Rift Valley fever virus (RVFV) is an arbovirus within the Bunyaviridae family capable of causing serious morbidity and mortality in humans and livestock. To identify host factors involved in bunyavirus replication, we employed genome-wide RNA interference (RNAi) screening and identified 381 genes whose knockdown reduced infection. The Wnt pathway was the most represented pathway when gene hits were functionally clustered. With further investigation, we found that RVFV infection activated Wnt signaling, was enhanced when Wnt signaling was preactivated, was reduced with knockdown of β-catenin, and was blocked using Wnt signaling inhibitors. Similar results were found using distantly related bunyaviruses La Crosse virus and California encephalitis virus, suggesting a conserved role for Wnt signaling in bunyaviral infection. We propose a model where bunyaviruses activate Wnt-responsive genes to regulate optimal cell cycle conditions needed to promote efficient viral replication. The findings in this study should aid in the design of efficacious host-directed antiviral therapeutics.
Molecular motor-driven self-assembly has been an active area of soft matter research for the past decade. Because molecular motors transform chemical energy into mechanical work, systems which employ molecular motors to drive self-assembly processes are able to overcome kinetic and thermodynamic limits on assembly time, size, complexity, and structure. Here, we review the progress in elucidating and demonstrating the rules and capabilities of motor-driven active self-assembly. We focus on the types of structures created and the degree of control realized over these structures, and discuss the next steps necessary to achieve the full potential of this assembly mode which complements robotic manipulation and passive self-assembly.
We report experimental results and simulations showing efficient laser energy coupling into plasmas at conditions relevant to the magnetized liner inertial fusion (MagLIF) concept. In MagLIF, to limit convergence and increase the hydrodynamic stability of the implosion, the fuel must be efficiently preheated. To determine the efficiency and physics of preheating by a laser, an Ar plasma with ne/ncrit∼0.04 is irradiated by a multi-ns, multi-kJ, 0.35-μm, phase-plate-smoothed laser at spot-averaged intensities ranging from 1.0×1014 to 2.5×1014W/cm2 and pulse widths from 2 to 10 ns. Time-resolved x-ray images of the laser-heated plasma are compared to two-dimensional radiation-hydrodynamic simulations that show agreement with the propagating emission front, a comparison that constrains laser energy deposition to the plasma. The experiments show that long-pulse, modest-intensity (I=1.5×1014W/cm2) beams can efficiently couple energy (∼82% of the incident energy) to MagLIF-relevant long-length (9.5 mm) underdense plasmas. The demonstrated heating efficiency is significantly higher than is thought to have been achieved in early integrated MagLIF experiments [A. B. Sefkow, Phys. Plasmas 21, 072711 (2014)10.1063/1.4890298].
The 2014 Sandia Verification & Validation Challenge Workshop was held at the 3rd ASME Verification & Validation Symposium in Las Vegas, on May 5-8, 2014. The workshop was built around a challenge problem, formulated as an engineering investigation that required integration of experimental data, modeling and simulation, and verification and validation. The challenge problem served as a common basis for the ASME Journal of Verification, Validation, and Uncertainty Quantification participants to both demonstrate methodology and explore a critical aspect of the field: the role of verification and validation in establishing credibility and supporting decision making. Ten groups presented responses to the challenge problem at the workshop, and the follow-on efforts are documented in this special edition of the ASME Journal of Verification, Validation, and Uncertainty Quantification.
The objective of this work was twofold: (1) measure reliable fatigue crack growth relationships for X65 steel and its girth weld in high-pressure hydrogen gas to enable structural integrity assessments of hydrogen pipelines, and (2) evaluate the hydrogen accelerated fatigue crack growth susceptibility of the weld fusion zone and heat-affected zone relative to the base metal. Fatigue crack growth relationships (da/dN versus ΔK) were measured for girth welded X65 pipeline steel in high pressure hydrogen gas (21 MPa) and in air. Hydrogen assisted fatigue crack growth was observed for the base metal (BM), fusion zone (FZ), and heat-affected zone (HAZ), and was manifested through crack growth rates reaching nearly an order of magnitude acceleration over rates in air. At higher ΔK values, crack growth rates of BM, FZ, and HAZ were coincident; however, at lower ΔK, the fatigue crack growth relationships exhibited some divergence with the fusion zone having the highest crack growth rates. These relative fatigue crack growth rates in the BM, FZ, and HAZ were provisional, however, since both crack closure and residual stress contributed to the crack-tip driving force in specimens extracted from the HAZ. Despite the relatively high applied R-ratio (R = 0.5), crack closure was detected in the heat affected zone tests, in contrast to the absence of crack closure in the base metal tests. Crack closure corrections were performed using the adjusted compliance ratio method and the effect of residual stress on Kmax was determined by the crack-compliance method. Crack-tip driving forces that account for closure and residual stress effects were quantified as a weighted function of ΔK and Kmax (i.e., Knorm), and the resulting da/dN versus Knorm relationships showed that the HAZ exhibited higher hydrogen accelerated fatigue crack growth rates than the BM at lower Knorm values.
Small or moderate-weight space launches could significantly benefit from an electrically powered launch complex, based on an electromagnetic coil launcher. This paper presents results of studies to estimate the required launcher parameters, and estimate the cost of such a launch facility. This study is based on electromagnetic launch, or electromagnetic gun technology which is constrained to a coaxial geometry to take advantage of the efficiency of closely-coupled coils. This geometry, along with reasonable constraints on the length and power requirements for the launcher, match most naturally to relatively small satellites in low-earth orbits. The launcher energy and power requirements fall in the range of 40 - 260 GJ and 20 - 400 GW electric. Parametric evaluations have been conducted with a launcher length of 1-2 km, exit velocity of 1 - 6 km/s, and payloads of 100 -1000 kg. The launch requires high acceleration, so the satellite package must be hardened. The EM launch complex could greatly reduce the amount of fuels handling, reduce the turn-around time between launches, allow more concurrence in launch preparation, reduce the manpower requirements for launch vehicle preparation and increase the reliability of launch by using more standardized vehicle preparations.
A systematic approach to developing compact reduced reaction models is proposed for liquid hydrocarbon fuels using n-dodecane and n-butane as the model fuels. The approach has three elements. Fast fuel cracking reactions are treated by the quasi-steady state approximation (QSSA) and lumped into semi-global reactions to yield key cracking products that are C1-C4 in size. Directed relation graph (DRG) and sensitivity analysis reduce the foundational fuel chemistry model to a skeletal model describing the oxidation of the C1-C4 compounds. Timescale-based reduction using, e.g., QSSA, is then employed to produce the final reduced model. For n-dodecane, a 24-species reduced model is derived from JetSurF and tested against the detailed model for auto-ignition, perfectly stirred reactors (PSR), premixed flame propagation, and extinction of premixed and non-premixed counterflow flames. It is shown that the QSSA of fuel cracking reactions is valid and robust under high-temperature conditions from laminar flames, where mixing is controlled by molecular diffusion, to perfectly stirred reactors, which correspond to the limit of fast turbulent mixing. Bifurcation analysis identifies the controlling processes of ignition and extinction and shows that these phenomena are insensitive to the details of fuel cracking. To verify the applicability of the above finding to turbulent flames, 2-D direct numerical simulation (DNS) of a lean turbulent premixed flame of n-butane/air with Karlovitz number of 250 was carried out using a reduced model developed from USC-Mech II. The results show that QSSA for fuel cracking remains valid even under intense turbulence conditions. Statistical analysis of the DNS data shows that fuel cracking is complete before the flame zone, and for the conditions tested, turbulent transport does not bring any significant fuel molecules into the flame zones, thus further substantiating the validity of the approach proposed.
As discussed in the previous chapter, the purpose of peridynamics is to unify the mechanics of continuous media, continuous media with evolving discontinuities, and discrete particles. To accomplish this, peridynamics avoids the use of partial derivatives of the deformation with respect to spatial coordinates. Instead, it uses integral equations that remain valid on discontinuities. Discrete particles, as will be discussed later in this chapter, are treated using Dirac delta functions.
Three-dimensional deformation of rupture discs subjected to gas-dynamic shock loading was measured using a stereomicroscope digital image correlation (DIC) system. One-dimensional blast waves generated with a small-diameter, explosively driven shock tube were used for studying the fluid-structure interactions that exist when incident onto relatively low-strength rupture discs. Prior experiments have shown that subjecting the 0. 64-cm-diameter, stainless steel rupture discs to shock waves of varying strength results in a range of responses from no rupture to shear at the outer weld diameter. In this work, the outer surface of the rupture discs were prepared for DIC using 100–150 _m-sized speckles and illuminated with a Xenon flashlamp. Two synchronized Shimadzu HPV-2 cameras coupled to an Olympus microscope captured stereoimage sequences of rupture disc behavior at speeds of 1 MHz. Image correlation performed on the stereo-images resulted in spatially resolved surface deformation. The experimental facility, specifics of the DIC diagnostic technique, and the temporal deformation and velocity of the surface of a rupturing disc are presented.
Experiments were performed to characterize the mechanical response of several different rigid polyurethane foams to large deformation. In these experiments, the effects of load path, loading rate, and temperature were investigated. Results from these experiments indicated that rigid polyurethane foams exhibit significant damage, volumetric and deviatoric plasticity when they are compressed. Rigid polyurethane foams were also found to be extremely strain-rate and temperature dependent. These foams are also rather brittle and crack when loaded to small strains in tension or to larger strains in compression. Thus, a phenomenological Unified Creep Plasticity Damage (UCPD) model was developed to describe the mechanical response of these foams to large deformation at a variety of temperatures and strain rates. This paper includes a description of recent experiments and experimental findings. Next, development of a UCPD model for rigid, polyurethane foams is described. Finite element simulations with the new UCPD model are compared with experimental results to show behavior that can be captured with this model.
Evermore sophisticated ductile plasticity and failure models demand experimental material characterization of shear behavior; yet, the mechanics community lacks a widely accepted, standard test method for shear-dominated deformation and failure of ductile metals. We investigated the use of the V-notched rail test, borrowed from the ASTM D7078 standard for shear testing of composites, for shear testing of Ti-6Al-4V titanium alloy sheet material, considering sheet rolling direction and quasi-static and transient load rates. In this paper, we discuss practical aspects of testing, modifications to the specimen geometry, and the experimental shear behavior of Ti-6Al-4V. Specimen installation, machine compliance, specimen-grip slip during testing, and specimen V-notched geometry all influenced the measured specimen behavior such that repeatable shear-dominated behavior was initially difficult to obtain. We will discuss the careful experimental procedure and set of measurements necessary to extract meaningful shear information for Ti-6Al-4V. We also evaluate the merits and deficiencies, including practicality of testing for engineering applications and quality of results, of the V-notched rail test for characterization of ductile shear behavior.
This paper describes the challenge problem associated with the 2014 Sandia Verification and Validation (V&V) Challenge Workshop. The problem was developed to highlight core issues in V&V of engineering models. It is intended as an analog to projects currently underway at the Sandia National Laboratories—in other words, a realistic case study in applying V&V methods and integrating information from experimental data and simulations to support decisions. The problem statement includes the data, model, and directions for participants in the challenge. In addition, the workings of the provided code and the “truth model” used to create the data are revealed. The code, data, and truth model are available in this paper.
Banded ferrite-pearlite X65 pipeline steel was tested in high pressure hydrogen gas to evaluate the effects of oriented pearlite on hydrogen assisted fatigue crack growth. Test specimens were oriented in the steel pipe such that cracks propagated either parallel or perpendicular to the banded pearlite. The ferrite-pearlite microstructure exhibited orientation dependent behavior in which fatigue crack growth rates were significantly lower for cracks oriented perpendicular to the banded pearlite compared to cracks oriented parallel to the bands. The reduction of hydrogen assisted fatigue crack growth across the banded pearlite is attributed to a combination of crack-tip branching and impeded hydrogen diffusion across the banded pearlite.
The contribution of each component of a power generation plant to the levelized cost of energy (LCOE) can be estimated and used to increase the power output while reducing system operation and maintenance costs. The LCOE is used in order to quantify solar receiver coating influence on the LCOE of solar power towers. Two new parameters are introduced: the absolute levelized cost of coating (LCOC) and the LCOC efficiency. Depending on the material properties, aging, costs, and temperature, the absolute LCOC enables quantifying the cost-effectiveness of absorber coatings, as well as finding optimal operating conditions. The absolute LCOC is investigated for different hypothetic coatings and is demonstrated on Pyromark 2500 paint. Results show that absorber coatings yield lower LCOE values in most cases, even at significant costs. Optimal reapplication intervals range from one to five years. At receiver temperatures greater than 700 °C, non-selective coatings are not always worthwhile while durable selective coatings consistently reduce the LCOE-up to 12% of the value obtained for an uncoated receiver. The absolute LCOC is a powerful tool to characterize and compare different coatings, not only considering their initial efficiencies but also including their durability.
Fast algorithms for matrix multiplication, namely those that perform asymptotically fewer scalar operations than the classical algorithm, have been considered primarily of theoretical interest. Apart from Strassen's original algorithm, few fast algorithms have been efficiently implemented or used in practical applications. However, there exist many practical alternatives to Strassen's algorithm with varying performance and numerical properties. Fast algorithms are known to be numerically stable, but because their error bounds are slightly weaker than the classical algorithm, they are not used even in cases where they provide a performance benefit. We argue in this paper that the numerical sacrifice of fast algorithms, particularly for the typical use cases of practical algorithms, is not prohibitive, and we explore ways to improve the accuracy both theoretically and empirically. The numerical accuracy of fast matrix multiplication depends on properties of the algorithm and of the input matrices, and we consider both contributions independently. We generalize and tighten previous error analyses of fast algorithms and compare their properties. We discuss algorithmic techniques for improving the error guarantees from two perspectives: manipulating the algorithms, and reducing input anomalies by various forms of diagonal scaling. Finally, we benchmark performance and demonstrate our improved numerical accuracy.
The model for penetration of a wire braid is rigorously formulated. Integral formulas are developed from energy principles for both self and transfer immittances in terms of potentials for the fields. The detailed boundary value problem for the wire braid is also set up in a very efficient manner; the braid wires act as sources for the potentials in the form of a sequence of line multipoles with unknown coefficients that are determined by means of conditions arising from the wire surface boundary conditions. Approximations are introduced to relate the local properties of the braid wires to a simplified infinite periodic planar geometry. This is used to treat nonuniform coaxial geometries including eccentric interior coaxial arrangements and an exterior ground plane.
Riley, Zachary B.; Deshmukh, Rohit; Miller, Brent A.; Mcnamara, Jack J.; Casper, Katya M.
The inherent relationship between boundary-layer stability, aerodynamic heating, and surface conditions makes the potential for interaction between the structural response and boundary-layer transition an important and challenging area of study in high-speed flows. This paper phenomenologically explores this interaction using a fundamental two-dimensional aerothermoelastic model under the assumption of an aluminum panel with simple supports. Specifically, an existing model is extended to examine the impact of transition onset location, transition length, and transitional overshoot in heat flux and fluctuating pressure on the structural response of surface panels. Transitional flow conditions are found to yield significantly increased thermal gradients, and they can result in higher maximumpanel temperatures compared to turbulent flow. Results indicate that overshoot in heat flux and fluctuating pressure reduces the flutter onset time and increases the strain energy accumulated in the panel. Furthermore, overshoot occurring near the midchord can yield average temperatures and peak displacements exceeding those experienced by the panel subject to turbulent flow. These results suggest that fully turbulent flow does not always conservatively predict the thermo-structural response of surface panels.
It has recently been reported that two types of triaxial electric or magnetic fields can drive vorticity in dielectric or magnetic particle suspensions, respectively. The first type - symmetry-breaking rational fields - consists of three mutually orthogonal fields, two alternating and one dc, and the second type - rational triads - consists of three mutually orthogonal alternating fields. In each case it can be shown through experiment and theory that the fluid vorticity vector is parallel to one of the three field components. For any given set of field frequencies this axis is invariant, but the sign and magnitude of the vorticity (at constant field strength) can be controlled by the phase angles of the alternating components and, at least for some symmetry-breaking rational fields, the direction of the dc field. In short, the locus of possible vorticity vectors is a 1-d set that is symmetric about zero and is along a field direction. In this paper we show that continuous, 3-d control of the vorticity vector is possible by progressively transitioning the field symmetry by applying a dc bias along one of the principal axes. Such biased rational triads are a combination of symmetry-breaking rational fields and rational triads. A surprising aspect of these transitions is that the locus of possible vorticity vectors for any given field bias is extremely complex, encompassing all three spatial dimensions. As a result, the evolution of a vorticity vector as the dc bias is increased is complex, with large components occurring along unexpected directions. More remarkable are the elaborate vorticity vector orbits that occur when one or more of the field frequencies are detuned. These orbits provide the basis for highly effective mixing strategies wherein the vorticity axis periodically explores a range of orientations and magnitudes.
Extension springs are used to apply a constant force at a set displacement in a wide variety of components. When subjected to an abnormal thermal event, such as in a fire, the load carrying capacity of these springs can degrade. In this study, relaxation tests were conducted on extension springs where the heating rate and dwell temperature were varied to investigate the reduction in force provided by the springs. Two commonly used spring material types were tested, 304 stainless steel and Elgiloy, a cobalt-chrome-nickel alloy. Challenges associated with obtaining accurate spring response to an abnormal thermal event are discussed. The resulting data can be used to help develop and test models for thermally activated creep in springs and to provide designers with recommendations to help ensure the reliability of the springs for the duration of the thermal event.
The Mount Simon Sandstone and Eau Claire Formation represent a potential reservoir-caprock system for wastewater disposal, geologic CO2 storage, and compressed air energy storage (CAES) in the Midwestern United States. A primary concern to site performance is heterogeneity in rock properties that could lead to nonideal injectivity and distribution of injected fluids (e.g., poor sweep efficiency). Using core samples from the Dallas Center domal structure, Iowa, we investigate pore characteristics that govern flow properties of major lithofacies of these formations. Methods include gas porosimetry and permeametry, mercury intrusion porosimetry, thin section petrography, and X-ray diffraction. The lithofacies exhibit highly variable intraformational and interformational distributions of pore throat and body sizes. Based on pore-throat size, there are four distinct sample groups. Micropore-throat-dominated samples are from the Eau Claire Formation, whereas the macropore-dominated, mesopore-dominated, and uniform-dominated samples are from the Mount Simon Sandstone. Complex paragenesis governs the high degree of pore and pore-throat size heterogeneity, due to an interplay of precipitation, nonuniform compaction, and later dissolution of cements. The cement dissolution event probably accounts for much of the current porosity in the unit. Mercury intrusion porosimetry data demonstrate that the heterogeneous nature of the pore networks in the Mount Simon Sandstone results in a greater than normal opportunity for reservoir capillary trapping of nonwetting fluids, as quantified by CO2 and air column heights that vary over three orders of magnitude, which should be taken into account when assessing the potential of the reservoir-caprock system for waste disposal (CO2 or produced water) and resource storage (natural gas and compressed air). Our study quantitatively demonstrates the significant impact of millimeter-scale to micron-scale porosity heterogeneity on flow and transport in reservoir sandstones.
