Publications

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We investigate the generation and propagation of intense pulsed ion beams at the 6 MeV level and above using the Hermes III facility at Sandia National Laboratories. While high-power ion beams have previously been produced using Hermes III, we have conducted systematic studies of several ion diode geometries for the purpose of maximizing focused ion energy for a number of applications. A self-field axial-gap diode of the pinch reflex type and operated in positive polarity yielded beam power below predicted levels. This is ascribed both to power flow losses of unknown origin upstream of the diode load in Hermes positive polarity operation, and to anomalies in beam focusing in this configuration. A change to a radial self-field geometry and negative polarity operation resulted in greatly increased beam voltage (> 6 MeV) and estimated ion current. A comprehensive diagnostic set was developed to characterize beam performance, including both time-dependent and time-integrated measurements of local and total beam power. A substantial high-energy ion population was identified propagating in reverse direction, i.e. from the back side of the anode in the electron beam dump. While significant progress was made in increasing beam power, further improvements in assessing the beam focusing envelope will be required before ultimate ion generation efficiency with this geometry can be completely determined.

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Membranes for liquid and gas separations and ion transport are critical to water purification, osmotic energy generation, fuel cells, batteries, supercapacitors, and catalysis. Often these membranes lack pore uniformity and robustness under operating conditions, which can lead to a decrease in performance. The lack of uniformity means that many pores are non-functional. Traditional membranes overcome these limitations by using thick membrane materials that impede transport and selectivity, which results in decreased performance and increased operating costs. For example, limitations in membrane performance demand high applied pressures to deionize water using reverse osmosis. In contrast, cellular membranes combine high flux and selective transport using membrane-bound protein channels operating at small pressure differences. Pore size and chemistry in the cellular channels is defined uniformly and with sub-nanometer precision through protein folding. The thickness of these cellular membranes is limited to that of the cellular membrane bilayer, about 4 nm thick, which enhances transport. Pores in the cellular membranes are robust under operating conditions in the body. Recent efforts to mimic cellular water channels for efficient water deionization produced a significant advance in membrane function. The novel biomimetic design achieved a 10-fold increase in membrane permeability to water flow compared to commercial membranes and still maintained high salt rejection. Despite this success, there is a lack of understanding about why this membrane performs so well. To address this lack of knowledge, we used highperformance computing to interrogate the structural and chemical environments experienced by water and electrolytes in the newly created biomimetic membranes. We also compared the solvation environments between the biomimetic membrane and cellular water channels. These results will help inform future efforts to optimize and tune the performance of synthetic biomimetic membranes for applications in water purification, energy, and catalysis.

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The valuation of an electricity storage device is based on the expected future cash flow generated by the device. Two potential sources of income for an electricity storage system are energy arbitrage and participation in the frequency regulation market. Energy arbitrage refers to purchasing (storing) energy when electricity prices are low, and selling (discharging) energy when electricity prices are high. Frequency regulation is an ancillary service geared towards maintaining system frequency, and is typically procured by the independent system operator in some type of market. This paper outlines the calculations required to estimate the maximum potential revenue from participating in these two activities. First, a mathematical model is presented for the state of charge as a function of the storage device parameters and the quantities of electricity purchased/sold as well as the quantities offered into the regulation market. Using this mathematical model, we present a linear programming optimization approach to calculating the maximum potential revenue from an electricity storage device. The calculation of the maximum potential revenue is critical in developing an upper bound on the value of storage, as a benchmark for evaluating potential trading strategies, and a tool for capital finance risk assessment. Then, we use historical California Independent System Operator (CAISO) data from 2010-2011 to evaluate the maximum potential revenue from the Tehachapi wind energy storage project, an American Recovery and Reinvestment Act of 2009 (ARRA) energy storage demonstration project. We investigate the maximum potential revenue from two different scenarios: arbitrage only and arbitrage combined with the regulation market. Our analysis shows that participation in the regulation market produces four times the revenue compared to arbitrage in the CAISO market using 2010 and 2011 data. Then we evaluate several trading strategies to illustrate how they compare to the maximum potential revenue benchmark. We conclude with a sensitivity analysis with respect to key parameters.

