Publications

We report the application of ultrafast rotational coherent anti-Stokes Raman scattering (CARS) for temperature and relative oxygen concentration measurements in the plume emanating from a burning aluminized ammonium perchlorate propellant strand. Combustion of these metal-based propellants is a particularly hostile environment for laserbased diagnostics, with intense background luminosity, scattering and beam obstruction from hot metal particles that can be as large as several hundred microns in diameter. CARS spectra that were previously obtained using nanosecond pulsed lasers in an aluminumparticle- seeded flame are examined and are determined to be severely impacted by nonresonant background, presumably as a result of the plasma formed by particulateenhanced laser-induced breakdown. Introduction of fs/ps laser pulses enables CARS detection at reduced pulse energies, decreasing the likelihood of breakdown, while simultaneously providing time-gated elimination of any nonresonant background interference. Temperature probability densities and temperature/oxygen correlations were constructed from ensembles of several thousand single-laser-shot measurements from the fs/ps rotational CARS measurement volume positioned within 3 mm or less of the burning propellant surface. Preliminary results in canonical flames are presented using a hybrid fs/ps vibrational CARS system to demonstrate our progress towards acquiring vibrational CARS measurements for more accurate temperatures in the very high temperature propellant burns.

Solving Laplacian linear systems is an important task in a variety of practical and theoretical applications. This problem is known to have solutions that perform in linear times polylogarithmic work in theory, but these algorithms are difficult to implement in practice. We examine existing solution techniques in order to determine the best methods currently available and for which types of problems are they useful. We perform timing experiments using a variety of solvers on a variety of problems and present our results. We discover differing solver behavior between web graphs and a class of synthetic graphs designed to model them.

We have recently reported that two classes of time-dependent triaxial magnetic fields can induce vorticity in magnetic particle suspensions. The first class-symmetry-breaking fields-is comprised of two ac components and one dc component. The second class-rational triad fields-is comprised of three ac components. In both cases deterministic vorticity occurs when the ratios of the field frequencies form rational numbers. A strange aspect of these fields is that they produce fluid vorticity without generally having a circulating field vector, such as would occur in a rotating field. It has been shown, however, that the symmetry of the field trajectory, considered jointly with that of the converse field, allows vorticity to occur around one particular field axis. This axis might be any of the field components, and is determined by the relative frequencies of the field components. However, the symmetry theories give absolutely no insight into why vorticity should occur. In this paper we propose a particle-based model of vorticity in these driven fluids. This model proposes that particles form volatile chains that follow, but lag behind, the dynamic field vector. This model is consistent with the predictions of symmetry theory and gives reasonable agreement with previously reported torque density measurements for a variety of triaxial fields.

It is well known that the derivative-based classical approach to strain is problematic when the displacement field is irregular, noisy, or discontinuous. Difficulties arise wherever the displacements are not differentiable. We present an alternative, nonlocal approach to calculating strain from digital image correlation (DIC) data that is well-defined and robust, even for the pathological cases that undermine the classical strain measure. This integral formulation for strain has no spatial derivatives and when the displacement field is smooth, the nonlocal strain and the classical strain are identical. We submit that this approach to computing strains from displacements will greatly improve the fidelity and efficacy of DIC for new application spaces previously untenable in the classical framework.

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.

Waterborne pathogens pose significant threat to the global population and early detection plays an important role both in making drinking water safe, as well as in diagnostics and treatment of water-borne diseases. We present an innovative centrifugal sedimentation immunoassay platform for detection of bacterial pathogens in water. Our approach is based on binding of pathogens to antibody-functionalized capture particles followed by sedimentation of the particles through a density-media in a microfluidic disk. Beads at the distal end of the disk are imaged to quantify the fluorescence and determine the bacterial concentration. Our platform is fast (20 min), can detect as few as ~10 bacteria with minimal sample preparation, and can detect multiple pathogens simultaneously. The platform was used to detect a panel of enteric bacteria (Escherichia coli, Salmonella typhimurium, Shigella, Listeria, and Campylobacter) spiked in tap and ground water samples.