Aerosol deposition (AD) is a solid-state deposition technology that has been developed to fabricate ceramic coatings nominally at room temperature. Sub-micron ceramic particles accelerated by pressurized gas impact, deform, and consolidate on substrates under vacuum. Ceramic particle consolidation in AD coatings is highly dependent on particle deformation and bonding; these behaviors are not well understood. In this work, atomistic simulations and in situ micro-compressions in the scanning electron microscope, and the transmission electron microscope (TEM) were utilized to investigate fundamental mechanisms responsible for plastic deformation/fracture of particles under applied compression. Results showed that highly defective micron-sized alumina particles, initially containing numerous dislocations or a grain boundary, exhibited no observable shape change before fracture/fragmentation. Simulations and experimental results indicated that particles containing a grain boundary only accommodate low strain energy per unit volume before crack nucleation and propagation. In contrast, nearly defect-free, sub-micron, single crystal alumina particles exhibited plastic deformation and fracture without fragmentation. Dislocation nucleation/motion, significant plastic deformation, and shape change were observed. Simulation and TEM in situ micro-compression results indicated that nearly defect-free particles accommodate high strain energy per unit volume associated with dislocation plasticity before fracture. The identified deformation mechanisms provide insight into feedstock design for AD.
Vertical GaN power diodes with a bilayer edge termination (ET) are demonstrated. The GaN p-n junction is formed on a low threading dislocation defect density (104 - 105 cm-2) GaN substrate, and has a 15-μm-thick n-type drift layer with a free carrier concentration of 5 × 1015 cm-3. The ET structure is formed by N implantation into the p+-GaN epilayer just outside the p-type contact to create compensating defects. The implant defect profile may be approximated by a bilayer structure consisting of a fully compensated layer near the surface, followed by a 90% compensated (p) layer near the n-type drift region. These devices exhibit avalanche breakdown as high as 2.6 kV at room temperature. Simulations show that the ET created by implantation is an effective way to laterally distribute the electric field over a large area. This increases the voltage at which impact ionization occurs and leads to the observed higher breakdown voltages.
During the Frio-I Brine Pilot CO2 injection experiment in 2004, distinct geochemical changes in response to the injection of 1600tons of CO2 were recorded in brine samples collected from the monitoring well. Previous geochemical modeling studies have considered dissolution of calcite and iron oxyhydroxides, or release of adsorbed iron, as the most likely sources of the increased ion concentrations. In this modeling study we explore possible alternative sources of the increasing calcium and iron, based on the data from the detailed petrographic characterization of the Upper Frio Formation "C". Particularly, we evaluate whether dissolution of pyrite and oligoclase (anorthite component) can account for the observed geochemical changes. Due to kinetic limitations, dissolution of pyrite and anorthite cannot account for the increased iron and calcium concentrations on the time scale of the field test (10 days). However, dissolution of these minerals is contributing to carbonate and clay mineral precipitation on the longer time scales (1000 years). We estimated that during the field test dissolution of calcite and iron oxide resulted in ~0.02wt.% loss of the reservoir rock mass. The reactive transport models were constructed for 25 and 59°C temperature and using Pitzer and B-dot activity correction methods. These models predict carbonate minerals, dolomite and ankerite, as well as clay minerals kaolinite, nontronite and montmorillonite, will precipitate in the Frio Formation "C" sandstone as the system progresses toward chemical equilibrium during a 1000-year period. Cumulative uncertainties associated with using different thermodynamic databases, activity correction models (Pitzer vs. B-dot), and extrapolating to reservoir temperature, are manifested in the difference in the predicted mineral phases. However, these models are consistent with regards to the total volume of mineral precipitation and porosity values which are predicted to within 0.002%.
Balzuweit, Evan; Bunde, David P.; Leung, Vitus J.; Finley, Austin; Lee, Alan C.S.
We present a local search strategy to improve the coordinate-based mapping of a parallel job's tasks to the MPI ranks of its parallel allocation in order to reduce network congestion and the job's communication time. The goal is to reduce the number of network hops between communicating pairs of ranks. Our target is applications with a nearest-neighbor stencil communication pattern running on mesh systems with non-contiguous processor allocation, such as Cray XE and XK Systems. Using the miniGhost mini-app, which models the shock physics application CTH, we demonstrate that our strategy reduces application running time while also reducing the runtime variability. We further show that mapping quality can vary based on the selected allocation algorithm, even between allocation algorithms of similar apparent quality.
This work describes the energy dissipation arising from microslip for an elastic shell incorporating shear and longitudinal deformation resting on a rough-rigid foundation. This phenomenon is investigated using finite element (FE) analysis and nonlinear geometrically exact shell theory. Both approaches illustrate the effect of shear within the shell and observe a reduction in the energy dissipated from microslip as compared to a similar system neglecting shear deformation. In particular, it is found that the shear deformation allows for load to be transmitted beyond the region of slip so that the entire interface contributes to the load carrying capability of the shell. The energy dissipation resulting from the shell model is shown to agree well with that arising from the FE model, and this representation can be used as a basis for reduced order models that capture the microslip phenomenon.
Nishawala, Vinesh V.; Ostoja-Starzewski, Martin; Leamy, Michael J.; Demmie, Paul N.
Peridynamics is a non-local continuum mechanics formulation that can handle spatial discontinuities as the governing equations are integro-differential equations which do not involve gradients such as strains and deformation rates. This paper employs bond-based peridynamics. Cellular Automata is a local computational method which, in its rectangular variant on interior domains, is mathematically equivalent to the central difference finite difference method. However, cellular automata does not require the derivation of the governing partial differential equations and provides for common boundary conditions based on physical reasoning. Both methodologies are used to solve a half-space subjected to a normal load, known as Lamb's Problem. The results are compared with theoretical solution from classical elasticity and experimental results. This paper is used to validate our implementation of these methods.
Throughout the development cycle of structural components or assemblies that require new and unproven manufacturing techniques, the issue of unit to unit variability inevitably arises. The challenge of defining dynamic similarity between units is a problem that is often overlooked or forgotten, but can be very important depending on the functional criteria of the final product. This work aims to provide some guidance on the approach to such a problem, utilizing different methodologies from the modal and vibration testing community. Expanding on previous efforts, a non-intrusive dynamic characterization test is defined to assess similarity on an assembly that is currently being developed. As the assembly is qualified through various test units, the same data sets are taken to build a database of “similarity” data. The work presented here will describe the challenges observed with defining similarity metrics on a multi-body structure with a limited quantity of test units. Also, two statistical characterizations of dynamic FRFs are presented from which one may choose criterion based on some judgment to establish whether units are in or out of family. The methods may be used when the “intended purpose” or “functional criteria” are unknown.
Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then they are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.
Magnetohydrodynamic (MHD) representations are used to model a wide range of plasma physics applications and are characterized by a nonlinear system of partial differential equations that strongly couples a charged fluid with the evolution of electromagnetic fields. The resulting linear systems that arise from discretization and linearization of the nonlinear problem are generally difficult to solve. In this paper, we investigate multigrid preconditioners for this system. We consider two well-known multigrid relaxation methods for incompressible fluid dynamics: Braess-Sarazin relaxation and Vanka relaxation. We first extend these to the context of steady-state one-fluid viscoresistive MHD. Then we compare the two relaxation procedures within a multigrid-preconditioned GMRES method employed within Newton's method. To isolate the effects of the different relaxation methods, we use structured grids, inf-sup stable finite elements, and geometric interpolation. We present convergence and timing results for a two-dimensional, steady-state test problem.
Broadband impact excitation in structural dynamics is a common technique used to detect and characterize nonlinearities in mechanical systems since it excites many frequencies of a structure at once. Non-stationary time signals from transient ring-down measurements require time-frequency analysis tools to observe variations in frequency and energy dissipation as the response evolves. This work uses the short-time Fourier transform to estimate the instantaneous parameters from measured or simulated data. By combining the discrete Fourier transform with an expanding or contracting window function that moves along the time axis, the resulting spectra are used to estimate the instantaneous frequencies, damping ratios and complex Fourier coefficients. This method is demonstrated on a multi-degree-of-freedom beam with a cubic spring attachment. The amplitude-frequency dependence in the damped response is compared to the undamped nonlinear normal modes. A second example shows the results from experimental ring-down measurements taken on a beam with a lap joint, revealing how the mechanical interface introduces nonlinear frequency and damping parameters.
Motivated by the current demands in high-performance structural analysis, and by a desire to better model systems with localized nonlinearities, analysts have developed a number of different approaches for modelling and simulating the dynamics of a bolted-joint structure. However, the types of conditions that make one approach more effective than the others remains poorly understood due to the fact that these approaches are developed from fundamentally and phenomenologically different concepts. To better grasp their similarities and differences, this research presents a numerical round robin that assesses how well three different approaches predict and simulate a mechanical joint. These approaches are applied to analyze a system comprised of two linear beam structures with a bolted joint interface, and their strengths and shortcomings are assessed in order to determine the optimal conditions for their use.
Simulation of the response of a system to an acoustic environment is desirable in the assessment of aerospace structures in flight-like environments. In simulating a laboratory acoustic test a large challenge is modeling the as-tested acoustic field. Acoustic source inversion capabilities in Sandia’s Sierra/SD structural dynamics code have allowed for the determination of an acoustic field based on measured microphone responses—given measured pressures, source inversion optimization algorithms determine the input parameters of a set of acoustic sources defined in an acoustic finite element model. Inherently, the resulting acoustic field is dependent on the target microphone data. If there are insufficient target points, then the as-tested field may not be recreated properly. Here, the question of number of microphones is studied using synthetic data, that is, target data taken from a previous simulation which allows for comparison of the full pressure field—an important benefit not available with test data. By exploring a range of target points distributed throughout the domain, a rate of convergence to the true field can be observed. Results will be compared with the goal of developing guidelines for the number of sensors required to aid in the design of future laboratory acoustic tests to be used for model assessment.
The exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.
Digital systems in an out-of-nominal environment (e.g., one causing hardware bit flips) may not be expected to function correctly in all respects but may be required to fail safely. We present an approach for understanding and verifying a system’s out-of-nominal behavior as an abstraction of nominal behavior that preserves designated critical safety requirements. Because abstraction and refinement are already widely used for improved tractability in formal design and proof techniques, this additional way of viewing an abstraction can potentially verify a system’s out-of-nominal safety with little additional work. We illustrate the approach with a simple model of a turnstile controller with possible logic faults (formalized in the temporal logic of actions and NuSMV), noting how design choices can be guided by the desired out-of-nominal abstraction. Principles of robustness in complex systems (specifically, Boolean networks) are found to be compatible with the formal abstraction approach. This work indicates a direction for broader use of formal methods in safety-critical systems.
Conference Proceedings of the Society for Experimental Mechanics Series
Bonney, Matthew S.; Kammer, Daniel C.; Brake, M.R.W.
The quantification of model form uncertainty is very important for engineers to understand when using a reduced order model. This quantification requires multiple numerical simulations which can be computationally expensive. Different sampling techniques, including Monte Carlo and Latin Hypercube, are explored while using the maximum entropy method to quantify the uncertainty. The maximum entropy method implements random matrices that maintain essential properties. This is explored on a planar frame using different types of substructure representations, such as Craig-Bampton. Along with the model form uncertainty of the substructure representation, the effect of component mode synthesis for each type of substructure representation on the model form uncertainty is studied.
Coherent change detection (CCD) images, which are prod- ucts of combining two synthetic aperture radar (SAR) images taken at different times of the same scene, can reveal subtle sur- face changes such as those made by tire tracks. These images, however, have low texture and are noisy, making it difficult to au- Tomate track finding. Existing techniques either require user cues and can only trace a single track or make use of templates that are difficult to generalize to different types of tracks, such as those made by motorcycles, or vehicles sizes. This paper presents an approach to automatically identify vehicle tracks in CCD images. We identify high-quality track segments and leverage the con- strained Delaunay triangulation (CDT) to find completion track segments. We then impose global continuity and track smoothness using a binary random field on the resulting CDT graph to determine edges that belong to real tracks. Experimental results show that our algorithm outperforms existing state-of-the- Art techniques in both accuracy and speed.
This paper presents a probabilistic origin-destination table for waterborne containerized imports. The analysis makes use of 2012 Port Import/Export Reporting Service data, 2012 Surface Transportation Board waybill data, a gravity model, and information on the landside transportation mode split associated with specifc ports. This analysis suggests that about 70% of the origin-destination table entries have a coeffcient of variation of less than 20%. This 70% of entries is associated with about 78% of the total volume. This analysis also makes evident the importance of rail interchange points in Chicago, Illinois; Memphis, Tennessee; Dallas, Texas; and Kansas City, Missouri, in supporting the transportation of containerized goods from Asia through West Coast ports to the eastern United States.
This paper describes the design of Teko, an object-oriented C++ library for implementing advanced block preconditioners. Mathematical design criteria that elucidate the needs of block preconditioning libraries and techniques are explained and shown to motivate the structure of Teko. For instance, a principal design choice was for Teko to strongly reflect the mathematical statement of the preconditioners to reduce development burden and permit focus on the numerics. Additional mechanisms are explained that provide a pathway to developing an optimized production capable block preconditioning capability with Teko. Finally, Teko is demonstrated on fluid flow and magnetohydrodynamics applications. In addition to highlighting the features of the Teko library, these new results illustrate the effectiveness of recent preconditioning developments applied to advanced discretization approaches.
Relative motion at bolted connections can occur for large shock loads as the internal shear force in the bolted connection overcomes the frictional resistive force. This macroslip in a structure dissipates energy and reduces the response of the components above the bolted connection. There is a need to be able to capture macroslip behavior in a structural dynamics model. A linear model and many nonlinear models are not able to predict marcoslip effectively. The proposed method to capture macroslip is to use the multi-body dynamics code ADAMS to model joints with 3-D contact at the bolted interfaces. This model includes both static and dynamic friction. The joints are preloaded and the pinning effect when a bolt shank impacts a through hole inside diameter is captured. Substructure representations of the components are included to account for component flexibility and dynamics. This method was applied to a simplified model of an aerospace structure and validation experiments were performed to test the adequacy of the method.
In this study, eye tracking metrics and visual saliency maps were used to assess analysts' interactions with synthetic aperture radar (SAR) imagery. Participants with varying levels of experience with SAR imagery completed a target detection task while their eye movements and behavioral responses were recorded. The resulting gaze maps were compared with maps of bottom-up visual saliency and with maps of automatically detected image features The results showed striking differences between professional SAR analysis and novices in terms of how their visual search patterns related to the visual saliency of features in the imagery. They also revealed patterns that reflect the utility of various features in the images for the professional analysts These findings have implications for system design andfor the design and use of automatic feature classification algorithms.
The Structural Dynamics department at Sandia National Laboratories has acquired a 3D Scanning Laser Doppler Vibrometer system for making vibration and modal test measurements. This paper presents the results of testing performed to examine the capabilities and limitations of that system. The test article under consideration was a conical part with two different surface materials which allowed the examination of the effect of angle of incidence and surface reflectivity on the measurement. The system was operated in both 1D and 3D modes, and the results from the 1D scan were compared to a scan performed with a previous generation system to evaluate the improvements between the generations. Data from the laser systems were exported to standard curve fitting software, and modes were fit to the data.
Reynolds-Averaged Navier-Stokes models are not very accurate for high-Reynolds-number compressible jet-incrossflow interactions. The inaccuracy arises from the use of inappropriate model parameters and model-form errors in the Reynolds-Averaged Navier-Stokes model. In this work, the hypothesis is pursued that Reynolds-Averaged Navier-Stokes predictions can be significantly improved by using parameters inferred from experimental measurements of a supersonic jet interacting with a transonic crossflow.ABayesian inverse problem is formulated to estimate three Reynolds-Averaged Navier-Stokes parameters (Cμ;Cϵ2;Cϵ1), and a Markov chain Monte Carlo method is used to develop a probability density function for them. The cost of the Markov chain Monte Carlo is addressed by developing statistical surrogates for the Reynolds-Averaged Navier-Stokes model. It is found that only a subset of the (Cμ;Cϵ2;Cϵ1) spaceRsupports realistic flow simulations.Ris used as a prior belief when formulating the inverse problem. It is enforced with a classifier in the current Markov chain Monte Carlo solution. It is found that the calibrated parameters improve predictions of the entire flowfield substantially when compared to the nominal/ literature values of (Cμ;Cϵ2;Cϵ1); furthermore, this improvement is seen to hold for interactions at other Mach numbers and jet strengths for which the experimental data are available to provide a comparison. The residual error is quantifies, which is an approximation of the model-form error; it is most easily measured in terms of turbulent stresses.
This work presents a new Krylov-subspace-recycling method for efficiently solving sequences of linear systems of equations characterized by varying right-hand sides and symmetric-positive-definite matrices. As opposed to typical truncation strategies used in recycling such as deflation, we propose a truncation method inspired by goal-oriented proper orthogonal decomposition (POD) from model reduction. This idea is based on the observation that model reduction aims to compute a low-dimensional subspace that contains an accurate solution; as such, we expect the proposed method to generate a low-dimensional subspace that is well suited for computing solutions that can satisfy inexact tolerances. In particular, we propose specific goal-oriented POD "ingredients" that align the optimality properties of POD with the objective of Krylov-subspace recycling. To compute solutions in the resulting "augmented" POD subspace, we propose a hybrid direct/iterative three-stage method that leverages (1) the optimal ordering of POD basis vectors, and (2) well-conditioned reduced matrices. Numerical experiments performed on solid-mechanics problems highlight the benefits of the proposed method over existing approaches for Krylov-subspace recycling.
We present all-dielectric 2D and 3D metamaterials that are monolithically fabricated from III-V semiconductor nanostructures. The active/gain and high optical nonlinearity properties of the metamaterials can lead to new classes of active devices.
The redox-active bis(imino)acenapthene (BIAN) ligand was used to synthesize homoleptic aluminum, chromium, and gallium complexes of the general formula (BIAN)3M. The resulting compounds were characterized using X-ray crystallography, NMR, EPR, magnetic susceptibility and cyclic voltammetry measurements and modeled using both DFT and ab initio wavefunction calculations to compare the orbital contributions of main group elements and transition metals in ligand-based redox events. Complexes of this type have the potential to improve the energy density and electrolyte stability of grid-scale energy storage technologies, such as redox flow batteries, through thermodynamically-clustered redox events.
Conference Proceedings of the Society for Experimental Mechanics Series
Stender, M.; Papangelo, A.; Allen, M.; Brake, M.R.W.; Schwingshackl, C.; Tiedemann, M.
Many engineered structures are assembled using different kinds of joints such as bolted, riveted and clamped joints. Even if joints are often a small part of the overall structure, they can have a massive impact on its dynamics due to the introduction of nonlinearities. Thus, joints are considered a design liability. Significant effort has been spent in joint characterization and modelling, but a predictive joint model is still non-existent. To overcome these uncertainties and ensure certain safety standards, joints are usually overdesigned according to static considerations and their stiffness. Especially damping and nonlinearity are not considered during the design process. This can lead to lower performance, lower payload, and as result of the joints structural dynamic models often do a poor job of predicting the dynamic response. However, it is well-known that, particularly for metal structures, joints represent the main source of energy dissipation. In this work a minimal model is used to show how structural performance can be improved using joints as a design variable. Common optimization tools are applied to a nonlinear joint model in order to damp undesired structural vibrations. Results illustrate how the intentional choice of joint parameters and locations can effectively reduce vibration level for a given operating point of a jointed structure.