Compression creep tests were performed on the ternary 91.84Sn-3.33Ag-4.83Bi (wt.%, abbreviated Sn-Ag-Bi) Pb-free alloy. The test temperatures were: -25 °C, 25 °C, 75 °C, 125 °C, and 160 °C (± 0.5 °C). Four loads were used at the two lowest temperatures and five at the higher temperatures. The specimens were tested in the as-fabricated condition or after having been subjected to one of two air aging conditions: 24 hours at either 125 °C or 150 °C. The strain-time curves exhibited frequent occurrences of negative creep and small-scale fluctuations, particularly at the slower strain rates, that were indicative of dynamic recrystallization (DRX) activity. The source of tertiary creep behavior at faster strain rates was likely to also be DRX rather than a damage accumulation mechanism. Overall, the strain-time curves did not display a consistent trend that could be directly attributed to the aging condition. The sinh law equation satisfactorily represented the minimum strain rate as a function of stress and temperature so as to investigate the deformation rate kinetics: dε/dtmin = Asinhn (ασ) exp (-ΔH/RT). The values of α, n, and ΔH were in the following ranges (±95% confidence interval): α, 0.010-0.015 (±0.005 1/MPa); n, 2.2-3.1 (±0.5); and ΔH, 54-66 (±8 kJ/mol). The rate kinetics analysis indicated that short-circuit diffusion was a contributing mechanism to dislocation motion during creep. The rate kinetics analysis also determined that a minimum creep rate trend could not be developed between the as-fabricated versus aged conditions. This study showed that the elevated temperature aging treatments introduced multiple changes to the Sn-Ag-Bi microstructure that did not result in a simple loss ("softening") of its mechanical strength. © 2012 by Sandia Corporation.

Over the course of time, the profession of quality engineering has witnessed significant change, from its original emphasis on quality control and inspection to a more contemporary focus on upholding quality processes throughout the organization and its product realization activities. This paper describes the profession of quality engineering, exploring how today's quality engineers and quality professionals are certified individuals committed to upholding quality processes and principles while working with different dimensions of product development. It also discusses the future of the quality engineering profession and the future of the quality movement as a whole.

The current framework for quality scholarship in the United States ranges from the training and education of future quality engineers, managers, and professionals to focused and sustained research initiatives that, through academic institutions and other organizations, aim to improve the knowledge and application of quality across a variety of sectors. Numerous quality journals also provide a forum for professional dissemination of information.

This document highlights the important results obtained from the subtask of the Goodyear CRADA devoted to better understanding reliability of tires and to developing better lifetime prediction methods. The overall objective was to establish the chemical and physical basis for the degradation of tires using standard as well as unique models and experimental techniques. Of particular interest was the potential application of our unique modulus profiling apparatus for assessing tire properties and for following tire degradation. During the course of this complex investigation, extensive relevant information was generated, including experimental results, data analyses and development of models and instruments. Detailed descriptions of the findings are included in this report.

Over the past few years, we have defined and gone a long ways towards implementing a component-based strategy for building scientific application codes. We have asserted that this approach offers significant advantages over a model of writing project-based application codes. There are now several technical and programmatic successes that validate these claims. Not only are there net benefits to code projects that follow this strategy, but also the most striking gains are for the long-term impact and productivity of our computational science organizations.

This work was funded by the U.S. Department of Energy Office of Nonproliferation Research to develop elpasolite materials, with an emphasis on high-atomic-number rare-earth elpasolites for gamma-ray spectrometer applications. Low-cost, high-performance gamma-ray spectrometers are needed for detection of nuclear proliferation. Cubic materials, such as some members of the elpasolite family (A2BLnX6; Ln-lanthanide and X-halogen), hold promise due to their high light output, proportionality, and potential for scale-up. Using both computational and experimental studies, a systematic investigation of the compositionstructureproperty relationships of these high-atomic-number elpasolite halides was performed. The results reduce the barrier to commercialization of large single crystals or transparent ceramics, and will facilitate economical scale-up of elpasolites for high-sensitivity gamma-ray spectroscopy.

Many reactions in both chemistry and biology rely on the ability to precisely control and fix the solution concentrations of either protons or hydroxide ions. In this report, we describe the behavior of thermally programmable pH buffer systems based on the copolymerization of varying amounts of acrylic acid (AA) groups into N-isopropylacrylamide polymers. Because the copolymers undergo phase transitions upon heating and cooling, the local environment around the AA groups can be reversibly switched between hydrophobic and hydrophilic states affecting the ionization behavior of the acids. Results show that moderate temperature variations can be used to change the solution pH by two units. However, results also indicate that the nature of the transition and its impact on the pH values are highly dependent on the AA content and the degree of neutralization. © 2012 American Chemical Society.