There has been a lot of interest in the matching error for two-dimensional digital image correlation (2D-DIC), including the matching bias and variance; however, there are a number of other sources of error that must also be considered. These include temperature drift of the camera, out-of-plane sample motion, lack of perpendicularity, under-matched subset shape functions, and filtering of the results during the strain calculation. This talk will use experimental evidence to demonstrate some of the ignored error sources and compile a complete “notional” error budget for a typical 2D measurement.

We are developing the capability to track material changes through numerous possible steps of the manufacturing process, such as forging, machining, and welding. In this work, experimental and modeling results are presented for a multiple-step process in which an ingot of stainless steel 304L is forged at high temperature, then machined into a thin slice, and finally subjected to an autogenous GTA weld. The predictions of temperature, yield stress, and recrystallized volume fraction are compared to experimental results.

Simulation is a widely adopted method to analyze and predict the performance of large-scale parallel applications. Validating the hardware model is highly important for complex simulations with a large number of parameters. Common practice involves calculating the percent error between the projected and the real execution time of a benchmark program. However, in a high-dimensional parameter space, this coarse-grained approach often suffers from parameter insensitivity, which may not be known a priori. Moreover, the traditional approach cannot be applied to the validation of software models, such as application skeletons used in online simulations. In this work, we present a methodology and a toolset for validating both hardware and software models by quantitatively comparing fine-grained statistical characteristics obtained from execution traces. Although statistical information has been used in tasks like performance optimization, this is the first attempt to apply it to simulation validation. Our experimental results show that the proposed evaluation approach offers significant improvement in fidelity when compared to evaluation using total execution time, and the proposed metrics serve as reliable criteria that progress toward automating the simulation tuning process.

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.

Glass forming materials like polymers exhibit a variety of complex, nonlinear, time-dependent relaxations in volume, enthalpy and stress, all of which affect material performance and aging. Durable product designs rely on the capability to predict accurately how these materials will respond to mechanical loading and temperature regimes over prolonged exposures to operating environments. This cannot be achieved by developing a constitutive framework to fit only one or two types of experiments. Rather, it requires a constitutive formalism that is quantitatively predictive to engineering accuracy for the broad range of observed relaxation behaviors. Moreover, all engineering analyses must be performed from a single set of material model parameters. The rigorous nonlinear viscoelastic Potential Energy Clock (PEC) model and its engineering phenomenological equivalent, the Simplified Potential Energy Clock (SPEC) model, were developed to fulfill such roles and have been applied successfully to thermoplastics and filled and unfilled thermosets. Recent work has provided an opportunity to assess the performance of the SPEC model in predicting the viscoelastic behavior of an inorganic sealing glass. This presentation will overview the history of PEC and SPEC and describe the material characterization, model calibration and validation associated with the high Tg (~460 °C) sealing glass.

To analyze the stresses and strains generated during the solidification of glass-forming materials, stress and volume relaxation must be predicted accurately. Although the modeling attributes required to depict physical aging in organic glassy thermosets strongly resemble the structural relaxation in inorganic glasses, the historical modeling approaches have been distinctly different. To determine whether a common constitutive framework can be applied to both classes of materials, the nonlinear viscoelastic simplified potential energy clock (SPEC) model, developed originally for glassy thermosets, was calibrated for the Schott 8061 inorganic glass and used to analyze a number of tests. A practical methodology for material characterization and model calibration is discussed, and the structural relaxation mechanism is interpreted in the context of SPEC model constitutive equations. SPEC predictions compared to inorganic glass data collected from thermal strain measurements and creep tests demonstrate the ability to achieve engineering accuracy and make the SPEC model feasible for engineering applications involving a much broader class of glassy materials.