The sequence of crystallization in a recrystallizable lithium silicate sealing glass-ceramic Li2O–SiO2–Al2O3–K2O–B2O3–P2O5–ZnO was analyzed by in situ high-temperature X-ray diffraction (HTXRD). Glass-ceramic specimens have been subjected to a two-stage heat-treatment schedule, including rapid cooling from sealing temperature to a first hold temperature 650°C, followed by heating to a second hold temperature of 810°C. Notable growth and saturation of Quartz was observed at 650°C (first hold). Cristobalite crystallized at the second hold temperature of 810°C, growing from the residual glass rather than converting from the Quartz. The coexistence of quartz and cristobalite resulted in a glass-ceramic having a near-linear thermal strain, as opposed to the highly nonlinear glass-ceramic where the cristobalite is the dominant silica crystalline phase. HTXRD was also performed to analyze the inversion and phase stability of the two types of fully crystallized glass-ceramics. While the inversion in cristobalite resembles the character of a first-order displacive phase transformation, i.e., step changes in lattice parameters and thermal hysteresis in the transition temperature, the inversion in quartz appears more diffuse and occurs over a much broader temperature range. Localized tensile stresses on quartz and possible solid-solution effects have been attributed to the transition behavior of quartz crystals embedded in the glass-ceramics.
Electric motors are a popular choice for mobile robots because they can provide high peak efficiencies, high speeds, and quiet operation. However, the continuous torque performance of these actuators is thermally limited due to joule heating, which can ultimately cause insulation breakdown. In this work we illustrate how motor housing design and active cooling can be used to significantly improve the ability of the motor to transfer heat to the environment. This can increase continuous torque density and reduce energy consumption. We present a novel housing design for brushless DC motors that provides improved heat transfer. This design achieves a 50% increase in heat transfer over a nominal design. Additionally, forced air or water cooling can be easily added to this configuration. Forced convection increases heat transfer over the nominal design by 79%with forced air and 107% with pumped water. Finally, we show how increased heat transfer reduces power consumption and we demonstrate that strategically spending energy on cooling can provide net energy savings of 4%-6%.
We present a synthetic study investigating the resolution limits of Full Wavefield Inversion (FWI) when applied to data generated from a visco-TTI-elastic (VTE) model. We compare VTE inversion having fixed Q and TTI, with acoustic inversion of acoustically generated data and elastic inversion of elastically generated data.
The need to better represent the material properties within the earth's interior has driven the development of higherfidelity physics, e.g., visco-tilted-transversely-isotropic (visco- TTI) elastic media and material interfaces, such as the ocean bottom and salt boundaries. This is especially true for full waveform inversion (FWI), where one would like to reproduce the real-world effects and invert on unprocessed raw data. Here we present a numerical formulation using a Discontinuous Galerkin (DG) finite-element (FE) method, which incorporates the desired high-fidelity physics and material interfaces. To offset the additional costs of this material representation, we include a variety of techniques (e.g., non-conformal meshing, and local polynomial refinement), which reduce the overall costs with little effect on the solution accuracy.
The kinetics of thermoset resin cure are multifaceted, with flow and wet-out being dependent on viscosity, devolatilization being a function of partial pressures, and crosslinking being dependent on temperature. A unique cure recipe must be developed to address and control each factor simultaneously. In the case of thick-section composites, an uncontrolled exotherm could cause the panel to cure from the inside out, causing severe process-induced residual stresses. To identify and control the peak heat generation from the exothermic crosslinking reaction, differential scanning calorimetry (DSC) was conducted for different candidate cure schedules. Resin rheology data and dynamic mechanical analysis (DMA) results were used to confirm a viable resin viscosity profile for each cure schedule. These experiments showed which isothermal holds and ramp rates best served to decrease the exothermic peak as well as when to apply pressure and vent the applied vacuum. From these data, a cure cycle was developed and applied to the material system. During cure, embedded thermocouples were used to monitor heat generation and drive cure temperature ramps and dwells. Ultrasonic testing and visual inspection by microscopy revealed good compaction and < 1 % porosity for two different composite panels with the same resin system. DSC of post-cured samples of each panel indicated a high degree of cure throughout the thickness of the panels, further qualifying the proven-in process.
A mathematical model was developed to investigate the performance limiting factors of Mg-ion battery with a Chevrel phase (MgxMo6S8) cathode and a Mg metal anode. The model was validated using experimental data from the literature [Cheng et al., Chem. Mater., 26, 4904 (2014)]. Two electrochemical reactions of the Chevrel phase with significantly different kinetics and solid diffusion were included in the porous electrode model, which captured the physics sufficiently well to generate charge curves of five rates (0.1C-2C) for two different particle sizes. Limitation analysis indicated that the solid diffusion and kinetics in the highervoltage plateau limit the capacity and increase the overpotential in the Cheng et al.'s thin (20-μm) electrodes. The model reveals that the performance of the cells with reasonable thickness would also be subject to electrolyte-phase limitations. The simulation also suggested that the polarization losses on discharge will be lower than that on charge, because of the differences in the kinetics and solid diffusion between the two reactions of the Chevrel phase.
We introduce Recursive Spoke Darts (RSD): a recursive hyperplane sampling algorithm that exploits the full duality between Voronoi and Delaunay entities of various dimensions. Our algorithm abandons the dependence on the empty sphere principle in the generation of Delaunay simplices providing the foundation needed for scalable consistent meshing. The algorithm relies on two simple operations: line-hyperplane trimming and spherical range search. Consequently, this approach improves scalability as multiple processors can operate on different seeds at the same time. Moreover, generating consistent meshes across processors eliminates the communication needed between them, improving scalability even more. We introduce a simple tweak to the algo- rithm which makes it possible not to visit all vertices of a Voronoi cell, generating almost-exact Delaunay graphs while avoiding the natural curse of dimensionality in high dimensions.
In this work we have presented a particle resuspension model implemented in the SNL code SIERRA/Fuego, which can be used to model particle dispersal and resuspension from surfaces. The method demonstrated is applicable to a class of particles, but would require additional parametric fits or physics models for extension to other applications, such as wetted particles or walls. We have demonstrated the importance of turbulent variations in the wall shear stress when considering resuspension, and implemented both shear stress variation models and stochastic resuspension models (not shown in this work). These models can be used in simulations with of physically realistic scenarios to augment lab-scale DOE Handbook data for airborne release fractions and respirable fractions in order to provide confidences for safety analysts and facility designers to apply in their analyses at DOE sites. Future work on this topic will involve validation of the presented model against experimental data and extension of the empirical models to be applicable to different classes of particles and surfaces.
The peridynamic theory of solid mechanics provides a natural framework for modeling constitutive response and simulating dynamic crack propagation, pervasive damage, and fragmentation. In the case of a fragmenting body, the principal quantities of interest include the number of fragments, and the masses and velocities of the fragments. We present a method for identifying individual fragments in a peridynamic simulation. We restrict ourselves to the meshfree approach of Silling and Askari, in which nodal volumes are used to discretize the computational domain. Nodal volumes, which are connected by peridynamic bonds, may separate as a result of material damage and form groups that represent fragments. Nodes within each fragment have similar velocities and their collective motion resembles that of a rigid body. The identification of fragments is achieved through inspection of the peridynamic bonds, established at the onset of the simulation, and the evolving damage value associated with each bond. An iterative approach allows for the identification of isolated groups of nodal volumes by traversing the network of bonds present in a body. The process of identifying fragments may be carried out at specified times during the simulation, revealing the progression of damage and the creation of fragments. Incorporating the fragment identification algorithm directly within the simulation code avoids the need to write bond data to disk, which is often prohibitively expensive. Results are recorded using fragment identification numbers. The identification number for each fragment is stored at each node within the fragment and written to disk, allowing for any number of post-processing operations, for example the construction of cumulative distribution functions for quantities of interest. Care is taken with regard to very small clusters of isolated nodes, including individual nodes for which all bonds have failed. Small clusters of nodes may be treated as tiny fragments, or may be omitted from the fragment identification process. The fragment identification algorithm is demonstrated using the Sierra/SolidMechanics analysis code. It is applied to a simulation of pervasive damage resulting from a spherical projectile impacting a brittle disk, and to a simulation of fragmentation of an expanding ductile ring.
Influence spread is an important phenomenon that occurs in many social networks. Influence maximization is the corresponding problem of finding the most influential nodes in these networks. In this paper, we present a new influence diffusion model, based on pairwise factor graphs, that captures dependencies and directions of influence among neighboring nodes.We use an augmented belief propagation algorithm to efficiently compute influence spread on this model so that the direction of influence is preserved. Due to its simplicity, the model can be used on large graphs with high-degree nodes, making the influence maximization problem practical on large, real-world graphs. Using large Flixster and Epinions datasets, we provide experimental results showing that our model predictions match well with ground-truth influence spreads, far better than other techniques. Furthermore, we show that the influential nodes identified by our model achieve significantly higher influence spread compared to other popular models. The model parameters can easily be learned from basic, readily available training data. In the absence of training, our approach can still be used to identify influential seed nodes.
Chambers, Mariah; Mallory, Stewart A.; Malone, Heather; Gao, Yuan; Anthony, Stephen M.; Yi, Yi; Cacciuto, Angelo; Yu, Yan
Amphiphilic Janus particles self-assemble into complex metastructures, but little is known about how their assembly might be modified by weak interactions with a nearby biological membrane surface. Here, we report an integrated experimental and molecular dynamics simulation study to investigate the self-assembly of amphiphilic Janus particles on a lipid membrane. We created an experimental system in which Janus particles are allowed to self-assemble in the same medium where zwitterionic lipids form giant unilamellar vesicles (GUVs). Janus particles spontaneously concentrated on the inner leaflet of the GUVs. They exhibited biased orientation and heterogeneous rotational dynamics as revealed by single particle rotational tracking. The combined experimental and simulation results show that Janus particles concentrate on the lipid membranes due to weak particle-lipid attraction, whereas the biased orientation of particles is driven predominantly by inter-particle interactions. This study demonstrates the potential of using lipid membranes to influence the self-assembly of Janus particles.
The structure-dependent vibrational properties of different Mg(BH4)2 polymorphs (α, β, γ, and δ phases) were investigated with a combination of neutron vibrational spectroscopy (NVS) measurements and density functional theory (DFT) calculations, with emphasis placed on the effects of the local structure and orientation of the BH4- anions. DFT simulations closely match the neutron vibrational spectra. The main bands in the low-energy region (20-80 meV) are associated with the BH4- librational modes. The features in the intermediate energy region (80-120 meV) are attributed to overtones and combination bands arising from the lower-energy modes. The features in the high-energy region (120-200 meV) correspond to the BH4- symmetric and asymmetric bending vibrations, of which four peaks located at 140, 142, 160, and 172 meV are especially intense. There are noticeable intensity distribution variations in the vibrational bands for different polymorphs. This is explained by the differences in the spatial distribution of BH4- anions within various structures. An example of the possible identification of products after the hydrogenation of MgB2, using NVS measurements, is presented. These results provide fundamental insights of benefit to researchers currently studying these promising hydrogen-storage materials.
Enhanced radiation tolerance of nanostructured metals is attributed to the high density of interfaces that can absorb radiationinduced defects. Here, cavity evolution mechanisms during cascade damage, helium implantation, and annealing of nanocrystalline nickel are characterized via in situ transmission electron microscopy (TEM). Films subjected to self-ion irradiation followed by helium implantation developed evenly distributed cavity structures, whereas films exposed in the reversed order developed cavities preferentially distributed along grain boundaries. Post-irradiation annealing and orientation mapping demonstrated uniform cavity growth in the nanocrystalline structure, and cavities spanning multiple grains. These mechanisms suggest limited ability to reduce swelling, despite the stability of the nanostructure.
The rapid release of energy from reactive multilayer foils can create extreme local temperature gradients near substrate materials. In order to fully exploit the potential of these materials, a better understanding of the interaction between the substrate or filler material and the foil is needed. Specifically, this work investigates how variations in local properties within the substrate (i.e. differences between properties in constituent phases) can affect heat transport into the substrate. This can affect the microstructural evolution observed within the substrate, which may affect the final joint properties. The effect of the initial substrate microstructure on microstructural evolution within the heat-affected zone is evaluated experimentally in two Sn-Zn alloys and numerical techniques are utilized to inform the analysis.
We know the rainbow color map is terrible, and it is emphatically reviled by the visualization community, yet its use continues to persist. Why do we continue to use a this perceptual encoding with so many known flaws? Instead of focusing on why we should not use rainbow colors, this position statement explores the rational for why we do pick these colors despite their flaws. Often the decision is influenced by a lack of knowledge, but even experts that know better sometimes choose poorly. A larger issue is the expedience that we have inadvertently made the rainbow color map become. Knowing why the rainbow color map is used will help us move away from it. Education is good, but clearly not sufficient. We gain traction by making sensible color alternatives more convenient. It is not feasible to force, a color map on users. Our goal is to supplant the rainbow color map as a common standard, and we w ill find that even those wedded to it will migrate away.
Performing experiments in the laboratory that mimic conditions in the field is challenging. In an attempt to understand hydraulic fracture in the field, and provide laboratory flow results for model verification, an effort to duplicate the typical fracture pattern for long horizontal wells has been made. The typical "disks on a string" fracture formation is caused by properly orienting the long horizontal well such that it is parallel to the minimum principal stress direction, then fracturing the rock. In order to replicate this feature in the laboratory with a traditional cylindrical specimen the test must be performed under extensile stress conditions and the specimen must have been cored parallel to bedding in order to avoid failure along a bedding plane, and replicate bedding orientation in the field. Testing has shown that it is possible to form failure features of this type in the laboratory. A novel method for jacketing is employed to allow fluid to flow out of the fracture and leave the specimen without risking the integrity of the jacket; this allows proppant to be injected into the fracture, simulating loss of fracturing fluids to the formation, and allowing a solid proppant pack to be developed.
Small silicon photonics micro-resonator modulators and filters hold the promise for multi-terabit per-second interconnects at energy consumptions well below 1 pJ/bit. To date, no products exist and little known commercial development is occurring using this technology. Why? In this talk, we review the many challenges that remain to be overcome in bringing this technology from the research labs to the field where they can overcome important commercial, industrial, and national security limitations of existing photonic technologies.
TlBr crystals have superior radiation detection properties; however, their properties degrade in the range of hours to weeks when an operating electrical field is applied. To account for this rapid degradation using the widely-accepted vacancy migration mechanism, the vacancy concentration must be orders of magnitude higher than any conventional estimates. The present work has incorporated a new analytical variable charge model in molecular dynamics (MD) simulations to examine the structural changes of materials under electrical fields. Our simulations indicate that dislocations in TlBr move under electrical fields. This discovery can lead to new understanding of TlBr aging mechanisms under external fields.
System-of-systems modeling has traditionally focused on physical systems rather than humans, but recent events have proved the necessity of considering the human in the loop. As technology becomes more complex and layered security continues to increase in importance, capturing humans and their interactions with technologies within the system-of-systems will be increasingly necessary. After an extensive job-task analysis, a novel type of system-ofsystems simulation model has been created to capture the human-technology interactions on an extra-small forward operating base to better understand performance, key security drivers, and the robustness of the base. In addition to the model, an innovative framework for using detection theory to calculate d’ for individual elements of the layered security system, and for the entire security system as a whole, is under development.
We report on the development of single-frequency VCSELs (vertical-cavity surface-emitting lasers) for sensing the position of a moving MEMS (micro-electro-mechanical system) object with resolution much less than 1nm. Position measurement is the basis of many different types of MEMS sensors, including accelerometers, gyroscopes, and pressure sensors. Typically, by switching from a traditional capacitive electronic readout to an interferometric optical readout, the resolution can be improved by an order of magnitude with a corresponding improvement in MEMS sensor performance. Because the VCSEL wavelength determines the scale of the position measurement, laser wavelength (frequency) stability is desirable. This paper discusses the impact of VCSEL amplitude and frequency noise on the position measurement.
When a severe nuclear power plant accident occurs, plant operators rely on Severe Accident Management Guidelines (SAMGs). However, current SAMGs are limited in scope and depth. The plant operators must work to mitigate the accident with limited experience and guidance for the situation. The SMART (Safely Managing Accidental Reactor Transients) procedures framework aims to fill the need for detailed guidance by creating a comprehensive probabilistic model, using a Dynamic Bayesian Network, to aid in the diagnosis of the reactor's state. In this paper, we explore the viability of the proposed SMART proceedures approach by building a prototype Bayesian network that allows tor the diagnosis of two types of accidents based on a comprehensive data set. We use Kullback-Leibler (K-L) divergence to gauge the relative importance of each of the plant's parameters. We compare accuracy and F-score measures across four different Bayesian networks: a baseline network that ignores observation variables, a network that ignores data from the observation variable with the highest K-L score, a network that ignores data from the variable with the lowest K-L score, and finally a network that includes all observation variable data. We conclude with an interpretation of these results for SMART procedures.
The present study results are focused on laboratory testing of surrogate materials representing Waste Isolation Pilot Plant (WIPP) waste. The surrogate wastes correspond to a conservative estimate of the containers and transuranic waste materials emplaced at the WIPP. Testing consists of hydrostatic, triaxial, and uniaxial tests performed on surrogate waste recipes based on those previously developed by Hansen et al. (1997). These recipes represent actual waste by weight percent of each constituent and total density. Testing was performed on full-scale and 1/4-scale containers. Axial, lateral, and volumetric strain and axial and lateral stress measurements were made. Unique testing techniques were developed during the course of the experimental program. The first involves the use of a spirometer or precision flow meter to measure sample volumetric strain under the various stress conditions. Since the manner in which the waste containers deformed when compressed was not even, the volumetric and axial strains were used to determine the lateral strains. The second technique involved the development of unique coating procedures that also acted as jackets during hydrostatic, triaxial, and full-scale uniaxial testing; 1/4-scale uniaxial tests were not coated but wrapped with clay to maintain an airtight seal for volumetric strain measurement. During all testing methods, the coatings allowed the use of either a spirometer or precision flow meter to estimate the amount of air driven from the container as it crushed down since the jacket adhered to the container and yet was flexible enough to remain airtight during deformation.
Analysts across national security domains are required to sift through large amounts of data to find and compile relevant information in a form that enables decision makers to take action in high-consequence scenarios. However, even the most experienced analysts are unable to be 100 % consistent and accurate based on the entire dataset, unbiased towards familiar documentation, and are unable to synthesize and process large amounts of information in a small amount of time. Sandia National Laboratories has attempted to solve this problem by developing an intelligent web crawler called Huntsman. Huntsman acts as a personal research assistant by browsing the internet or offline datasets in a way similar to the human search process, only much faster (millions of documents per day), by submitting queries to search engines and assessing the usefulness of page results through analysis of full-page content with a suite of text analytics. This paper will discuss Huntsman’s capability to both mirror and enhance human analysts using intelligent web crawling with analysts-in-the-loop. The goal is to demonstrate how weaknesses in human cognitive processing can be compensated for by fusing human processes with text analytics and web crawling systems, which ultimately reduces analysts’ cognitive burden and increases mission effectiveness.
In this study, eye tracking metrics and visual saliency maps were used to assess analysts' interactions with synthetic aperture radar (SAR) imagery. Participants with varying levels of experience with SAR imagery completed a target detection task while their eye movements and behavioral responses were recorded. The resulting gaze maps were compared with maps of bottom-up visual saliency and with maps of automatically detected image features The results showed striking differences between professional SAR analysis and novices in terms of how their visual search patterns related to the visual saliency of features in the imagery. They also revealed patterns that reflect the utility of various features in the images for the professional analysts These findings have implications for system design andfor the design and use of automatic feature classification algorithms.