Under an applied electric field, concentration polarization (CP) arises from ion permselectivity of most nanoporous materials and biological ion channels. We present novel methods to quantitatively assess CP-induced spatiotemporal changes of pH that may significantly impact transport dynamics, device functionality, and physicochemical properties of molecular analytes in devices with nanofluidic constrictions. We measured pH fluctuations of >1.5 pH units and changes extending over 100's of micrometers from nanoconstrictions. The degree of change depends on key system parameters including buffer composition, surface charge, and strength of electric field. The results highlight the importance of neglected contributions of pH changes, and the approach can aid characterization and manipulation of mass transport in nanofluidic systems. © 2012 American Chemical Society.

A significant portion of all energy capacity is wasted in over-provisioning to meet peak demand. The current state-of-the-art in reducing peak demand requires central authorities to limit device usage directly, and are generally reactive. We apply techniques drawn from established distributed computing principles to propose a novel and proactive solution to decentralize management of demand and to provide a more scalable and resilient approach to reducing overall peak demand. We demonstrate that such a system approaches the performance of an ideal centralized control authority, and experimentally demonstrate a 10-25% reduction in peak energy demand under conservative assumptions. Under worst-case demand scenarios, our approach has the potential to reduce peak demand by 65-85%. © 2012 IEEE.

The 2011 National Electrical Code® Article 690.11 requires photovoltaic systems on or penetrating a building to include a DC arc-fault protection device. In order to satisfy this requirement, new Arc-Fault Detectors (AFDs) are being developed by multiple manufacturers including Sensata Technologies. Arc-fault detection algorithms often utilize the AC noise on the PV string to determine when arcing conditions exist in the DC system. In order to accelerate the development and testing of Sensata Technologies' arc-fault detection algorithm, Sandia National Laboratories (SNL) provided a number of data sets. These prerecorded 10 MHz baseline and arc-fault data sets included different inverter and arc-fault noise signatures. Sensata Technologies created a data evaluation method focused on regeneration of the prerecorded arcing and baseline test data with an arbitrary function generator, thereby reducing AFD development time. © 2012 IEEE.

Existing screening procedures contained in state and federal interconnection rules are designed to balance the need for efficiency and technical rigor for all Distributed Generation (DG). The interconnection of DG that pose no risk of system impacts based on the screens can be expedited without the need for further studies. While the interconnection screening procedures have served the industry well, they also need to evolve in order to remain relevant with respect to evolving standards, technology, and practical experience. This is particularly important considering the large and increasing volume of DG applications, particularly photovoltaic (PV) generation. This paper discusses the application of two screens from the point of view of PV: the 15% penetration on line sections and the 20 kW aggregate capacity screen for single-phase secondary circuits. We discuss extensions to the existing interconnection screens that allow for a more rigorous upfront technical evaluation to identify potential system impacts, based on the characteristics of PV generation. More effective and efficient screens will allow utilities to focus the interconnection study effort for PV systems on the cases most likely to impact the electric distribution system and avoid unnecessary interconnection study costs and delays. © 2012 IEEE.

A novel model-based prognostics and health management (PHM) system has been designed to monitor the health of a photovoltaic (PV) system, measure degradation, and indicate maintenance schedules. Current state-of-the-art PV monitoring systems require module and array topology details or extensive modeling of the PV system. We present a method using an artificial neural network (ANN) which eliminates the need for a priori information by teaching the algorithm "good" performance behavior based on the initial performance of the array. The PHM algorithm was tested on two PV systems under test at the Outdoor Test Facility (OTF) at the National Renewable Energy Laboratory (NREL). The PHM algorithm was trained using two months of AC power production. The model then predicted the output power of the system using irradiance, wind, and temperature data. Based on the deviation in measured AC power from the AC power predicted by the trained ANN model, system outages and other faults causing a reduction in power were detected. Had these been commercial installations, rather than research installations, an alert for maintenance could have been initiated. Further use of the PHM system may be able to indicate degradation, detect module or inverter failures, or detect excessive soiling. © 2012 IEEE.

