over the last decades. We introduce a new project, SECURE, that aims to bring more rigor into cyber experimentation. The core idea is to follow the footsteps of computational science and engineering and expand similar capabilities to support rigorous cyber experimentation. In this paper, we review the cyber experimentation process, present the research areas that underlie our effort, discuss the underlying research challenges, and report on our progress to date. This paper is based on work in progress, and we expect to have more complete results for the conference.
Images are often not the optimal data form to perform machine learning tasks such as scene classification. Compressive classification can reduce the size, weight, and power of a system by selecting the minimum information while maximizing classification accuracy.In this work we present designs and simulations of prism arrays which realize sensing matrices using a monolithic element. The sensing matrix is optimized using a neural network architecture to maximize classification accuracy of the MNIST dataset while considering the blurring caused by the size of each prism. Simulated optical hardware performance for a range of prism sizes are reported.
Krishnamoorthy, Siddharth; Komjathy, Attila; Pauken, Michael T.; Bowman, Daniel B.; Cutts, James A.; Izraelevitz, Jacob; Jackson, Jennifer M.; Martire, Leo; Garcia, Raphael F.; Mimoun, David
We present a 30 GHz heterogeneously integrated silicon photonic/lithium niobate Mach-Zehnder modulator simultaneously utilizing the strong Pockels effect in LiNbO3 while also taking advantage of the ability for photonic/electronic integration and mass production associated with silicon photonics. Aside from the final step of bonding the LiNbO3, this modulator can be entirely fabricated using CMOS facilities.
AVFOP 2019 - Avionics and Vehicle Fiber-Optics and Photonics Conference
Yang, Benjamin B.; Lovelace, Brandon; Wier, Brian R.; Campbell, Jacob; Bolding, Mark; Chan, Cheong W.; Vinson, J.G.; Muthuchamy, Tarun; Bhattacharjea, Rajib; Harris, T.R.; Davis, Kyle; Stark, Andrew; Ward, Christopher; Bottenfield, Christian; Ralph, Stephen E.; Gehl, M.; Kodigala, Ashok; Lentine, Anthony L.
A compact radio frequency (RF) photonic receiver consisting of several photonic integrated circuits (PIC) that performs channelization and simultaneously downconverts the signal is described. A technique is also presented to adjust the phase shifters of the arrayed waveguide grating channelizer without direct phase measurements.
In FY 19, the Sandia National Laboratories' "Laboratory Resilience and Continuity Management" Organization established the groundwork to create a business continuity program. The organization is leveraging best practices from established industry and ISO standards and Federal Emergency Management Agency (FEMA) continuity guidance.
Today’s networked systems utilize advanced security components such as Next Generation Firewall (NGFW), Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS), and methods for network traffic classification. A fundamental aspect of these security components and methods is network packet visibility and packet inspection. To achieve packet visibility, a compute mechanism used by these security components and methods is Deep Packet Inspection (DPI). DPI is used to obtain visibility into packet fields by looking deeper inside packets, beyond just IP address, port, and protocol. However, DPI is considered extremely expensive in terms of compute processing costs and very challenging to implement on high speed network systems. The fundamental scientific paradigm addressed in this research project is the application of greater network packet visibility and packet inspection at data rates greater than 40Gbps to secure computer network systems. The greater visibility and inspection will enable detection of advanced content-based threats that exploit application vulnerabilities and are designed to bypass traditional security approaches such as firewalls and antivirus scanners. Greater visibility and inspection are achieved through identification of the application protocol (e.g., HTTP, SMTP, Skype) and, in some cases, extraction and processing of the information contained in the packet payload. Analysis is then performed on the resulting DPI data to identify potentially malicious behavior. In order to obtain visibility and inspect the application protocol and contents at high speed data rates, advanced DPI technologies and implementations are developed.