We present here an example of how a large,multi-dimensional unstructured data set, namely aircraft trajectories over the United States, can be analyzed using relatively straightforward unsupervised learning techniques. We begin by adding a rough structure to the trajectory data using the notion of distance geometry. This provides a very generic structure to the data that allows it to be indexed as an n-dimensional vector. We then do a clustering based on the HDBSCAN algorithm to both group flights with similar shapes and find outliers that have a relatively unique shape. Next, we expand the notion of geometric features to more specialized features and demonstrate the power of these features to solve specific problems. Finally, we highlight not just the power of the technique but also the speed and simplicity of the implementation by demonstrating them on very large data sets.
A critical challenge in data science is conveying the meaning of data to human decision makers. While working with visualizations, decision makers are engaged in a visual search for information to support their reasoning process. As sensors proliferate and high performance computing becomes increasingly accessible, the volume of data decision makers must contend with is growing continuously and driving the need for more efficient and effective data visualizations. Consequently, researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles to assess the effectiveness of data visualizations. In this paper, we compare the performance of three different saliency models across a common set of data visualizations. This comparison establishes a performance baseline for assessment of new data visualization saliency models.
‘Big data’ is a phrase that has gained much traction recently. It has been defined as ‘a broad term for data sets so large or complex that traditional data processing applications are inadequate and there are challenges with analysis, searching and visualization’ [1]. Many domains struggle with providing experts accurate visualizations of massive data sets so that the experts can understand and make decisions about the data e.g., [2, 3, 4, 5]. Abductive reasoning is the process of forming a conclusion that best explains observed facts and this type of reasoning plays an important role in process and product engineering. Throughout a production lifecycle, engineers will test subsystems for critical functions and use the test results to diagnose and improve production processes. This paper describes a value-driven evaluation study [7] for expert analyst interactions with big data for a complex visual abductive reasoning task. Participants were asked to perform different tasks using a new tool, while eye tracking data of their interactions with the tool was collected. The participants were also asked to give their feedback and assessments regarding the usability of the tool. The results showed that the interactive nature of the new tool allowed the participants to gain new insights into their data sets, and all participants indicated that they would begin using the tool in its current state.
This report presents computational analyses that simulate the structural response of crude oil storage caverns at the U.S. Strategic Petroleum Reserve (SPR) West Hackberry site in Louisiana. These analyses evaluate the geomechanical behavior of the 22 caverns at the West Hackberry SPR site for the current condition of the caverns and their wellbores, the effect of the caverns on surface facilities, and for potential enlargement related to drawdowns. These analyses represent a significant upgrade in modeling capability, as the following enhancements have been developed: a 6-million-element finite element model of the entire West Hackberry dome; cavern finite element mesh geometries fit to sonar measurements of those caverns; the full implementation of the multi-mechanism deformation (M-D) creep model; and the use of historic wellhead pressures to analyze the past geomechanical behavior of the caverns. The analyses examined the overall performance of the West Hackberry site by evaluating surface subsidence, horizontal surface strains, and axial well strains. This report presents a case study of how large-scale computational analyses may be used in conjunction with site data to make recommendations for safe depressurization and repressurization of oil storage caverns with unusual geometries and close proximity, and for the determination of the number of available drawdowns for a particular cavern.
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
In an effort to increase thermal energy storage densities and turbine inlet temperatures in concentrating solar power (CSP) systems, focus on energy storage media has shifted from molten salts to solid particles. These solid particles are stable at temperatures far greater than that of molten salts, allowing the use of efficient high-temperature turbines in the power cycle. Furthermore, many of the solid particles under development store heat via reversible chemical reactions (thermochemical energy storage, TCES) in addition to the heat they store as sensible energy. The heat-storing reaction is often the thermal reduction of a metal oxide. If coupled to an Air-Brayton system, wherein air is used as the turbine working fluid, the subsequent extraction of both reaction and sensible heat, as well as the transfer of heat to the working fluid, can be accomplished in a direct-contact, counter-flow reoxidation reactor. However, there are several design challenges unique to such a reactor, such as maintaining requisite residence times for reactions to occur, particle conveying and mitigation of entrainment, and the balance of kinetics and heat transfer rates to achieve reactor outlet temperatures in excess of 1200 °C. In this paper, insights to addressing these challenges are offered, and design and operational tradeoffs that arise in this highlycoupled system are introduced and discussed.
Organizing multivariate time series data for presentation to an analyst is a challenging task. Typically, a dataset contains hundreds or thousands of datapoints, and each datapoint consists of dozens of time series measurements. Analysts are interested in how the datapoints are related, which measurements drive trends and/or produce clusters, and how the clusters are related to available metadata. In addition, interest in particular time series measurements will change depending on what the analyst is trying to understand about the dataset. Rather than providing a monolithic single use machine learning solution, we have developed a system that encourages analyst interaction. This system, Dial-A-Cluster (DAC), uses multidimensional scaling to provide a visualization of the datapoints depending on distance measures provided for each time series. The analyst can interactively adjust (dial) the relative influence of each time series to change the visualization (and resulting clusters). Additional computations are provided which optimize the visualization according to metadata of interest and rank time series measurements according to their influence on analyst selected clusters. The DAC system is a plug-in for Slycat (slycat.readthedocs.org), a framework which provides a web server, database, and Python infrastructure. The DAC web application allows an analyst to keep track of multiple datasets and interact with each as described above. It requires no installation, runs on any platform, and enables analyst collaboration. We anticipate an open source release in the near future.
Truly quantifying soot concentrations within turbulent flames is a difficult prospect. Laser extinction measurements are constrained by spatial resolution limitations and by uncertainty in the local soot extinction coefficient. Laser-induced incandescence (LII) measurements rely on calibration against extinction and thereby are plagued by uncertainty in the extinction coefficient. In addition, the LII measurements are subject to signal trapping in flames with significant soot concentrations and/or flame widths. In the study reported here, a turbulent ethylene non-premixed jet flame (jet exit Reynolds number of 20,000) is investigated by a combination of LII and full-flame HeNe laser (633 nm) extinction measurements. The LII measurements have been calibrated against extinction measurements in a laminar ethylene flame. An extinction coefficient previously measured in laminar ethylene flames is used as the basis of the calibration. The time-Averaged LII data in the turbulent flame has been corrected for signal trapping, which is shown to be significant in this flame, and then the line-of-sight extinction for a theoretical 633 nm light source has been calculated acrob the LII-determined soot concentration field. Comparison of the LII-based extinction with that actual measured along the flame centerline is favorable, showing an average deviation of approximately 10%. This lends credence to the measured values of soot concentrations in the flame and also gives a good indication of the level of uncertainty in the measured soot concentrations, subject to the additional uncertainty in the previously measured extinction coefficient, estimated to be ±15%.
As CMOS technology approaches the end of its scaling, oxide-based memristors have become one of the leading candidates for post-CMOS memory and logic devices. To facilitate the understanding of physical switching mechanisms and accelerate experimental development of memristors, we have developed a three-dimensional fully-coupled electrical and thermal transport model, which captures all the important processes that drive memristive switching and is applicable for simulating a wide range of memristors. The model is applied to simulate the RESET and SET switching in a 3D filamentary TaOx memristor. Extensive simulations show that the switching dynamics of the bipolar device is determined by thermally-activated field-dominant processes: with Joule heating, the raised temperature enables the movement of oxygen vacancies, and the field drift dominates the overall motion of vacancies. Simulated current-voltage hysteresis and device resistance profiles as a function of time and voltage during RESET and SET switching show good agreement with experimental measurement.
Electrical conductivity is key to the performance of thermal battery cathodes. In this work we present the effects of manufacturing and processing conditions on the electrical conductivity of Li/FeS2 thermal battery cathodes. We use finite element simulations to compute the conductivity of three-dimensional microcomputed tomography cathode microstructures and compare results to experimental impedance spectroscopy measurements. A regression analysis reveals a predictive relationship between composition, processing conditions, and electrical conductivity; a trend which is largely erased after thermally-induced deformation. The trend applies to both experimental and simulation results, although is not as apparent in simulations. This research is a step toward a more fundamental understanding of the effects of processing and composition on thermal battery component microstructure, properties, and performance.
Synthetic aperture radar (SAR) images contain a grainy pattern, called speckle, that is a consequence of a coherent imaging system. For fine resolution SAR images speckle can obscure subtle features and reduce visual appeal. Many speckle reduction methods result in a loss of image resolution and reduce visual appeal which can obscure subtle features. Another approach to maintain resolution while reducing speckle is to register and combine multiple images. For persistent surveillance applications it is more efficient for an airborne platform to fly circles around the particular area of interest. In these cases, it would be beneficial to combine multiple circle mode SAR images, however the image registration process is not so straightforward because the layover angle changes in each image. This paper develops a SAR image registration process for combining multiple circle mode SAR images to reduce speckle while preserving resolution. The registration first uses a feature matching algorithm for a coarse rotation and alignment, and then uses a fine registration and warp. Ku band SAR data from a circle mode SAR collection is used to show the effectiveness of the registration and enhanced visual appeal from multi-looking.
We present a detailed set of measurements from a piloted, sooting, turbulent C2H4-fueled jet flame. Hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (CARS) is used to monitor temperature and oxygen, while laser-induced incandescence (LII) is applied for imaging of the soot volume fraction in the challenging jet-flame environment at Reynolds number, Re = 20,000. A new dual-detection channel CARS instrument provides the enhanced dynamic range required in this highly intermittent and turbulent environment. LII measurements are made across a wide field of view requiring us to account for spatial variation in the soot-volume-fraction response of the instrument. Single-laser-shot results are used to illustrate the mean and rms statistics, as well as probability densities of all three measured quantities. LII data from the soot-growth region of the jet are used to benchmark the soot source term for one-dimensional turbulence (ODT) modeling of this turbulent flame. The ODT code is then used to predict temperature, oxygen and soot fluctuations within the soot oxidation region higher in the flame.
In this paper we report on a transmission-line model for calculating the shielding effectiveness of multiple-shield cables with arbitrary terminations. Since the shields are not perfect conductors and apertures in the shields permit external magnetic and electric fields to penetrate into the interior regions of the cable, we use this model to estimate the effects of the outer shield current and voltage (associated with the external excitation and boundary conditions associated with the external conductor) on the inner conductor current and voltage. It is commonly believed that increasing the number of shields of a cable will improve the shielding performance. However, this is not always the case, and a cable with multiple shields may perform similar to or in some cases worse than a cable with a single shield. We want to shed more light on these situations, which represent the main focus of this paper.
For film cooling of combustor linings and turbine blades, it is critical to be able to accurately model jets-in-crossflow. Current Reynolds Averaged Navier Stokes (RANS) models often give unsatisfactory predictions in these flows, due in large part to model form error, which cannot be resolved through calibration or tuning of model coefficients. The Boussinesq hypothesis, upon which most two-equation RANS models rely, posits the existence of a non-negative scalar eddy viscosity, which gives a linear relation between the Reynolds stresses and the mean strain rate. This model is rigorously analyzed in the context of a jet-in-crossflow using the high fidelity Large Eddy Simulation data of Ruiz et al. (2015), as well as RANS k-e results for the same flow. It is shown that the RANS models fail to accurately represent the Reynolds stress anisotropy in the injection hole, along the wall, and on the lee side of the jet. Machine learning methods are developed to provide improved predictions of the Reynolds stress anisotropy in this flow.
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
Flux distributions from solar field collectors are typically evaluated using a beam characterization system, which consists of a digital camera with neutral density filters, flux gauge or calorimeter, and water-cooled Lambertian target panel. The pixels in camera image of the flux distribution are scaled by the flux peak value measured with the flux gauge or the total power value measured with the calorimeter. An alternative method, called PHLUX developed at Sandia National Laboratories, can serve the same purpose using a digital camera but without auxiliary instrumentation. The only additional information required besides the digital images recorded from the camera are the direct normal irradiance, an image of the sun using the same camera, and the reflectivity of the receiver or target panel surface. The PHLUX method was evaluated using two digital cameras (Nikon D90 and D3300) at different flux levels on a target panel. The performances of the two cameras were compared to each other and to measurements from a Kendall radiometer. For consistency in comparison of the two cameras, the same focal length lenses and same number of neutral density filters were used. Other camera settings (e.g., shutter speed, f-stop, etc.) were set based on the aperture size and performance of the cameras. The Nikon D3300 has twice the number of pixels as the D90. D3300 provided higher resolution, however, due to the smaller pixel sizes the images were noisier, and the D90 with larger pixels had better response to low light levels. The noise in the D3300, if not corrected, could result in gross overestimation of the irradiance calculations. After corrections to the D3300 flux images, the PHLUX results from the two cameras showed they agreed to within 8% for a peak flux level of 1000 suns on the target, and less than 10% error in the peak flux when compared to the Kendall radiometer.
Channeled spectropolarimeters (CSP) measure the polarization state of light as a function of wavelength. Conventional Fourier reconstruction suffers from noise, assumes the channels are band-limited, and requires uniformly spaced samples. To address these problems, we propose an iterative reconstruction algorithm. We develop a mathematical model of CSP measurements and minimize a cost function based on this model. We simulate a measured spectrum using example Stokes parameters, from which we compare conventional Fourier reconstruction and iterative reconstruction. Importantly, our iterative approach can reconstruct signals that contain more bandwidth, an advancement over Fourier reconstruction. Our results also show that iterative reconstruction mitigates noise effects, processes non-uniformly spaced samples without interpolation, and more faithfully recovers the ground truth Stokes parameters. This work offers a significant improvement to Fourier reconstruction for channeled spectropolarimetry.
ASME 2016 Heat Transfer Summer Conference, HT 2016, collocated with the ASME 2016 Fluids Engineering Division Summer Meeting and the ASME 2016 14th International Conference on Nanochannels, Microchannels, and Minichannels
Radiation heat transfer is an important phenomenon in many physical systems of practical interest. When participating media is important, the radiative transfer equation (RTE) must be solved for the radiative intensity as a function of location, time, direction, and wavelength. In many heat transfer applications, a quasi-steady assumption is valid. The dependence on wavelength is often treated through a weighted sum of gray gases type approach. The discrete ordinates method is the most common method for approximating the angular dependence. In the discrete ordinates method, the intensity is solved exactly for a finite number of discrete directions, and integrals over the angular space are accomplished through a quadrature rule. In this work, a projection-based model reduction approach is applied to the discrete ordinates method. A small number or ordinate directions are used to construct the reduced basis. The reduced model is then queried at the quadrature points for a high order quadrature in order to inexpensively approximate this highly accurate solution. This results in a much more accurate solution than can be achieved by the low-order quadrature alone. One-, two-, and three-dimensional test problems are presented.
The evolution of exquisitely sensitive Synthetic Aperture Radar (SAR) systems is positioning this technology for use in time-critical environments, such as search-and-rescue missions and improvised explosive device (IED) detection. SAR systems should be playing a keystone role in the United States' Intelligence, Surveillance, and Reconnaissance activities. Yet many in the SAR community see missed opportunities for incorporating SAR into existing remote sensing data collection and analysis challenges. Drawing on several years' of field research with SAR engineering and operational teams, this paper examines the human and organizational factors that mitigate against the adoption and use of SAR for tactical ISR and operational support. We suggest that SAR has a design problem, and that context-sensitive, human and organizational design frameworks are required if the community is to realize SAR's tactical potential.
We investigate a novel application of Fŕechet derivatives for time-lapse mapping of deep, electrically-enhanced fracture systems with a borehole to surface DC resistivity array. The simulations are evaluated for a cased horizontal wellbore embedded in a homogeneous halfspace, where measurements are evaluated near, mid-range, and far from the well head. We show that, in all cases, measurements are sensitive to perturbations centered on the borehole axis and that the sensitivity volume decreases as a function of increased measurement offset from the well head. The sensitivity analysis also illustrates that careful consideration must be taken when developing an electrical survey design for these scenarios. Specifically, we show that positive perturbations in earth conductivity near the wellbore can manifest as both positive and negative measurement perturbations, depending on where the measurement is taken. Furthermore, we show that the transition between the regions along the wellbore of positive and negative contribution results in a "pinch point", representing a region along the wellbore where a given surface measurement is blind to any changes or enhancement of electrical conductivity.
We present a general technique to solve Partial Differential Equations, called robust stencils, which make them tolerant to soft faults, i.e. bit flips arising in memory or CPU calculations. We show how it can be applied to a two-dimensional Lax-Wendroff solver. The resulting 2D robust stencils are derived using an orthogonal application of their 1D counterparts. Combinations of 3 to 5 base stencils can then be created. We describe how these are then implemented in a parallel advection solver. Various robust stencil combinations are explored, representing tradeoff between performance and robustness. The results indicate that the 3-stencil robust combinations are slightly faster on large parallel workloads than Triple Modular Redundancy (TMR). They also have one third of the memory footprint. We expect the improvement to be significant if suitable optimizations are performed. Because faults are avoided each time new points are computed, the proposed stencils are also comparably robust to faults as TMR for a large range of error rates. The technique can be generalized to 3D (or higher dimensions) with similar benefits.
Proceedings of the 6th International Conference on Recrystallization and Grain Growth, ReX and GG 2016
Hattar, Khalid; Miller, Bryan; Robertson, Ian M.; Kacher, Josh
Nanostructured metal thin films have been shown to have unique thermal, mechanical, and electrical properties when the internal structure can be maintained. However, this far-from-equilibrium structure has been shown in many cases to be unstable at elevated temperatures. This work investigates the role of surface ledges, large nickel inclusions, electron beam exposure and film thickness on the evolution of high purity, pulsed-laser deposited, free-standing, nickel films via in situ transmission electron microscopy annealing. Grain growth appeared enhanced in a limited temperature range near surface ledges present in the film, but was not affected by large nickel inclusions. In addition, extended exposure to the electron beam resulted in abnormal grain growth. This was hypothesized to be a result of enhanced nickel oxide growth on the surfaces. Finally, increasing film thickness was observed to accelerate the onset of abnormal grain growth and increased the size and number of larger grains. These observations should provide warning that the initial and dynamic surface present in thin films should be taken under consideration during any annealing study, as it may significantly impact the final crystalline structure.
Fracture and fragmentation are extremely nonlinear multiscale processes in which microscale damage mechanisms emerge at the macroscale as new fracture surfaces. Numerous numerical methods have been developed for simulating fracture initiation, propagation, and coalescence. Here, we present a computational approach for modeling pervasive fracture in quasi-brittle materials based on random close-packed Voronoi tessellations. Each Voronoi cell is formulated as a polyhedral finite element containing an arbitrary number of vertices and faces. Fracture surfaces are allowed to nucleate only at the intercell faces. Cohesive softening tractions are applied to new fracture surfaces in order to model the energy dissipated during fracture growth. The randomly seeded Voronoi cells provide a regularized discrete random network for representing fracture surfaces. The potential crack paths within the random network are viewed as instances of realizable crack paths within the continuum material. Mesh convergence of fracture simulations is viewed in a weak, or distributional, sense. The explicit facet representation of fractures within this approach is advantageous for modeling contact on new fracture surfaces and fluid flow within the evolving fracture network. Applications of interest include fracture and fragmentation in quasi-brittle materials and geomechanical applications such as hydraulic fracturing, engineered geothermal systems, compressed-air energy storage, and carbon sequestration.
This paper demonstrates that another class of three-dimensional integrated circuits (3D-ICs) exists, distinct from through silicon via centric and monolithic 3D-ICs. Furthermore, it is possible to create devices that are 3D at the device level (i.e. with active channels oriented in each of the three coordinate axes), by performing standard CMOS fabrication operations at an angle with respect to the wafer surface into high aspect ratio silicon substrates using membrane projection lithography (MPL). MPL requires only minimal fixturing changes to standard CMOS equipment, and no change to current state-of-the-art lithography. Eliminating the constraint of 2D planar device architecture enables a wide range of new interconnect topologies which could help reduce interconnect resistance/capacitance, and potentially improve performance.