A custom IR spot scanning experiment was constructed to project subpixel spots on a mercury cadmium telluride focal plane array (FPA). The hardware consists of an FPA in a liquid nitrogen cooled Dewar, high precision motorized stages, a custom aspheric lens, and a 1.55 and 3.39 laser source. By controlling the position and intensity of the spot, characterizations of cross talk, saturation, blooming, and (indirectly) the minority carrier lifetime were performed. In addition, a Monte–Carlo-based charge diffusion model was developed to validate experimental data and make predictions. Results show very good agreement between the model and experimental data. Parameters such as wavelength, reverse bias, and operating temperature were found to have little effect on pixel crosstalk in the absorber layer of the detector. Saturation characterizations show that these FPAs, which do not have antiblooming circuitry, exhibit an increase in cross talk due to blooming at ∼39% beyond the flux required for analog saturation. © 2012 Optical Society of America.

Stackelberg games increasingly influence security policies deployed in real-world settings. Much of the work to date focuses on devising a fixed randomized strategy for the defender, accounting for an attacker who optimally responds to it. In practice, defense policies are often subject to constraints and vary over time, allowing an attacker to infer characteristics of future policies based on current observations. A defender must therefore account for an attacker's observation capabilities in devising a security policy. We show that this general modeling framework can be captured using stochastic Stackelberg games (SSGs), where a defender commits to a dynamic policy to which the attacker devises an optimal dynamic response. We then offer the following contributions. 1) We show that Markov stationary policies suffice in SSGs, 2) present a finite-time mixed-integer non-linear program for computing a Stackelberg equilibrium in SSGs, and 3) present a mixed-integer linear program to approximate it. 4) We illustrate our algorithms on a simple SSG representing an adversarial patrolling scenario, where we study the impact of attacker patience and risk aversion on optimal defense policies. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

This paper presents a counterintuitive Pre-Sprint Work Balancing methodology that has substantially increased the ability of our highly heterogeneous Scrum [1] team to deliver what it promises at the end of each sprint. The process essentially consists of preplanning steps that acknowledge both the heterogeneity in developer's time and skill level, as well as Product Owner priorities. These preplanning activities act as a starting point for negotiations with the team during the Sprint Planning Meeting. For our team, delivery of all promised tasks in a sprint has increased from less than 1/3 of our sprints to more than 2/3, with indications that we are heading towards nearly 100% delivery. © 2012 IEEE.

Tomographic spectral imaging is a powerful technique for the 3D analysis of materials. The present work describes the application of this technique to the analysis of localized corrosion of a connector pin. Implemented via serial sectioning in a focused ion-beam/scanning electron microscope, electron-excited x-ray spectra were acquired from each voxel in a 3D array. The resultant tomographic spectral image was analyzed in its entirety with Sandia's Automated eXpert Spectral Image Analysis multivariate statistical analysis software. The result of the analysis is a small number of chemical components which describe the 3D phase distribution in the volume of material sampled. © 2012 IEEE.

Assessing the impact of parameter estimation accuracy in models of heterogeneous, three-dimensional (3-D) groundwater systems is critical for predictions of solute transport. A unique experimental data set provides concentration breakthrough curves (BTCs) measured at a 0.253 cm 3 scale over the 13 × 8 × 8 cm3 domain (∼53,000 measurement locations). Advective transport is used to match the first temporal moments of BTCs (or mean arrival times, m1) averaged at 0.253 and 1.0 cm3 scales through simultaneous inversion of highly parameterized heterogeneous hydraulic conductivity (K) and porosity (φ) fields. Pilot points parameterize the fields within eight layers of the 3-D medium, and estimations are completed with six different models of the K-φ relationship. Parameter estimation through advective transport shows accurate estimation of the observed m1 values. Results across the six different K-φ relationships have statistically similar fits to the observed m1 values and similar spatial estimates of m1 along the main flow direction. The resulting fields provide the basis for forward transport modeling of the advection-dispersion equation (ADE). Using the estimated K and φ fields demonstrates that advective transport coupled with inversion using dense spatial field parameterization provides an efficient surrogate for the ADE. These results indicate that there is not a single set of model parameters, or a single K-φ relationship, that leads to a best representation of the actual experimental sand packing pattern (i.e., nonuniqueness). Additionally, knowledge of the individual sand K and values along with their arrangement in the 3-D experiment does not reproduce the observed transport results at small scales. Small-scale variation in the packing and mixing of the sands causes large deviations from the expected transport results as highlighted in forward ADE simulations. Highly parameterized inverse estimation is able to identify those regions where variations in mixing and packing alter the expected property values and significantly improve results relative to the nave application of the experimentally derived property values. Impacts of the observation scale, the scale over which results are averaged and the number of observations and parameters on the final estimations are also examined. Results indicate existence of a representative element volume (REV) at 0.25 cm3, the existence of subgrid scale heterogeneity that impacts transport and the accuracy of highly parameterized models with even relatively small amounts of observations. Finally, this work suggests that local-heterogeneity features below the REV scale are difficult to incorporate into parameterized models, highlighting the importance of addressing prediction uncertainty for small-scale variability (i.e., uncaptured variability) in modeling practice. © 2012. American Geophysical Union. All Rights Reserved.