Iridium alloys have been utilized as structural materials for certain high-temperature applications due to their superior strength and ductility at elevated temperatures. In some applications where the iridium alloys are subjected to high-temperature and high-speed impact simultaneously, the high-temperature high-strain-rate mechanical properties of the iridium alloys must be fully characterized to understand the mechanical response of the components in these severe applications. In this study, the room-temperature Kolsky tension bar was modified to characterize a DOP-26 iridium alloy in tension at elevated strain rates and temperatures. The modifications include (1) a unique cooling system to cool down the bars while the specimen was heated to high temperatures with an induction heater; (2) a small-force pre-tension system to compensate for the effect of thermal expansion in the high-temperature tensile specimen; (3) a laser system to directly measure the displacements at both ends of the tensile specimen independently; and (4) a pair of high-sensitivity semiconductor strain gages to measure the weak transmitted force. The dynamic high-temperature tensile stress-strain curves of the iridium alloy were experimentally obtained with the modified high-temperature Kolsky tension bar techniques at two different strain rates (~1000 and 3000 s-1) and temperatures (~750 and 1030 °C).

Simulations of low velocity impact with a flat cylindrical indenter upon a carbon fiber fabric reinforced polymer laminate are rigorously validated. Comparison of the impact energy absorption between the model and experiment is used as the validation metric. Additionally, non-destructive evaluation, including ultrasonic scans and three-dimensional computed tomography, provide qualitative validation of the models. The simulations include delamination, matrix cracks and fiber breaks. An orthotropic damage and failure constitutive model, capable of predicting progressive damage and failure, is developed in conjunction and described. An ensemble of simulations incorporating model parameter uncertainties is used to predict a response distribution which is then compared to experimental output using appropriate statistical methods. Finally, the model form errors are exposed and corrected for use in an additional blind validation analysis. The result is a quantifiable confidence in material characterization and model physics when simulating low velocity impact in structures of interest.

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

At the completion of the National Ignition Campaign (NIC), the National Ignition Facility (NIF) had about 36 different types of diagnostics. These were based on several decades of development on Nova and OMEGA and involved the whole U.S. inertial confinement fusion community. In 1994, the Joint Central Diagnostic Team documented a plan for a limited set of NIF diagnostics in the NIF Conceptual Design Report. Two decades later, these diagnostics, and many others, were installed workhorse tools for all users of NIF. We give a short description of each of the 36 different types of NIC diagnostics grouped by the function of the diagnostics, namely, target drive, target response and target assembly, stagnation, and burn. A comparison of NIF diagnostics with the Nova diagnostics shows that the NIF diagnostic capability is broadly equivalent to that of Nova in 1999. Although NIF diagnostics have a much greater degree of automation and rigor than Nova's, new diagnostics are limited such as the higher-speed X-ray imager. Recommendations for future diagnostics on the NIF are discussed.

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.

Abstract not provided.

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.

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.

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.

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.

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%.

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.

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.

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.

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.

Abstract not provided.

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.

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.

We report the application of ultrafast rotational coherent anti-Stokes Raman scattering (CARS) for temperature and relative oxygen concentration measurements in the plume emanating from a burning aluminized ammonium perchlorate propellant strand. Combustion of these metal-based propellants is a particularly hostile environment for laserbased diagnostics, with intense background luminosity, scattering and beam obstruction from hot metal particles that can be as large as several hundred microns in diameter. CARS spectra that were previously obtained using nanosecond pulsed lasers in an aluminumparticle- seeded flame are examined and are determined to be severely impacted by nonresonant background, presumably as a result of the plasma formed by particulateenhanced laser-induced breakdown. Introduction of fs/ps laser pulses enables CARS detection at reduced pulse energies, decreasing the likelihood of breakdown, while simultaneously providing time-gated elimination of any nonresonant background interference. Temperature probability densities and temperature/oxygen correlations were constructed from ensembles of several thousand single-laser-shot measurements from the fs/ps rotational CARS measurement volume positioned within 3 mm or less of the burning propellant surface. Preliminary results in canonical flames are presented using a hybrid fs/ps vibrational CARS system to demonstrate our progress towards acquiring vibrational CARS measurements for more accurate temperatures in the very high temperature propellant burns.

Abstract not provided.

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.

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.

Abstract not provided.

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.

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.

Abstract not provided.

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.

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.

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.

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.

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.

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.

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%.