A 4-color imaging pyrometer was developed to investigate the thermal behavior of laser-based metal processes, specifically laser welding and laser additive manufacturing of stainless steel. The new instrument, coined a 2x pyrometer, consists of four, high-sensitivity silicon CMOS cameras configured as two independent 2-color pyrometers combined in a common hardware assembly. This coupling of pyrometers permitted low and high temperature regions to be targeted within the silicon response curve, thereby broadening the useable temperature range of the instrument. Also, by utilizing the high dynamic range features of the CMOS cameras, the response gap between the two wavelength bands can be bridged. Together these hardware and software enhancements are predicted to expand the real-time (60 fps) temperature response of the 2x pyrometer from 600 °C to 3500 °C. Initial results from a calibrated tungsten lamp confirm this increased response, thus making it attractive for measuring absolute temperatures of steel forming processes.
This paper presents the findings of using convolutional neural networks (CNNs) to classify human activity from micro-Doppler features. An emphasis on activities involving potential security threats such as holding a gun are explored. An automotive 24 GHz radar on chip was used to collect the data and a CNN (normally applied to image classification) was trained on the resulting spectrograms. The CNN achieves an error rate of 1.65 % on classifying running vs. walking, 17.3 % error on armed walking vs. unarmed walking, and 22 % on classifying six different actions.
This contribution is the second part of three papers on Adaptive Multigrid Methods for the eXtended Fluid-Structure Interaction (eXFSI) Problem, where we introduce a monolithic variational formulation and solution techniques. To the best of our knowledge, such a model is new in the literature. This model is used to design an on-line structural health monitoring (SHM) system in order to determine the coupled acoustic and elastic wave propagation in moving domains and optimum locations for SHM sensors. In a monolithic nonlinear fluid-structure interaction (FSI), the fluid and structure models are formulated in different coordinate systems. This makes the FSI setup of a common variational description difficult and challenging. This article presents the state-of-the-art in the finite element approximation of FSI problem based on monolithic variational formulation in the well-established arbitrary Lagrangian Eulerian (ALE) framework. This research focuses on the newly developed mathematical model of a new FSI problem, which is referred to as extended Fluid-Structure Interaction (eXFSI) problem in the ALE framework. The eXFSI is a strongly coupled problem of typical FSI with a coupled wave propagation problem on the fluid-solid interface (WpFSI). The WpFSI is a strongly coupled problem of acoustic and elastic wave equations, where wave propagation problems automatically adopts the boundary conditions from the FSI problem at each time step. The ALE approach provides a simple but powerful procedure to couple solid deformations with fluid flows by a monolithic solution algorithm. In such a setting, the fluid problems are transformed to a fixed reference configuration by the ALE mapping. The goal of this work is the development of concepts for the efficient numerical solution of eXFSI problem, the analysis of various fluid-solid mesh motion techniques and comparison of different second-order time-stepping schemes. This work consists of the investigation of different time stepping scheme formulations for a nonlinear FSI problem coupling the acoustic/elastic wave propagation on the fluid-structure interface. Temporal discretization is based on finite differences and is formulated as a one step-θ scheme, from which we can consider the following particular cases: the implicit Euler, Crank-Nicolson, shifted Crank-Nicolson and the Fractional-Step-θ schemes. The nonlinear problem is solved with a Newton-like method where the discretization is done with a Galerkin finite element scheme. The implementation is accomplished via the software library package DOPELIB based on the deal. II finite element library for the computation of different eXFSI configurations.
Fiber Bragg gratings (FBGs) are well-suited for embedded sensing of interfacial phenomena in materials systems, due to the sensitivity of their spectral response to locally non-uniform strain fields. Over the last 15 years, FBGs have been successfully employed to sense delamination at interfaces, with a clear emphasis on planar events induced by transverse cracks in fiber-reinforced plastic laminates. We have built upon this work by utilizing FBGs to detect circular delamination events at the interface between epoxy films and alumina substrates. Two different delamination processes are examined, based on stress relief induced by indentation of the epoxy film or by cooling to low temperature. We have characterized the spectral response pre-and post-delamination for both simple and chirped FBGs as a function of delamination size. We show that delamination is readily detected by the evolution of a non-uniform strain distribution along the fiber axis that persists after the stressing condition is removed. These residual strain distributions differ substantially between the delamination processes, with indentation and cooling producing predominantly tensile and compressive strain, respectively, that are well-captured by Gaussian profiles. More importantly, we observe a strong correlation between spectrally-derived measurements, such as spectral widths, and delamination size. Our results further highlight the unique capabilities of FBGs as diagnostic tools for sensing delamination in materials systems.
A 4-color imaging pyrometer was developed to investigate the thermal behavior of laser-based metal processes, specifically laser welding and laser additive manufacturing of stainless steel. The new instrument, coined a 2x pyrometer, consists of four, high-sensitivity silicon CMOS cameras configured as two independent 2-color pyrometers combined in a common hardware assembly. This coupling of pyrometers permitted low and high temperature regions to be targeted within the silicon response curve, thereby broadening the useable temperature range of the instrument. Also, by utilizing the high dynamic range features of the CMOS cameras, the response gap between the two wavelength bands can be bridged. Together these hardware and software enhancements are predicted to expand the real-time (60 fps) temperature response of the 2x pyrometer from 600 °C to 3500 °C. Initial results from a calibrated tungsten lamp confirm this increased response, thus making it attractive for measuring absolute temperatures of steel forming processes.
We present experimental and simulation results for a laboratory-based forward-scattering environment, where 1 μm diameter polystyrene spheres are suspended in water to model the optical scattering properties of fog. Circular polarization maintains its degree of polarization better than linear polarization as the optical thickness of the scattering environment increases. Both simulation and experiment quantify circular polarization's superior persistence, compared to that of linear polarization, and show that it is much less affected by variations in the field of view and collection area of the optical system. Our experimental environment's lateral extent was physically finite, causing a significant difference between measured and simulated degree of polarization values for incident linearly polarized light, but not for circularly polarized light. Through simulation we demonstrate that circular polarization is less susceptible to the finite environmental extent as well as the collection optic's limiting configuration.
Proceedings of SPIE - The International Society for Optical Engineering
Klem, John F.; Lotfi, Hossein; Li, Lu; Lei, Lin; Ye, Hao; Rassel, Sm S.; Jiang, Yuchao; Yang, Rui Q.; Mishima, Tetsuya D.; Santos, Michael B.; Johnson, Matthew B.; Gupta, James A.
We investigate high-temperature and high-frequency operation of interband cascade infrared photodetectors (ICIPs)-two critical properties. Short-wavelength ICIPs with a cutoff wavelength of 2.9 μm had Johnson-noise limited detectivity of 5.8×109 cmHz1/2/W at 300 K, comparable to the commercial Hg1-xCdxTe photodetectors of similar wavelengths. A simple but effective method to estimate the minority carrier diffusion length in short-wavelength ICIPs is introduced. Using this approach, the diffusion length was estimated to be significantly shorter than 1 μm at high temperatures, indicating the importance of a multiple-stage photodetector (e.g., ICIPs) at high temperatures. Recent investigations on the high-frequency operation of mid-wavelength ICIPs (λc=4.3 μm) are discussed. These photodetectors had 3-dB bandwidths up to 1.3 GHz with detectivities exceeding 1x109 cmHz1/2/W at room temperature. These results validate the ability of ICIPs to achieve high bandwidths with large sensitivity and demonstrate the great potential for applications such as: heterodyne detection, and free-space optical communication.
The IRDFF cross section library provides the highest fidelity cross section characterization and is the recommended data library to be used for dosimetry in support of reactor pressure vessel surveillance programs. In order to support this critical application, quantified validation evidence is required for the cross section library. Results are reported here on the use of various advanced approaches to uncertainty quantification using metrics relevant to spectrum characterization applications. The use of a quantified least squares approach, combining a consistent treatment of uncertainty from the spectral characterizations, the dosimetry cross sections, and measured activation products, is identified as one of the most sensitive metrics by which to report validation evidence. Using this metric the status of the validation of the IRDFF library was investigated. This analysis began with a consideration of the best characterized 252Cf spontaneous fission standard neutron benchmark field. Good validation evidence is found for 39 of the 79 IRDFF reactions. The 235U thermal fission reference neutron field was then investigated, and found to yield good validation evidence for an additional 10 of the IRDFF reactions. Extending the analysis further to include four different reactor-based reference neutron benchmark fields, ranging from fast burst reactors to well-moderated pool-type reactors, yielded good validation evidence for an additional 6 IRDFF reactions. In total, evidence is reported here for 55 of the 79 reactions in the IRDFF library.
This work examines the variability of predicted responses when multiple stress-strain curves (reflecting variability from replicate material tests) are propagated through a transient dynamics finite element model of a ductile steel can being slowly crushed. An elastic-plastic constitutive model is employed in the large-deformation simulations. The present work assigns the same material to all the can parts: lids, walls, and weld. Time histories of 18 response quantities of interest (including displacements, stresses, strains, and calculated measures of material damage) at several locations on the can and various points in time are monitored in the simulations. Each response quantity's behavior varies according to the particular stressstrain curves used for the materials in the model. We estimate response variability due to variability of the input material curves. When only a few stress-strain curves are available from material testing, response variance will usually be significantly underestimated. This is undesirable for many engineering purposes. This paper describes the can-crush model and simulations used to evaluate a simple classical statistical method, Tolerance Intervals (TIs), for effectively compensating for sparse stress-strain curve data in the can-crush problem. Using the simulation results presented here, the accuracy and reliability of the TI method are being evaluated on the highly nonlinear inputto- output response mappings and non-standard response distributions in the can-crush UQ problem.
The influence of compressibility on the shear layer over a rectangular cavity of variable width has been studied at a freestream Mach number range of 0.6 to 2.5 using particle image velocimetry data in the streamwise center plane. As the Mach number increases, the vertical component of the turbulence intensity diminishes modestly in the widest cavity, but the two narrower cavities show a more substantial drop in all three components as well as the turbulent shear stress. This contrasts with canonical free shear layers, which show significant reductions in only the vertical component and the turbulent shear stress due to compressibility. The vorticity thickness of the cavity shear layer grows rapidly as it initially develops, then transitions to a slower growth rate once its instability saturates. When normalized by their estimated incompressible values, the growth rates prior to saturation display the classic compressibility effect of suppression as the convective Mach number rises, in excellent agreement with comparable free shear layer data. The specific trend of the reduction in growth rate due to compressibility is modified by the cavity width.
Performing experiments in the laboratory that mimic conditions in the field is challenging. In an attempt to understand hydraulic fracture in the field, and provide laboratory flow results for model verification, an effort to duplicate the typical fracture pattern for long horizontal wells has been made. The typical "disks on a string" fracture formation is caused by properly orienting the long horizontal well such that it is parallel to the minimum principal stress direction, then fracturing the rock. In order to replicate this feature in the laboratory with a traditional cylindrical specimen the test must be performed under extensile stress conditions and the specimen must have been cored parallel to bedding in order to avoid failure along a bedding plane, and replicate bedding orientation in the field. Testing has shown that it is possible to form failure features of this type in the laboratory. A novel method for jacketing is employed to allow fluid to flow out of the fracture and leave the specimen without risking the integrity of the jacket; this allows proppant to be injected into the fracture, simulating loss of fracturing fluids to the formation, and allowing a solid proppant pack to be developed.
Ward, Daniel R.; Kim, Dohun; Savage, Donald E.; Lagally, Max G.; Foote, Ryan H.; Friesen, Mark; Coppersmith, Susan N.; Eriksson, Mark A.
Universal quantum computation requires high-fidelity single-qubit rotations and controlled two-qubit gates. Along with high-fidelity single-qubit gates, strong efforts have been made in developing robust two-qubit logic gates in electrically gated quantum dot systems to realise a compact and nanofabrication-compatible architecture. Here we perform measurements of state-conditional coherent oscillations of a charge qubit. Using a quadruple quantum dot formed in a Si/SiGe heterostructure, we show the first demonstration of coherent two-axis control of a double quantum dot charge qubit in undoped Si/SiGe, performing Larmor and Ramsey oscillation measurements. We extract the strength of the capacitive coupling between a pair of double quantum dots by measuring the detuning energy shift (≈75 μeV) of one double dot depending on the excess charge configuration of the other double dot. We further demonstrate that the strong capacitive coupling allows fast, state-conditional Landau–Zener–Stückelberg oscillations with a conditional π phase flip time of about 80 ps, showing a promising pathway towards multi-qubit entanglement and control in semiconductor quantum dots.
Remote detection of a surface-bound chemical relies on the recognition of a pattern, or "signature," that is distinct from the background. Such signatures are a function of a chemical's fundamental optical properties, but also depend upon its specific morphology. Importantly, the same chemical can exhibit vastly different signatures depending on the size of particles composing the deposit. We present a parameterized model to account for such morphological effects on surface-deposited chemical signatures. This model leverages computational tools developed within the planetary and atmospheric science communities, beginning with T-matrix and ray-tracing approaches for evaluating the scattering and extinction properties of individual particles based on their size and shape, and the complex refractive index of the material itself. These individual-particle properties then serve as input to the Ambartsumian invariant imbedding solution for the reflectance of a particulate surface composed of these particles. The inputs to the model include parameters associated with a functionalized form of the particle size distribution (PSD) as well as parameters associated with the particle packing density and surface roughness. The model is numerically inverted via Sandia's Dakota package, optimizing agreement between modeled and measured reflectance spectra, which we demonstrate on data acquired on five size-selected silica powders over the 4-16 μm wavelength range. Agreements between modeled and measured reflectance spectra are assessed, while the optimized PSDs resulting from the spectral fitting are then compared to PSD data acquired from independent particle size measurements.
We have developed high damage threshold filters to modify the spatial profile of a high energy laser beam. The filters are formed by laser ablation of a transmissive window. The ablation sites constitute scattering centers which can be filtered in a subsequent spatial filter. By creating the filters in dielectric materials, we see an increased laser-induced damage threshold from previous filters created using 'metal on glass' lithography.
The Z-backlighter laser facility primarily consists of two high energy, high-power laser systems. Z-Beamlet laser (ZBL) (Rambo et al., Appl. Opt. 44, 2421 (2005)) is a multi-kJ-class, nanosecond laser operating at 1054 nm which is frequency doubled to 527 nm in order to provide x-ray backlighting of high energy density events on the Z-machine. Z-Petawatt (ZPW) (Schwarz et al., J. Phys.: Conf. Ser. 112, 032020 (2008)) is a petawatt-class system operating at 1054 nm delivering up to 500 J in 500 fs for backlighting and various short-pulse laser experiments (see also Figure 10 for a facility overview). With the development of the magnetized liner inertial fusion (MagLIF) concept on the Z-machine, the primary backlighting missions of ZBL and ZPW have been adjusted accordingly. As a result, we have focused our recent efforts on increasing the output energy of ZBL from 2 to 4 kJ at 527 nm by modifying the fiber front end to now include extra bandwidth (for stimulated Brillouin scattering suppression). The MagLIF concept requires a well-defined/behaved beam for interaction with the pressurized fuel. Hence we have made great efforts to implement an adaptive optics system on ZBL and have explored the use of phase plates. We are also exploring concepts to use ZPW as a backlighter for ZBL driven MagLIF experiments. Alternatively, ZPW could be used as an additional fusion fuel pre-heater or as a temporally flexible high energy pre-pulse. All of these concepts require the ability to operate the ZPW in a nanosecond long-pulse mode, in which the beam can co-propagate with ZBL. Some of the proposed modifications are complete and most of them are well on their way.
Low temperature cofired ceramic (LTCC) technology has proven itself in military/space electronics, wireless communication, microsystems, medical and automotive electronics, and sensors. The use of LTCC for high frequency applications is appealing due to its low losses, design flexibility and packaging and integration capability. The LTCC thick film process is summarized including some unconventional process steps such as feature machining in the unfired state and thin film definition of outer layer conductors. The LTCC thick film process was characterized to optimize process yields by focusing on these factors: 1) Print location, 2) Print thickness, 3) Drying of tapes and panels, 4) Shrinkage upon firing, and 5) Via topography. Statistical methods were used to analyze critical process and product characteristics in the determination towards that optimization goal.
We present a resilient domain-decomposition preconditioner for partial differential equations (PDEs). The algorithm reformulates the PDE as a sampling problem, followed by a solution update through data manipulation that is resilient to both soft and hard faults. We discuss an implementation based on a server-client model where all state information is held by the servers, while clients are designed solely as computational units. Servers are assumed to be “sandboxed”, while no assumption is made on the reliability of the clients. We explore the scalability of the algorithm up to ∼12k cores, build an SST/macro skeleton to extrapolate to∼50k cores, and show the resilience under simulated hard and soft faults for a 2D linear Poisson equation.
Over 25 years, scientists and engineers designed engineered features to complement attributes of the natural barrier of volcanic tuff at Yucca Mountain in southern Nevada such that a proposed repository in the unsaturated zone would safely isolate spent nuclear fuel and highlevel radioactive waste over 106 years. Initially in 1983, an engineered barrier design applicable to several geologic media was used. With the Congressional direction to characterize Yucca Mountain, the engineered design gradually adapted to conditions in unsaturated tuff in the 1990s. The repository switched from floor emplacement of waste in small, single-walled stainless steel canisters to in-drift emplacement in large, double-layered containers. By 2000, the outer layer was high-nickel alloy to resist corrosion and the inner layer was stainless steel for strength. To avoid localized corrosion during the ∼1000-yr thermal period, titanium drip shields were also added above the containers. By 2008, a modular design of the repository was used for flexibility. In general, flexibility in accommodating various waste forms has been an intended attribute of geologic disposal system designs, rather than tuning the disposal system to specific characteristics of waste durability. The degradation rate of the radioactive waste matrix was an important parameter of the source-term in early modeling analysis. However, by the mid 1990s, analyses used fairly rapid degradation rates within the oxygenated environment of the unsaturated zone. Other components of the multiple barrier disposal system compensated for high degradation rates.
Sandia engineers use the Temporal Logic of Actions (TLA) early in the design process for digital systems where safety considerations are critical. TLA allows us to easily build models of interactive systems and prove (in the mathematical sense) that those models can never violate safety requirements, all in a single formal language. TLA models can also be refined, that is, extended by adding details in a carefully prescribed way, such that the additional details do not break the original model. Our experience suggests that engineers using refinement can build, maintain, and prove safety for designs that are significantly more complex than they otherwise could. We illustrate the way in which we have used TLA, including refinement, with a case study drawn from a real safety-critical system. This case exposes a need for refinement by composition, which is not currently provided by TLA. We have extended TLA to support this kind of refinement by building a specialized version of it in the Coq theorem prover. Taking advantage of Coq’s features, our version of TLA exhibits other benefits over stock TLA: we can prove certain difficult kinds of safety properties using mathematical induction, and we can certify the correctness of our proofs.