Recent estimates of fuel consumption in construction projects are highly variable. Lack of standards for reporting at both the equipment and project levels make it difficult to quantify the magnitude of fuel consumption and the associated opportunities for efficiency improvements in construction projects. In this study, we examined clusters of Environmental Impact Reports for seemingly similar construction projects in California. We observed that construction projects are not characterized consistently by task or equipment. We found wide variations in estimates for fuel use in terms of tasks, equipment, and overall projects, which may be attributed in part to inconsistencies in methodology and parameter ranges. Our analysis suggests that standardizing fuel consumption reporting and estimation methodologies for construction projects would enable quantification of opportunities for efficiency improvements at both the equipment and project levels. With increasing emphasis on reducing fossil fuel consumption, it will be important to quantify opportunities to increase fuel efficiency, including across the construction sector. © 2012 Elsevier Ltd.

The reaction cure kinetics of a novel polyoxometalate (POM) loaded epoxy nanocomposite is described. The POM is dispersed in the epoxy resin up to volume fractions of 0.1. Differential scanning calorimetry measurements show the cure of the epoxy resin to be sensitive to the POM loading. A kinetics study of the cure exotherm confirms that POM acts as a catalyst promoting cationic homopolymerization of the epoxy resin. The cure reaction is shown to propagate through two cure regimes. A fast cure at short time is shown to be propagation by the activated chain end (ACE) mechanism. A slow cure at long time is shown to be propagation by the activated monomer (AM) mechanism. The activation energies for the fast and slow cure regimes agree well with other epoxy based systems that have been confirmed to propagate by the ACE and AM mechanisms.© 2012 Wiley Periodicals, Inc.

Stereoscopic Particle Image Velocimetry data of a trailing vortex shed from a tapered fin installed on a wind-tunnel wall have been analyzed to provide turbulent statistics. After correcting for the effects of vortex meander, the radial and azimuthal turbulent normal stresses are smallest at the vortex center, reaching a maximum around its periphery to produce an annulus of turbulence. Conversely, the streamwise turbulent stress peaks at the vortex center. The ringed turbulent structure is consistent with rotation stabilizing the flow in the vortex core, whereas a fluctuating axial velocity contributes to vortex decay. All three turbulent normal stresses decay with downstream distance. Turbulent shear stresses also decay with downstream distance but possess a relatively small magnitude, suggesting minimal coupling between turbulent velocity components. The vortex turbulence is strongly anisotropic in a manner that varies greatly with spatial position. As the vortex strength is reduced, the axial turbulent normal stress diminishes more sharply than the two cross-plane turbulent normal stresses, possibly because the latter components are influenced by external turbulence spiraling towards the vortex core. The turbulent shear stresses do not show discernable reductions in magnitude with lower vortex strength.

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Since the Polar Format Algorithm (PFA) was first introduced by Jack Walker 30 years ago, digital processing and Moore’s law have provided the means by which to process an increasing amount of data, at finer resolutions, over a larger area, and in real-time. Inherent in the polar format algorithm are assumptions that limit the focused scene size. This report presents a development of PFA for a linear frequency modulated chirp pulsed radar utilizing stretch processing to illustrate how PFA approximations are used to form an image. Also techniques to mitigate the errors resulting from the approximations are presented from a survey of literature sources. There are many techniques that are successful at increasing the focused scene size, these include image corrections made after image formation, subaperture processing, and careful selection of processing coordinates. This report only considers methods that use the polar format algorithm.

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This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandia’s Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generation of machines employing advanced network interface architectures that support enhanced offload capabilities.