Volumetric measurements of the flow within four open cavities were made using stereoscopic particle image velocimetry at a freestream Mach number of 0.8. The cavities nominally had a length-to-diameter ratio, L/D = 7, along with an aspect ratio, b/L = 0.5. The three complex cavity geometries were selected to model features representative of real aircraft bays and compare them to a finite-span rectangular cavity: these included features such as leading edge and side ramps, a scooped leading edge ramp, and a jagged leading edge. Flow is drawn into the cavity at the edges due to a lack of pressure recovery within the cavity. Due to the influence of the leading edge shape and side edges, three-dimensionalities are formed within the cavities that influence the development of the Rossiter tones. In the rectangular cavity, these three-dimensionalities lead to the formation of a set of counter-rotating streamwise-oriented vortices, which create a nearly-sinusoidal, spanwise waviness within its mixing layer. The addition of leading edge and side ramps disrupt the formation of these vortical structures and displace the mixing layer vertically, reducing Rossiter modal amplitudes. The leading edge ramp accelerates the oncoming flow, resulting in a shift in the Rossiter frequencies. A scooped leading edge reintroduced streamwise vorticity, increasing cavity turbulence, whereas an overhanging jagged leading edge reduced cavity velocity fluctuations while increasing the strength of the second Rossiter mode.
Time-resolved PIV has been accomplished in three high-speed flows using a pulse-burst laser: a supersonic jet exhausting into a transonic crossflow, a transonic flow over a rectangular cavity, and a shock-induced transient onset to cylinder vortex shedding. Temporal supersampling converts spatial information into temporal information by employing Taylor’s frozen turbulence hypothesis along local streamlines, providing frequency content until about 150 kHz where the noise floor is reached. The spectra consistently reveal two regions exhibiting power-law dependence describing the turbulent decay. One is the well-known inertial subrange with a slope of-5/3 at high frequencies. The other displays a-1 power-law dependence for as much as a decade of mid-range frequencies lying between the inertial subrange and the integral length scale. The evidence for the-1 power law is most convincing in the jet-in-crossflow experiment, which is dominated by in-plane convection and the vector spatial resolution does not impose an additional frequency constraint. Data from the transonic cavity flow that are least likely to be subject to attenuation due to limited spatial resolution or out-of-plane motion exhibit the strongest agreement with the-1 and-5/3 power laws. The cylinder wake data also appear to show the-1 regime and the inertial subrange in the near-wake, but farther downstream the frozen-turbulence assumption may deteriorate as large-scale vortices interact with one another in the von Kármán vortex street.
Best-estimate fuel performance codes such as BISON currently under development at the Idaho National Laboratory, utilize empirical and mechanistic lower-length-scale informed correlations to predict fuel behavior under normal operating and accident reactor conditions. Traditionally, best-estimate results are presented using the correlations with no quantification of the uncertainty in the output metrics of interest. However, there are associated uncertainties in the input parameters and correlations used to determine the behavior of the fuel and cladding under irradiation. Therefore, it is important to perform uncertainty quantification and include confidence bounds on the output metrics that take into account the uncertainties in the inputs. In addition, sensitivity analyses can be performed to determine which input parameters have the greatest influence on the outputs. In this paper we couple the BISON fuel performance code to the DAKOTA uncertainty analysis software to analyze a representative fuel performance problem. The case studied in this paper is based upon rod 1 from the IFA-432 integral experiment performed at the Halden Reactor in Norway. The rodlet is representative of a BWR fuel rod. The input parameters uncertainties are broken into three separate categories including boundary condition uncertainties (e.g., power, coolant flow rate), manufacturing uncertainties (e.g., pellet diameter, cladding thickness), and model uncertainties (e.g., fuel thermal conductivity, fuel swelling). Utilizing DAKOTA, a variety of statistical analysis techniques are applied to quantify the uncertainty and sensitivity of the output metrics of interest. Specifically, we demonstrate the use of sampling methods, polynomial chaos expansions, surrogate models, and variance-based decomposition. The output metrics investigated in this study are the fuel centerline temperature, cladding surface temperature, fission gas released, and fuel rod diameter. The results highlight the importance of quantifying the uncertainty and sensitivity in fuel performance modeling predictions and the need for additional research into improving the material models that are currently available.
Here, we present the draft genome sequence of Burkholderia pseudomallei PHLS 6, a virulent clinical strain isolated from a melioidosis patient in Bangladesh in 1960. The draft genome consists of 39 contigs and is 7,322,181 bp long.
Time-resolved PIV has been accomplished in three high-speed flows using a pulse-burst laser: a supersonic jet exhausting into a transonic crossflow, a transonic flow over a rectangular cavity, and a shock-induced transient onset to cylinder vortex shedding. Temporal supersampling converts spatial information into temporal information by employing Taylor’s frozen turbulence hypothesis along local streamlines, providing frequency content until about 150 kHz where the noise floor is reached. The spectra consistently reveal two regions exhibiting power-law dependence describing the turbulent decay. One is the well-known inertial subrange with a slope of-5/3 at high frequencies. The other displays a-1 power-law dependence for as much as a decade of mid-range frequencies lying between the inertial subrange and the integral length scale. The evidence for the-1 power law is most convincing in the jet-in-crossflow experiment, which is dominated by in-plane convection and the vector spatial resolution does not impose an additional frequency constraint. Data from the transonic cavity flow that are least likely to be subject to attenuation due to limited spatial resolution or out-of-plane motion exhibit the strongest agreement with the-1 and-5/3 power laws. The cylinder wake data also appear to show the-1 regime and the inertial subrange in the near-wake, but farther downstream the frozen-turbulence assumption may deteriorate as large-scale vortices interact with one another in the von Kármán vortex street.
In previous studies, complex cavity geometries showed higher amplitude and more three- dimensional pressure fields than simple rectangular cavities. However, those studies relied on twenty point measurements within the cavity. To further understand the development of the pressure field within complex bays, high-frequency pressure-sensitive paint (PSP) was applied to the floor of an L/D = 7 complex cavity at Mach 0.9; unsteady pressure measurements were obtained at 10 kHz. Power spectra of the PSP measurements have a spatial distribution at each cavity resonance frequency with an oscillatory pattern; additional maxima and minima appear as the mode number is increased. This behavior was tied to the superposition of a downstream propagating shear-layer disturbance and an upstream propagating acoustic wave of different amplitudes, consistent with the classical Rossiter model. Complex geometries added spanwise asymmetries to the spatial pattern and amplified specific modes. These spatially dependent features of the pressure field might be missed by point measurements of the pressure field.
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
Thermochemical energy storage (TCES) offers the potential for greatly increased storage density relative to sensible-only energy storage. Moreover, heat may be stored indefinitely in the form of chemical bonds via TCES, accessed upon demand, and converted to heat at temperatures significantly higher than current solar thermal electricity production technology and is therefore well-suited to more efficient high-temperature power cycles. The PROMOTES effort seeks to advance both materials and systems for TCES through the development and demonstration of an innovative storage approach for solarized Air-Brayton power cycles and that is based on newly-developed redox-active metal oxides that are mixed ionic-electronic conductors (MIEC). In this paper we summarize the system concept and review our work to date towards developing materials and individual components.
Time-resolved PIV has been accomplished in three high-speed flows using a pulse-burst laser: a supersonic jet exhausting into a transonic crossflow, a transonic flow over a rectangular cavity, and a shock-induced transient onset to cylinder vortex shedding. Temporal supersampling converts spatial information into temporal information by employing Taylor’s frozen turbulence hypothesis along local streamlines, providing frequency content until about 150 kHz where the noise floor is reached. The spectra consistently reveal two regions exhibiting power-law dependence describing the turbulent decay. One is the well-known inertial subrange with a slope of-5/3 at high frequencies. The other displays a-1 power-law dependence for as much as a decade of mid-range frequencies lying between the inertial subrange and the integral length scale. The evidence for the-1 power law is most convincing in the jet-in-crossflow experiment, which is dominated by in-plane convection and the vector spatial resolution does not impose an additional frequency constraint. Data from the transonic cavity flow that are least likely to be subject to attenuation due to limited spatial resolution or out-of-plane motion exhibit the strongest agreement with the-1 and-5/3 power laws. The cylinder wake data also appear to show the-1 regime and the inertial subrange in the near-wake, but farther downstream the frozen-turbulence assumption may deteriorate as large-scale vortices interact with one another in the von Kármán vortex street.
Solution verification is the process of verifying the solution of a finite element analysis by performing a series of analyses on meshes of increasing mesh densities, to determine if the solution is converging. Solution verification has historically been too expensive, relying upon refinement templates resulting in an 8X multiplier in the number of elements. For even simple convergence studies, the 8X and 64X meshes must be solved, quickly exhausting computational resources. In this paper, we introduce Mesh Scaling, a new global mesh refinement technique for building series of all-hexahedral meshes for solution verification, without the 8X multiplier. Mesh Scaling reverse engineers the block decomposition of existing all-hexahedral meshes followed by remeshing the block decomposition using the original mesh as the sizing function multiplied by any positive floating number (e.g. 0.5X, 2X, 4X, 6X, etc.), enabling larger series of meshes to be constructed with fewer elements, making solution verification tractable.
Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials' coefficients of thermal expansion as well as the shrinkage upon cure exhibited by most thermoset polymer matrix materials. Depending upon the specific geometric details of the composite structure and the materials' curing parameters, it is possible that these residual stresses can result in interlaminar delamination and fracture within the composite as well as plastic deformation in the structure's metallic materials. Therefore, the consideration of potential residual stresses is important when designing composite parts and their manufacturing processes. However, the experimental determination of residual stresses in prototype parts can be prohibitive, both in terms of financial and temporal costs. As an alternative to physical measurement, it is possible for computational tools to be used to quantify potential residual stresses in composite prototype parts. Therefore, the objective of this study is the development of a simplistic method for simulating the residual stresses formed in polymer matrix composite structures. Specifically, a simplified approach accounting for both coefficient of thermal expansion mismatch and polymer shrinkage is implemented within the Sandia National Laboratories' developed solid mechanics code, SIERRA. This approach is then used to model the manufacturing of two simple, bi-material structures composed of a carbon fiber/epoxy composite and aluminum: a flat rectangular plate and cylinders. Concurrent with the computational efforts, structures similar to those modeled are fabricated and the residual stresses are quantified through the measurement of deformation. The simulations' results are compared to the experimentally observed behaviors for model validation, as well as a more complex modeling approach. The results of the comparisons indicate that the proposed finite element modeling approach is capable of accurately simulating the formation of residual stresses in composite structures.
Dispersion engineering enables phase matching for nonlinear down conversion from 775nm to the telecom c-band in lithium niobite microdisk resonators without periodic poling. High rates of spontaneous creation of entangled photon pairs is observed.
Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials' coefficients of thermal expansion as well as the cure shrinkage exhibited by polymer matrix materials. These residual stresses can have a profound effect on the measured performance of a loaded composite structure. A material property of particular interest when modeling the formation of damage in composite materials is the mode I fracture toughness. Currently, the standard method of measuring the mode I fracture toughness involves a double cantilever beam (DCB) experiment, where a pre-crack is introduced into a laminate and subsequently opened under tension. The resulting apparent fracture toughness from the DCB experiment may depend upon a coupled interaction between a material property, the mode I energy release rate, and the effect of residual stresses. Therefore, in this study, a series of DCB experiments are completed in conjunction with the solution of representative finite element models to quantify and understand the effect of process-induced residual stresses and temperature variations on the apparent fracture toughness. Specifically, double cantilever beam experiments are completed at three temperatures to characterize three types of specimens composed of carbon fiber/epoxy and glass fiber/epoxy materials: carbon bonded to carbon, glass bonded to glass, and carbon bonded to glass. The carbon-to-carbon and glass-to-glass specimens provide estimates of the composite's fracture toughness in the absence of significant residual stresses and the carbon-to-glass specimens indicate the effect of measurable process induced stresses. Upon completion of testing, the measured results and observations are used to develop high-fidelity finite element models simulating the residual stresses formed throughout the manufacturing process and the subsequent DCB testing of a laminate composed of the carbon/epoxy and glass/epoxy materials. The stress fields and delamination behavior predicted through simulation assist in understanding the trends observed during the DCB experiments and demonstrate the important relationship between experimental and computational efforts.
We demonstrate doubly resonant second harmonic generation from 1550 to 775 nm in microdisks fabricated from lithium niobate on insulator wafers. We use a novel phase matching technique to achieve a conversion efficiency of 0.167%/mW.
This study examined whether coating system contamination, indicated by poor base pressure, has a negative impact on the laser-induced damage threshold of HfO2/SiO2 high reflection coatings for 527 nm.
The electroreduction of Er3+ in propylene carbonate, N,N-dimethylformamide, or a variety of quaternary ammonium ionic liquids (ILs) was investigated using [Er(OTf)3] and [Er(NTf2)3]. Systematic variation of the ILs' cation and anion, Er3+ salt, and electrode material revealed a disparity in electrochemical interactions not previously seen. For most ILs at a platinum electrode, cyclic voltammetry exhibits irreversible interactions between Er3+ salts and the electrode at potentials significantly less than the theoretical reduction potential for Er3+. Throughout all solvent-salt systems tested, a deposit could be formed on the electrode, though obtaining a high purity, crystalline Er0 deposit is challenging due to the extreme reactivity of the deposit and resulting chemical interactions, often resulting in the formation of a complex, amorphous solid-electrolyte interface that slowed deposition rates. Comparison of platinum, gold, nickel, and glassy carbon (GC) working electrodes revealed oxidation processes unique to the platinum surface. While no appreciable reduction current was observed on GC at the potentials investigated, deposits were seen on platinum, gold, and nickel electrodes.
The Wave Energy Converter Simulator (WEC-Sim) is an open-source code jointly developed by Sandia National Laboratories and the National Renewable Energy Laboratory. It is used to model wave energy converters subjected to operational and extreme waves. In order for the WEC-Sim code to be beneficial to the wave energy community, code verification and physical model validation is necessary. This paper describes numerical modeling of the wave tank testing for the 1:33-scale experimental testing of the floating oscillating surge wave energy converter. The comparison between WEC-Sim and the Phase 1 experimental data set serves as code validation. This paper is a follow-up to the WEC-Sim paper on experimental testing, and describes the WEC-Sim numerical simulations for the floating oscillating surge wave energy converter.
As the population ages, prediction of falls risk is becoming an increasingly important research area. Due to built-in inertial sensors and ubiquity, smartphones provide an at- tractive data collection and computing platform for falls risk prediction and continuous gait monitoring. One challenge in continuous gait monitoring is that significant signal variability exists between individuals with a high falls risk and those with low-risk. This variability increases the difficultly in building a universal system which segments and labels changes in signal state. This paper presents a method which uses unsu- pervised learning techniques to automatically segment a gait signal by computing the dissimilarity between two consecutive windows of data, applying an adaptive threshold algorithm to detect changes in signal state, and using a rule-based gait recognition al- gorithm to label the data. Using inertial data,the segmentation algorithm is compared against manually segmented data and is capable of achieving recognition rates greater than 71.8%.
Sutherland, John W.; Richter, Justin S.; Hutchins, Margot J.; Dornfeld, David; Dzombak, Rachel; Mangold, Jennifer; Robinson, Stefanie; Hauschild, Michael Z.; Bonou, Alexandra; Schonsleben, Paul; Friemann, Felix
Manufacturing affects all three dimensions of sustainability: economy, environment, and society. This paper addresses the last of these dimensions. It explores social impacts identified by national level social indicators, frameworks, and principles. The effects of manufacturing on social performance are framed for different stakeholder groups with associated social needs. Methodology development as well as various challenges for social life cycle assessment (S-LCA) are further examined. Efforts to integrate social and another dimension of sustainability are considered, with attention to globalization challenges, including offshoring and reshoring. The paper concludes with a summary of key takeaways and promising directions for future work.
An a posteriori error-estimation framework is introduced to quantify and reduce modeling errors resulting from approximating complex mesoscale material behavior with a simpler macroscale model. Such errors may be prevalent when modeling welds and additively manufactured structures, where spatial variations and material textures may be present in the microstructure. We consider a case where a <100> fiber texture develops in the longitudinal scanning direction of a weld. Transversely isotropic elastic properties are obtained through homogenization of a microstructural model with this texture and are considered the reference weld properties within the error-estimation framework. Conversely, isotropic elastic properties are considered approximate weld properties since they contain no representation of texture. Errors introduced by using isotropic material properties to represent a weld are assessed through a quantified error bound in the elastic regime. An adaptive error reduction scheme is used to determine the optimal spatial variation of the isotropic weld properties to reduce the error bound.
Understanding the connectivity of fracture networks in a reservoir and obtaining an accurate chemical characterization of the geothermal fluid are vital for the successful operation of a geothermal power plant. Tracer experiments can be used to elucidate fracture connectivity and in most cases are conducted by injecting the tracer at the injection well, manually collecting liquid samples at the wellhead of the production well, and sending the samples off for laboratory analysis. This method does not identify which specific fractures are the ones producing the tracer; it is only a depth-averaged value over the entire wellbore. Sandia is developing a high-temperature wireline tool capable of measuring ionic tracer concentrations and pH downhole using electrochemical sensors. The goal of this effort is to collect real-time pH and ionic tracer concentration data at temperatures up to 225 °C and pressures up to 3000 psi.
This report presents computational analyses that simulate the structural response of crude oil storage caverns at the U.S. Strategic Petroleum Reserve (SPR) West Hackberry site in Louisiana. These analyses evaluate the geomechanical behavior of the 22 caverns at the West Hackberry SPR site for the current condition of the caverns and their wellbores, the effect of the caverns on surface facilities, and for potential enlargement related to drawdowns. These analyses represent a significant upgrade in modeling capability, as the following enhancements have been developed: a 6-million-element finite element model of the entire West Hackberry dome; cavern finite element mesh geometries fit to sonar measurements of those caverns; the full implementation of the multi-mechanism deformation (M-D) creep model; and the use of historic wellhead pressures to analyze the past geomechanical behavior of the caverns. The analyses examined the overall performance of the West Hackberry site by evaluating surface subsidence, horizontal surface strains, and axial well strains. This report presents a case study of how large-scale computational analyses may be used in conjunction with site data to make recommendations for safe depressurization and repressurization of oil storage caverns with unusual geometries and close proximity, and for the determination of the number of available drawdowns for a particular cavern.
Donaldson, Olivia K.; Hattar, Khalid; Trelewicz, Jason R.
Microstructural evolution during the devitrification of amorphous tantalum thin films synthesized via pulsed laser deposition was investigated using in situ transmission electron microscopy (TEM) combined with ex situ isothermal annealing, bright-field imaging, and electron-diffraction analysis. The phases formed during crystallization and their stability were characterized as a function of the chamber pressure during deposition, devitrification temperature, and annealing time. A range of metastable nanocrystalline tantalum oxides were identified following devitrification including multiple orthorhombic oxide phases, which often were present with, or evolved to, the tetragonal TaO2 phase. While the appearance of these phases indicated the films were evolving to the stable form of tantalum oxide—monoclinic tantalum pentoxide—it was likely not achieved for the conditions considered due to an insufficient amount of oxygen present in the films following deposition. Nevertheless, the collective in situ and ex situ TEM analysis applied to thin film samples enabled the isolation of a number of metastable tantalum oxides. New insights were gained into the transformation sequence and stability of these nanocrystalline phases, which presents opportunities for the development of advanced tantalum oxide-based dielectric materials for novel memristor designs.
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
This paper evaluates novel particle release patterns for high-temperature falling particle receivers. Spatial release patterns resembling triangular and square waves are investigated and compared to the conventional straight-line particle release. A design of experiments was developed, and a simulation matrix was developed that investigated three twolevel factors: amplitude, wavelength, and wave type. Results show that the wave-like patterns increased both the particle temperature rise and thermal efficiency of the receiver relative to the straight-line particle release. Larger amplitudes and smaller wavelengths increased the performance by creating a volumetric heating effect that increased light absorption and reduced heat loss. Experiments are also being designed to investigate the hydraulic and thermal performance of these new particle release configurations.
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
This paper evaluates the on-sun performance of a 1 MW falling particle receiver. Two particle receiver designs were investigated: obstructed flow particle receiver vs.free-falling particle receiver. The intent of the tests was to investigate the impact of particle mass flow rate, irradiance, and particle temperature on the particle temperature rise and thermal efficiency of the receiver for each design. Results indicate that the obstructed flow design increased the residence time of the particles in the concentrated flux, thereby increasing the particle temperature and thermal efficiency for a given mass flow rate. The obstructions, a staggered array of chevronshaped mesh structures, also provided more stability to the falling particles, which were prone to instabilities caused by convective currents in the free-fall design. Challenges encountered during the tests included non-uniform mass flow rates, wind impacts, and oxidation/deterioration of the mesh structures. Alternative materials, designs, and methods are presented to overcome these challenges.
Ebeida, Mohamed S.; Rushdi, Ahmad A.; Awad, Muhammad A.; Mahmoud, Ahmed H.; Yan, Dong M.; English, Shawn A.; Owens, John D.; Bajaj, Chandrajit L.; Mitchell, Scott A.
We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations.
During the initial phase of this Department of Energy (DOE) Geothermal Technologies Office (GTO) SubTER project, we conducted a series of high-energy stimulations in shallow wells, the effects of which were evaluated with high resolution seismic imaging campaigns designed to characterize induced fractures. The high-energy stimulations use a novel explosive source that limits damage to the borehole, which was paramount for change detection seismic imaging and re-fracturing experiments. This work provided evidence that the high-energy stimulations were generating self-propping fractures and that these fracture locations could be imaged at inch scales using high-frequency seismic tomography. While the seismic testing certainly provided valuable feedback on fracture generation for the suite of explosives, it left many fracture properties (i.e. permeability) unresolved. We present here the methodology for the second phase of the project, where we are developing and demonstrating emerging seismic and electrical geophysical imaging technologies that have been designed to characterize 1) the 3D extent and distribution of fractures stimulated from the explosive source, 2) 3D fluid transport within the stimulated fracture network through use of a contrasting tracer, and 3) fracture attributes through advanced data analysis. Focus is being placed upon advancing these technologies toward near real-time acquisition and processing in order to help provide the feedback mechanism necessary to understand and control fracture stimulation and fluid flow.
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
Multiple receiver designs have been evaluated for improved optics and efficiency gains including flat panel, vertical-finned flat panel, horizontal-finned flat panel, and radially finned. Ray tracing using SolTrace was performed to understand the light-trapping effects of the finned receivers. Re-reflections of the fins to other fins on the receiver were captured to give an overall effective solar absorptance. The ray tracing, finite element analysis, and previous computational fluid dynamics showed that the horizontalfinned flat panel produced the most efficient receiver with increased light-trapping and lower overall heat loss. The effective solar absorptance was shown to increase from an intrinsic absorptance of 0.86 to 0.96 with ray trace models. The predicted thermal efficiency was shown in CFD models to be over 95%. The horizontal panels produce a re-circulating hot zone between the panel fins reducing convective loss resulting in a more efficient receiver. The analysis and design of these panels are described with additional engineering details on testing a flat panel receiver and the horizontal-finned receiver at the National Solar Thermal Test Facility. Design considerations include the structure for receiver testing, tube sizing, surrounding heat shielding, and machinery for cooling the receiver tubes.
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
The high-temperature particle - supercritical carbon dioxide (sCO2) Brayton power system is a promising option for concentrating solar power (CSP) plants to achieve SunShot metrics for high-temperature operation, efficiency, and cost. This system includes a falling particle receiver to collect solar thermal radiation, a dry-cooled sCO2 Brayton power block to produce electricity, and a particle to sCO2 heat exchanger to couple the previous two. While both falling particle receivers and sCO2 Brayton cycles have been demonstrated previously, a high temperature, high pressure particle/sCO2 heat exchanger has never before been demonstrated. Industry experience with similar heat exchangers is limited to lower pressures, lower temperatures, or alternative fluids such as steam. Sandia is partnering with three experienced heat exchanger manufacturers to develop and down-select several designs for the unit that achieves both high performance and low specific cost to retire risks associated with a solar thermal particle/sCO2 power system. This paper describes plans for the construction of a particle sCO2 heat exchanger testbed at Sandia operating above 700 °C and 20 MPa, with the ability to couple directly with a previously-developed falling particle receiver for on-sun testing at the National Solar Thermal Test Facility (NSTTF).
ASME 2016 10th International Conference on Energy Sustainability, ES 2016, collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
Direct solar power receivers consist of tubular arrays, or panels, which are typically tubes arranged side by side and connected to an inlet and outlet manifold. The tubes absorb the heat incident on the surface and transfer it to the fluid contained inside them. To increase the solar absorptance, high temperature black paint or a solar selective coating is applied to the surface of the tubes. However, current solar selective coatings degrade over the lifetime of the receiver and must be reapplied, which reduces the receiver thermal efficiency and increases the maintenance costs. This work presents an evaluation of several novel receiver shapes which have been denominated as fractal like geometries (FLGs). The FLGs are geometries that create a light-trapping effect, thus, increasing the effective solar absorptance and potentially increasing the thermal efficiency of the receiver. Five FLG prototypes were fabricated out of Inconel 718 and tested in Sandia's solar furnace at two irradiance levels of ∼15 and 30 W/cm2 and two fluid flow rates. Photographic methods were used to capture the irradiance distribution on the receiver surfaces and compared to results from ray-tracing models. This methods provided the irradiance distribution and the thermal input on the FLGs. Air at nearly atmospheric pressure was used as heat transfer fluid. The air inlet and outlet temperatures were recorded, using a data acquisition system, until steady state was achieved. Computational fluid dynamics (CFD) models, using the Discrete Ordinates (DO) radiation and the k-? Shear Stress Transport (SST) equations, were developed and calibrated, using the test data, to predict the performance of the five FLGs at different air flow rates and irradiance levels. The results showed that relative to a flat plate (base case), the new FLGs exhibited an increase in the effective solar absorptance from 0.86 to 0.92 for an intrinsic material absorptance of 0.86. Peak surface temperatures of ∼1000°C and maximum air temperature increases of ∼200°C were observed. Compared to the base case, the new FLGs showed a clear air outlet temperature increase. Thermal efficiency increases of ∼15%, with respect to the base case, were observed. Several tests, in different days, were performed to assess the repeatability of the results. The results obtained, so far, are very encouraging and display a very strong potential for incorporation in future solar power receivers.
Temperature monitoring is essential in automation, mechatronics, robotics and other dynamic systems. Wireless methods which can sense multiple temperatures at the same time without the use of cables or slip-rings can enable many new applications. A novel method utilizing small permanent magnets is presented for wirelessly measuring the temperature of multiple points moving in repeatable motions. The technique utilizes linear least squares inversion to separate the magnetic field contributions of each magnet as it changes temperature. The experimental setup and calibration methods are discussed. Initial experiments show that temperatures from 5 to 50 °C can be accurately tracked for three neodymium iron boron magnets in a stationary configuration and while traversing in arbitrary, repeatable trajectories. This work presents a new sensing capability that can be extended to tracking multiple temperatures inside opaque vessels, on rotating bearings, within batteries, or at the tip of complex endeffectors.
The polymer-composite binder used in lithium-ion battery electrodes must both hold the electrodes together and augment their electrical conductivity while subjected to mechanical stresses caused by active material volume changes due to lithiation and delithiation. We have discovered that cyclic mechanical stresses cause significant degradation in the binder electrical conductivity. After just 160 mechanical cycles, the conductivity of polyvinylidene fluoride (PVDF):carbon black binder dropped between 45-75%. This degradation in binder conductivity has been shown to be quite general, occurring over a range of carbon black concentrations, with and without absorbed electrolyte solvent and for different polymer manufacturers. Mechanical cycling of lithium cobalt oxide (LiCoO2 ) cathodes caused a similar degradation, reducing the effective electrical conductivity by 30-40%. Mesoscale simulations on a reconstructed experimental cathode geometry predicted the binder conductivity degradation will have a proportional impact on cathode electrical conductivity, in qualitative agreement with the experimental measurements. Finally, ohmic resistance measurements were made on complete batteries. Direct comparisons between electrochemical cycling and mechanical cycling show consistent trends in the conductivity decline. This evidence supports a new mechanism for performance decline of rechargeable lithium-ion batteries during operation - electrochemically-induced mechanical stresses that degrade binder conductivity, increasing the internal resistance of the battery with cycling.
Preparation of sodium zirconium silicate phosphate (NaSICon), Na1+ xZr2SixP3− xO12(0.25 ≤ x ≤ 1.0), thin films has been investigated via a chemical solution approach on platinized silicon substrates. Increasing the silicon content resulted in a reduction in the crystallite size and a reduction in the measured ionic conductivity. Processing temperature was also found to affect microstructure and ionic conductivity with higher processing temperatures resulting in larger crystallite sizes and higher ionic conductivities. The highest room temperature sodium ion conductivity was measured for an x = 0.25 composition at 2.3 × 10−5 S/cm. The decreasing ionic conductivity trends with increasing silicon content and decreasing processing temperature are consistent with grain boundary and defect scattering of conducting ions.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Terboven, Christian; Hahnfeld, Jonas; Teruel, Xavier; Mateo, Sergi; Duran, Alejandro; Klemm, Michael; Olivier, Stephen L.; De Supinski, Bronis R.
OpenMP tasking supports parallelization of irregular algorithms. Recent OpenMP specifications extended tasking to increase functionality and to support optimizations, for instance with the taskloop construct. However, task scheduling remains opaque, which leads to inconsistent performance on NUMA architectures. We assess design issues for task affinity and explore several approaches to enable it. We evaluate these proposals with implementations in the Nanos++ and LLVM OpenMP runtimes that improve performance up to 40% and significantly reduce execution time variation.
Recent budget reductions have posed tremendous challenges to the U.S. Army in managing its portfolio of ground combat systems (tanks and other fighting vehicles), thus placing many important programs at risk. To address these challenges, the Army and a supporting team developed and applied the Capability Portfolio Analysis Tool (CPAT) to optimally invest in ground combat modernization over the next 25-35 years. CPAT provides the Army with the analytical rigor needed to help senior Army decision makers allocate scarce modernization dollars to protect soldiers and maintain capability overmatch. CPAT delivers unparalleled insight into multiple-decade modernization planning using a novel multiphase mixed-integer linear programming technique and illustrates a cultural shift toward analytics in the Army's acquisition thinking and processes. CPAT analysis helped shape decisions to continue modernization of the $10 billion Stryker family of vehicles (originally slated for cancellation) and to strategically reallocate over $20 billion to existing modernization programs by not pursuing the Ground Combat Vehicle program as originally envisioned. More than 40 studies have been completed using CPAT, applying operations research methods to optimally prioritize billions of taxpayer dollars and allowing Army acquisition executives to base investment decisions on analytically rigorous evaluations of portfolio trade-offs.
Fatigue crack growth rate (da/dN) versus stress intensity factor range (AK) relationships were measured for various grades of pipeline steel along with their respective welds in high pressure hydrogen. Tests were conducted in both 21 MPa hydrogen gas and a reference environment (e.g. air) at room temperature. Girth welds fabricated by arc welding and friction stir welding processes were examined in X65 and X52 pipeline grades, respectively. Results showed accelerated fatigue crack growth rates for all tests in hydrogen as compared to tests in air. Modestly higher hydrogen-assisted crack growth rates were observed in the welds as compared to their respective base metals. The arc weld and friction stir weld exhibited similar fatigue crack growth behavior suggesting similar sensitivity to hydrogen. A detailed study of microstructure and fractography was performed to identify relationships between microstructure constituents and hydrogen accelerated fatigue crack growth.
ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Sahm, Aaron; Burnham, Laurie; Boehm, Robert; Betemedhin, Adam; Wood, Gary
Total lifetime costs of photovoltaic (PV) systems are important determinants of profitability. But such costs are not always accurately measured and compared against fluctuating electricity costs, which can be an important contributor to longterm profitability. In this paper, we consider the economics of concentrated photovoltaics (CPV), which offer significantly higher efficiency and greater energy production over traditional fixed flat-plate PV installations in high-irradiance regions, but are perceived to be risky investments. Working with two models, one a simple annual model that uses only direct normal solar insolation; the other a more complex hourly model that uses direct normal solar insolation, ambient temperature, and wind speed to predict energy yield, we calculated the energy production and corresponding revenue generation for a 28 kW CPV unit and a comparable single-axis tracker field in Nevada. Our resulting cost matrix shows how much revenue a CPV system can reasonably be expected to generate under different pricing schemes and time periods. While the values vary depending on the assumptions made, the matrix provides an index of profitability, enabling prospective buyers to compare the costs of purchasing, installing and maintaining a system against likely revenue. As a result of our calculations, we anticipate that CPV systems will still be viable in high flux areas because they offer the promise of profitability now and continued or increased profitability as cell costs decrease and/or overall efficiency increases. Nonetheless, other factors, such as long-term reliability and O&M costs, must be addressed if CPV is to compete with other simpler technologies, such as single-axis PV trackers, which have lower upfront costs and are therefore becoming more attractive to potential customers.
ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Chattopadhyay, Ashesh; Kotteda, V.M.K.; Kumar, Vinod; Spotz, William S.
A framework is developed to integrate the existing MFiX (Multiphase Flow with Interphase eXchanges) flow solver with state-of-the-art linear equation solver packages in Trilinos. The integrated solver is tested on various flow problems. The performance of the solver is evaluated on fluidized bed problems and observed that the integrated flow solver performs better compared to the native solver.
We present a resilient domain-decomposition preconditioner for partial differential equations (PDEs). The algorithm reformulates the PDE as a sampling problem, followed by a solution update through data manipulation that is resilient to both soft and hard faults. We discuss an implementation based on a server-client model where all state information is held by the servers, while clients are designed solely as computational units. Servers are assumed to be “sandboxed”, while no assumption is made on the reliability of the clients. We explore the scalability of the algorithm up to ∼12k cores, build an SST/macro skeleton to extrapolate to∼50k cores, and show the resilience under simulated hard and soft faults for a 2D linear Poisson equation.
Inferring the cognitive state of an individual in real time during task performance allows for implementation of corrective measures prior to the occurrence of an error. Current technology allows for real time cognitive state assessment based on objective physiological data though techniques such as neuroimaging and eye tracking. Although early results indicate effective construction of classifiers that distinguish between cognitive states in real time is a possibility in some settings, implementation of these classifiers into real world settings poses a number of challenges. Cognitive states of interest must be sufficiently distinct to allow for continuous discrimination in the operational environment using technology that is currently available as well as practical to implement.
This paper discusses the factor analysis that provides the basis for development and use of Bayesian Network (BN) models to support qualification planning in order to predict the suitability of Six Degrees of Freedom (6DOF) vibration testing for qualification. Qualification includes environmental testing such as temperature, vibration and shock to support a stochastic argument about the suitability of a design. Qualification is becoming more complex because it involves significant human expert judgment and relies on new technologies that have often never been fully utilized to support design assessment. Technology has advanced to the state where 6DOF vibration tests are possible, but these tests are far more complex than traditional single degree of freedom tests. This challenges systems engineers as they strive to plan qualification in an environment where technical and environmental constraints are coupled with the traditional costs, risk and schedule constraints. BN models may provide a framework to aid Systems Engineers in planning qualification efforts with complex constraints. Previous work identified a method for building a BN model for the predictive framework. This paper discusses validation efforts of models derived from the factor analysis and summarizes some recommendations on the factor analyses from industry subject matter experts.
A critical challenge in data science is conveying the meaning of data to human decision makers. While working with visualizations, decision makers are engaged in a visual search for information to support their reasoning process. As sensors proliferate and high performance computing becomes increasingly accessible, the volume of data decision makers must contend with is growing continuously and driving the need for more efficient and effective data visualizations. Consequently, researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles to assess the effectiveness of data visualizations. In this paper, we compare the performance of three different saliency models across a common set of data visualizations. This comparison establishes a performance baseline for assessment of new data visualization saliency models.
Research, the manufacture of knowledge, is currently practiced largely as an “art,” not a “science.” Just as science (understanding) and technology (tools) have revolutionized the manufacture of other goods and services, it is natural, perhaps inevitable, that they will ultimately also be applied to the manufacture of knowledge. In this article, we present an emerging perspective on opportunities for such application, at three different levels of the research enterprise. At the cognitive science level of the individual researcher, opportunities include: overcoming idea fixation and sloppy thinking, and balancing divergent and convergent thinking. At the social network level of the research team, opportunities include: overcoming strong links and groupthink, and optimally distributing divergent and convergent thinking between individuals and teams. At the research ecosystem level of the research institution and the larger national and international community of researchers, opportunities include: overcoming performance fixation, overcoming narrow measures of research impact, and overcoming (or harnessing) existential/social stress.
Cognitive science is an interdisciplinary science which studies the human dimension, drawing from academic disciplines such as psychology, linguistics, philosophy, and computer modeling. Business management is controlling, leading, monitoring, organizing, and planning critical information to bring useful resources and capabilities to a viable market. Finally, the government sector has many roles, but one primary goal is to bring innovative solutions to maintain and enhance national security. There currently is a gap in the government sector between applied research and solutions applicable to the national security field. This is a deep problem since a critical element to many national security issues is the human dimension and requires cognitive science approaches. One major cause to this gap is the separation between business management and cognitive science: scientific research is either not being tailored to the mission need or deployed at a time when it can best be absorbed by national security concerns. This paper addresses three major themes: (1) how cognitive science and business management benefits the government sector, (2) the current gaps that exist between cognitive science and business management, and (3) how cognitive science and business management may work to address government sector, national security needs.
‘Big data’ is a phrase that has gained much traction recently. It has been defined as ‘a broad term for data sets so large or complex that traditional data processing applications are inadequate and there are challenges with analysis, searching and visualization’ [1]. Many domains struggle with providing experts accurate visualizations of massive data sets so that the experts can understand and make decisions about the data e.g., [2, 3, 4, 5]. Abductive reasoning is the process of forming a conclusion that best explains observed facts and this type of reasoning plays an important role in process and product engineering. Throughout a production lifecycle, engineers will test subsystems for critical functions and use the test results to diagnose and improve production processes. This paper describes a value-driven evaluation study [7] for expert analyst interactions with big data for a complex visual abductive reasoning task. Participants were asked to perform different tasks using a new tool, while eye tracking data of their interactions with the tool was collected. The participants were also asked to give their feedback and assessments regarding the usability of the tool. The results showed that the interactive nature of the new tool allowed the participants to gain new insights into their data sets, and all participants indicated that they would begin using the tool in its current state.
Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on host immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to thein vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. The adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection.
Jagannathan, Kaushik; Benson, David M.; Robinson, David B.; Stickney, John L.
Nanofilms of Pd were grown using an electrochemical form of atomic layer deposition (E-ALD) on 100 nm evaporated Au films on glass. Multiple cycles of surface-limited redox replacement (SLRR) were used to grow deposits. Each SLRR involved the underpotential deposition (UPD) of a Cu atomic layer, followed by open circuit replacement via redox exchange with tetrachloropalladate, forming a Pd atomic layer: one E-ALD deposition cycle. That cycle was repeated in order to grow deposits of a desired thickness. 5 cycles of Pd deposition were performed on the Au on glass substrates, resulting in the formation of 2.5 monolayers of Pd. Those Pd films were then modified with varying coverages of Pt, also formed using SLRR. The amount of Pt was controlled by changing the potential for Cu UPD, and by increasing the number of Pt deposition cycles. Hydrogen absorption was studied using coulometry and cyclic voltammetry in 0.1 M H2SO4 as a function of Pt coverage. The presence of even a small fraction of a Pt monolayer dramatically increased the rate of hydrogen desorption. However, this did not reduce the films' hydrogen storage capacity. The increase in desorption rate in the presence of Pt was over an order of magnitude.
A new model of electrodeposition and electrodissolution is developed and applied to the evolution of Mg deposits during anode cycling. The model captures Butler-Volmer kinetics, facet evolution, the spatially varying potential in the electrolyte, and the time-dependent electrolyte concentration. The model utilizes a diffuse interface approach, employing the phase field and smoothed boundary methods. Scanning electron microscope (SEM) images of magnesium deposited on a gold substrate show the formation of faceted deposits, often in the form of hexagonal prisms. Orientation-dependent reaction rate coefficients were parameterized using the experimental SEM images. Three-dimensional simulations of the growth of magnesium deposits yield deposit morphologies consistent with the experimental results. The simulations predict that the deposits become narrower and taller as the current density increases due to the depletion of the electrolyte concentration near the sides of the deposits. Increasing the distance between the deposits leads to increased depletion of the electrolyte surrounding the deposit. Two models relating the orientation-dependence of the deposition and dissolution reactions are presented. The morphology of the Mg deposit after one deposition-dissolution cycle is significantly different between the two orientation-dependence models, providing testable predictions that suggest the underlying physical mechanisms governing morphology evolution during deposition and dissolution.
The peridynamic theory of solid mechanics provides a natural framework for modeling constitutive response and simulating dynamic crack propagation, pervasive damage, and fragmentation. In the case of a fragmenting body, the principal quantities of interest include the number of fragments, and the masses and velocities of the fragments. We present a method for identifying individual fragments in a peridynamic simulation. We restrict ourselves to the meshfree approach of Silling and Askari, in which nodal volumes are used to discretize the computational domain. Nodal volumes, which are connected by peridynamic bonds, may separate as a result of material damage and form groups that represent fragments. Nodes within each fragment have similar velocities and their collective motion resembles that of a rigid body. The identification of fragments is achieved through inspection of the peridynamic bonds, established at the onset of the simulation, and the evolving damage value associated with each bond. An iterative approach allows for the identification of isolated groups of nodal volumes by traversing the network of bonds present in a body. The process of identifying fragments may be carried out at specified times during the simulation, revealing the progression of damage and the creation of fragments. Incorporating the fragment identification algorithm directly within the simulation code avoids the need to write bond data to disk, which is often prohibitively expensive. Results are recorded using fragment identification numbers. The identification number for each fragment is stored at each node within the fragment and written to disk, allowing for any number of post-processing operations, for example the construction of cumulative distribution functions for quantities of interest. Care is taken with regard to very small clusters of isolated nodes, including individual nodes for which all bonds have failed. Small clusters of nodes may be treated as tiny fragments, or may be omitted from the fragment identification process. The fragment identification algorithm is demonstrated using the Sierra/SolidMechanics analysis code. It is applied to a simulation of pervasive damage resulting from a spherical projectile impacting a brittle disk, and to a simulation of fragmentation of an expanding ductile ring.
Additive manufacturing (AM) has reached a critical point which enables production of complex, high resolution, custom parts from robust materials. However, traditional fasteners are still use to join these complex parts together. Integrating fasteners into additively manufactured parts is beneficial for part production but there is uncertainty in their design. To understand how the fasteners fit and function, mechanical property data was collected on the prototypes. This data along with insights gained while building and testing the prototypes increased the knowledge base of design for additive manufacturing and build-to-build variability in selective laser sintering (SLS).
Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.
Additive manufacturing (AM) has reached a critical point which enables production of complex, high resolution, custom parts from robust materials. However, traditional fasteners are still use to join these complex parts together. Integrating fasteners into additively manufactured parts is beneficial for part production but there is uncertainty in their design. To understand how the fasteners fit and function, mechanical property data was collected on the prototypes. This data along with insights gained while building and testing the prototypes increased the knowledge base of design for additive manufacturing and build-to-build variability in selective laser sintering (SLS).
Computational Science and Engineering (CSE) software can benefit substantially from an explicit focus on quality improvement. This is especially true as we face increased demands in both modeling and software complexities. At the same time, just desiring improved quality is not sufficient. We must work with the entities that provide CSE research teams with publication venues, funding, and professional recognition in order to increase incentives for improved software quality. In fact, software quality is precisely calibrated to the expectations, explicit and implicit, set by these entities. We will see broad improvements in sustainability and productivity only when publishers, funding agencies and employers raise their expectations for software quality. CSE software community leaders, those who are in a position to inform and influence these entities, have a unique opportunity to broadly and positively impact software quality by working to establish incentives that will spur creative and novel approaches to improve developer productivity and software sustainability.
Extensive all-atom molecular dynamics calculations on the water-squalane interface for nine different loadings with sorbitan monooleate (SPAN80), at T = 300K, are analyzed for the surface tension equation of state, desorption free energy profiles as they depend on loading, and to evaluate escape times for absorbed SPAN80 into the bulk phases. These results suggest that loading only weakly affects accommodation of a SPAN80 molecule by this squalane-water interface. Specifically, the surface tension equation of state is simple through the range of high tension to high loading studied, and the desorption free energy profiles are weakly dependent on loading here. The perpendicular motion of the centroid of the SPAN80 head-group ring is well-described by a diffusional model near the minimum of the desorption free energy profile. Lateral diffusional motion is weakly dependent on loading. Escape times evaluated on the basis of a diffusional model and the desorption free energies are 7 × 10-2 s (into the squalane) and 3 × 102 h (into the water). The latter value is consistent with irreversible absorption observed by related experimental work.
Enteric and diarrheal diseases are a major cause of childhood illness and death in countries with developing economies. Each year, more than half of a million children under the age of five die from these diseases. We have developed a portable, microfluidic platform capable of simultaneous, multiplexed detection of several of the bacterial pathogens that cause these diseases. This platform can perform fast, sensitive immunoassays directly from relevant, complex clinical matrices such as stool without extensive sample cleanup or preparation. Using only 1 μL of sample per assay, we demonstrate simultaneous multiplexed detection of four bacterial pathogens implicated in diarrheal and enteric diseases in less than 20 min.
Solid freeform fabrication has the potential to affect both financial and environmental concerns for manufacturing enterprises. However, when planning for installation of a new machine tool, accurate energy usage estimation relies heavily on the data and model selections of the estimator. This project used a variety data sources and model decision options to examine the spread of energy consumption and global warming potential estimates for a fused deposition modeling machine. In addition to primary and secondary data sources, the use of similar machines was explored as proxy estimates for the target machine. A Monte Carlo simulation was constructed to vary the model selections, machine utilization, and data sources. The results indicated data sources and model decisions had large effects on the output and that most model estimates were low.
Previous work has shown that conventional diesel ignition improvers, 2-ethylhexyl nitrate (EHN) and di-tert-butyl peroxide (DTBP), can be used to enhance the autoignition of a regular-grade E10 gasoline in a well premixed low-temperature gasoline combustion (LTGC) engine, hereafter termed an HCCI engine, at naturally aspirated and moderately boosted conditions (up to 180 kPa absolute) with a constant engine speed of 1200 rpm and a 14:1 compression ratio. In the current work the effect of EHN on boosted HCCI combustion is further investigated with a higher compression ratio (16:1) piston and over a range of engine speeds (up to 2400 rpm). The results show that the higher compression ratio and engine speeds can make the combustion of a regular-grade E10 gasoline somewhat less stable. The addition of EHN improves the combustion stability by allowing combustion phasing to be more advanced for the same ringing intensity. The high-load limits of both the straight (unadditized) and additized fuels are determined, and the additized fuel is found to achieve a higher maximum load at all engine speeds and intake pressures tested, if it is not limited by lack of oxygen. The results reveal that the higher loads with EHN are the result of either reduced intake temperature requirements at naturally aspirated conditions or a reduction in heat release rate at higher intake pressures. Such effects are also found to increase the thermal efficiency, and a maximum indicated thermal efficiency of 50.1% is found for 0.15% EHN additized fuel at 1800 rpm and 180 kPa intake pressure. Similar to previous studies, the nitrogen in EHN increases NOx emissions, but they remain well below US-2010 standards. Higher engine speeds are found to have slightly lower NOx emissions for additized fuel at intake boosted conditions.
Influence spread is an important phenomenon that occurs in many social networks. Influence maximization is the corresponding problem of finding the most influential nodes in these networks. In this paper, we present a new influence diffusion model, based on pairwise factor graphs, that captures dependencies and directions of influence among neighboring nodes.We use an augmented belief propagation algorithm to efficiently compute influence spread on this model so that the direction of influence is preserved. Due to its simplicity, the model can be used on large graphs with high-degree nodes, making the influence maximization problem practical on large, real-world graphs. Using large Flixster and Epinions datasets, we provide experimental results showing that our model predictions match well with ground-truth influence spreads, far better than other techniques. Furthermore, we show that the influential nodes identified by our model achieve significantly higher influence spread compared to other popular models. The model parameters can easily be learned from basic, readily available training data. In the absence of training, our approach can still be used to identify influential seed nodes.
The Hippogriff camera developed at Sandia National Laboratories as part of the Ultra-Fast X-ray Imager (UXI) program is a high-speed, multi-frame, time-gated imager for use on a wide variety of High Energy Density (HED) physics experiments on both Sandia's Z-Machine and the National Ignition Facility. The camera is a 1024 x 448 pixel array with 25 μm spatial resolution, containing 2 frames per pixel natively and has achieved 2 ns minimum integration time. It is sensitive to both optical photons as well as soft X-rays up to ∼6 keV. The Hippogriff camera is the second generation UXI camera that contains circuitry to trade spatial resolution for additional frames of temporal coverage. The user can reduce the row-wise spatial resolution from the native 25 μm to increase the number of frames in a data set to 4 frames at 50 μm or 8 frames at 100 μm spatial resolution. This feature, along with both optical and X-ray sensitivity, facilitates additional experimental flexibility. Minimum signal is 1500 erms and full well is 1.5 million e-.
The energetics of Sn2+ substitution into the Ca2+ sublattice of hydroxylapatite (HA), Ca10(PO4)6(OH)2, has been investigated within the framework of density functional theory. Calculations reveal that Sn2+ incorporation via coupled substitutions at Ca(ii) sites is energetically favourable up to a composition of Sn6Ca4(PO4)6(OH)2, and further substitutions at Ca(i) sites proceed once full occupancy of Ca(ii) sites by Sn2+ is achieved. Compositions of SnxCa10−x(PO4)6(OH)2 (x = 4-9) are predominant, with an optimal stoichiometry of Sn8Ca2(PO4)6(OH)2, and Sn-substituted HA follows approximately Vegard's law across the entire composition range.
Fluid-structure interactions were studied on a 7° half-angle cone in the Sandia Hypersonic Wind Tunnel at Mach 8 over a range of freestream Reynolds numbers between 3.3 and 14.5 × 106/m. A thin panel with tunable structural natural frequencies was integrated into the cone and exposed to naturally developing boundary layers. An elevated panel response was measured during boundary-layer transition at frequencies corresponding to the turbulent burst rate, and lower vibrations were measured under a turbulent boundary layer. Controlled perturbations from an electrical discharge were then introduced into the boundary layer at varying frequencies corresponding to the structural natural frequencies of the panel. The perturbations were not strong enough to drive a panel response exceeding that due to natural transition. Instead at high repetition rates, the perturber modified the turbulent burst rate and intermittency on the cone and therefore changed the conditions for when an elevated transitional panel vibration response occurred.
We study nanoporous-carbon (NPC) grown via pulsed laser deposition (PLD) as an electrically conductive anode host material for Mg2+ intercalation. NPC has high surface area, and an open, accessible pore structure tunable via mass density that can improve diffusion. We fabricate 2032 coin cells using NPC coated stainless-steel disk anodes, metallic Mg cathodes, and a Grignardbased electrolyte. NPC mass density is controlled during growth, ranging from 0.06-1.3 g/cm3. The specific surface area of NPC increases linearly from 1,000 to 1,700 m2/g as mass density decreases from 1.3 to 0.26 g/cm3, however, the surface area falls off dramatically at lowermass densities, implying a lack of mechanical integrity in such nanostructures. These structural characterizations correlate directly with coin cell electrochemical measurements. In particular, cyclic voltammetry (CV) scans for NPC with density ∼0.5 g/cm3 and BET surface area ∼1500 m2/g infer the possibility of reversible Mg-ion intercalation. Higher density NPC yields capacitive behavior, most likely resulting from the smaller interplanar spacings between graphene sheet fragments and tighter domain boundaries; lower density NPC results in asymmetrical CV scans, consistent with the likely structural degradation resulting from mass transport through soft, low-density carbon materials.
Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials' coefficients of thermal expansion as well as the shrinkage upon cure exhibited by most thermoset polymer matrix materials. Depending upon the specific geometric details of the composite structure and the materials' curing parameters, it is possible that these residual stresses can result in interlaminar delamination and fracture within the composite as well as plastic deformation in the structure's metallic materials. Therefore, the consideration of potential residual stresses is important when designing composite parts and their manufacturing processes. However, the experimental determination of residual stresses in prototype parts can be prohibitive, both in terms of financial and temporal costs. As an alternative to physical measurement, it is possible for computational tools to be used to quantify potential residual stresses in composite prototype parts. Therefore, the objective of this study is the development of a simplistic method for simulating the residual stresses formed in polymer matrix composite structures. Specifically, a simplified approach accounting for both coefficient of thermal expansion mismatch and polymer shrinkage is implemented within the Sandia National Laboratories' developed solid mechanics code, SIERRA. This approach is then used to model the manufacturing of two simple, bi-material structures composed of a carbon fiber/epoxy composite and aluminum: a flat rectangular plate and cylinders. Concurrent with the computational efforts, structures similar to those modeled are fabricated and the residual stresses are quantified through the measurement of deformation. The simulations' results are compared to the experimentally observed behaviors for model validation, as well as a more complex modeling approach. The results of the comparisons indicate that the proposed finite element modeling approach is capable of accurately simulating the formation of residual stresses in composite structures.
We consider the problem of sampling points from a collection of smooth curves in the plane, such that the CRUST family of proximity-based reconstruction algorithms can rebuild the curves. Reconstruction requires a dense sampling of local features, i.e., parts of the curve that are close in Euclidean distance but far apart geodesically. We show that e < 0:47-sampling is sufficient for our proposed HNN-CRUST variant, improving upon the state-of-the-art requirement of e < 13-sampling. Thus we may reconstruct curves with many fewer samples. We also present a new sampling scheme that reduces the required density even further than e < 0:47-sampling. We achieve this by better controlling the spacing between geodesically consecutive points. Our novel sampling condition is based on the reach, the minimum local feature size along intervals between samples. This is mathematically closer to the reconstruction density requirements, particularly near sharp-angled features. We prove lower and upper bounds on reach r-sampling density in terms of lfs e-sampling and demonstrate that we typically reduce the required number of samples for reconstruction by more than half.
The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the network characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. As a result, we discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.
We have designed and reported on a dichroic beam combiner coating consisting of HfO2/SiO2 layer pairs to provide high transmission at 527 nm and high reflection at 1054 nm for 22.5° angle of incidence (AOI) in S polarization (Spol). The laser-induced damage threshold (LIDT) of this first coating at the use AOI and polarization with 3.5 nanosecond (ns) pulses at 532 nm is 7 J/cm2, and only marginally adequate for our beam combining application. In this paper, we describe the use of a combination of Al2O3 and HfO2 high index layers to modify the first as well as a second dichroic coating in two different ways, which results in a higher LIDT of 10 J/cm2 for 3.5 ns pulses at 532 nm and 22.5° AOI, Spol for the second dichroic coating, and in the same 7 J/cm2 LIDT for the first dichroic coating.
COBRA-TF (CTF) is a thermal hydraulic (T/H) subchannel code using either three-dimensional (3D) Cartesian or subchannel coordinate formulations for two-phase fluid flow and heat transfer solutions. CTF has been improved under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program for Pressurized Water Reactor (PWR) applications, including software optimization, new closure models, pre- and post-processing and parallelization for modeling full reactor core T/H responses under normal operating and accident conditions. As a result of collaboration among CASL partners including the Westinghouse Electric Company, the Oak Ridge National Laboratory (ORNL), and the Sandia National Laboratories, additional modeling improvements were made to CTF specifically for PWR Departure from Nucleate Boiling (DNB) analysis, including a code option to evaluate fuel thermal margin in terms of DNB Ratio (DNBR) and an axial shape factor to account for effect of non-uniform axial power distribution on DNB. Multiple DNB correlations are now linked with CTF for different applications, including the Westinghouse proprietary WRB-1 correlation for fuel designs containing mixing vane grid spacers. The improved CTF code with the WRB-1 correlation (CTF/WRB-1) was validated using the DNB data from the PWR Subchannel Bundle Tests (PSBT). In addition to the comparison with the test data, the CTF/WRB-1 DNBR results and the associated local fluid conditions were compared to the results of the Westinghouse T/H design code, VIPRE-W, which is an enhanced version of the VIPRE-01 code originally developed by the Electric Power Research Institute (EPRI). The comparisons showed that CTF/WRB-1 DNBR predictions are in good agreement with the VIPRE-W results within the applicable range of the DNB correlation. A model sensitivity study was performed to confirm that the CTF void drift model had an insignificant effect on DNBR under the steam line break (SLB) low pressure condition.
Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials' coefficients of thermal expansion as well as the cure shrinkage exhibited by polymer matrix materials. These residual stresses can have a profound effect on the measured performance of a loaded composite structure. A material property of particular interest when modeling the formation of damage in composite materials is the mode I fracture toughness. Currently, the standard method of measuring the mode I fracture toughness involves a double cantilever beam (DCB) experiment, where a pre-crack is introduced into a laminate and subsequently opened under tension. The resulting apparent fracture toughness from the DCB experiment may depend upon a coupled interaction between a material property, the mode I energy release rate, and the effect of residual stresses. Therefore, in this study, a series of DCB experiments are completed in conjunction with the solution of representative finite element models to quantify and understand the effect of process-induced residual stresses and temperature variations on the apparent fracture toughness. Specifically, double cantilever beam experiments are completed at three temperatures to characterize three types of specimens composed of carbon fiber/epoxy and glass fiber/epoxy materials: carbon bonded to carbon, glass bonded to glass, and carbon bonded to glass. The carbon-to-carbon and glass-to-glass specimens provide estimates of the composite's fracture toughness in the absence of significant residual stresses and the carbon-to-glass specimens indicate the effect of measurable process induced stresses. Upon completion of testing, the measured results and observations are used to develop high-fidelity finite element models simulating the residual stresses formed throughout the manufacturing process and the subsequent DCB testing of a laminate composed of the carbon/epoxy and glass/epoxy materials. The stress fields and delamination behavior predicted through simulation assist in understanding the trends observed during the DCB experiments and demonstrate the important relationship between experimental and computational efforts.