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There is great interest to develop proactive methods of cyber defense, in which future attack strategies are anticipated and these insights are incorporated into defense designs; however, little has been done to place this ambitious objective on a sound scientific foundation. Indeed, even fundamental issues associated with how the “arms race” between attackers and defenders actually leads to predictability in attacker activity, or how to effectively and scalably detect this predictability in the relational/temporal data streams generated by attacker/defender adaptation, haven’t been resolved. This LDRD project addressed many of these challenges and the results are briefly summarized here. We have characterized the predictability of attacker/defender coevolution and have leveraged our findings to create a framework for designing proactive defenses for large (organizational) networks. More specifically, this project applied rigorous predictability-based analytics to two central and complementary aspects of the network defense problem – attack strategies of the adversaries and vulnerabilities of the defenders’ systems – and used the results to develop a scientifically-grounded, practically-implementable methodology for designing proactive cyber defense systems. Briefly, predictive analysis of attack strategies involved first conducting predictability assessments to characterize attacker adaptation patterns in given domains, and then used these patterns to “train” adaptive defense systems capable of providing robust performance against both current and (near) future threats. The problem of identifying and prioritizing defender system vulnerabilities was addressed using statistical and machine learning to analyze a broad range of data (e.g., cyber, social media) on recently detected system vulnerabilities to “learn” classifiers that predict how likely it is that, and how soon, new vulnerabilities will be exploited. A variety of cyber threat case studies were developed and investigated throughout the project, one selected from the cyber security research community and one that is more comprehensive and of higher priority to SNL and to external national security partners. A sample of research results and application of this methodology are included in this report (as a series of peer-reviewed publications). For ease of reference the title and SAND number are included below.

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This report describes the planning and initial development of an advanced disposal system PA modeling capability to facilitate the science-based evaluation of disposal system performance for a range of fuel cycle alternatives in a variety of geologic media and generic disposal system concepts. The advanced modeling capability will provide a PA model framework that facilitates PA model development, execution, and evaluation within a formal PA methodology. The PA model framework will provide a formalized structure that enables (a) representation and implementation of a range of generic geologic disposal system options, (b) representation of subsystem processes and couplings at varying levels of complexity in an integrated disposal system model, (c) flexible, modular representation of multi-physics processes, including the use of legacy codes, (d) evaluation of system- and subsystem-level performance, (e) uncertainty and sensitivity analyses to isolate key subsystem processes and components, (f) data and configuration management functions, and (g) implementation in HPC environments.

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Standing-edge joints made by a continuous-wave Nd:YAG laser are examined in 304L stainless steel to advance understanding of the linkage between processing and microstructure in high-rate solidification events. Microcomputed tomography combined with traditional metallography has provided qualitative and quantitative characterization of welds in this material system of broad use and applicability. Pore presence and variability have been examined three-dimensionally for average values, spatial distributions and morphology, and related to processing parameters such as weld speed, delivered power and focal lens. © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Isothermal magnetic advection (IMA) is a recently discovered method of inducing highly organized, non-contact flow lattices in suspensions of magnetic particles, using only uniform ac magnetic fields of modest strength. The initiation of these vigorous flows requires neither a thermal gradient nor a gravitational field, and so can be used to transfer heat and mass in circumstances where natural convection does not occur. These advection lattices are comprised of a square lattice of antiparallel flow columns. If the column spacing is sufficiently large compared to the column length and the flow rate within the columns is sufficiently large, then one would expect efficient transfer of both heat and mass. Otherwise, the flow lattice could act as a countercurrent heat exchanger and only mass will be efficiently transferred. Although this latter case might be useful for feeding a reaction front without extracting heat, it is likely that most interest will be focused on using IMA for heat transfer. In this paper, we explore the various experimental parameters of IMA to determine which of these can be used to control the column spacing. These parameters include the field frequency, strength, and phase relation between the two field components, the liquid viscosity, and particle volume fraction. We find that the column spacing can easily be tuned over a wide range to enable the careful control of heat and mass transfer. © 2012 American Institute of Physics.

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Within cyber security, the human element represents one of the greatest untapped opportunities for increasing the effectiveness of network defenses. However, there has been little research to understand the human dimension in cyber operations. To better understand the needs and priorities for research and development to address these issues, a workshop was conducted August 28-29, 2012 in Washington DC. A synthesis was developed that captured the key issues and associated research questions. Research and development needs were identified that fell into three parallel paths: (1) human factors analysis and scientific studies to establish foundational knowledge concerning factors underlying the performance of cyber defenders; (2) development of models that capture key processes that mediate interactions between defenders, users, adversaries and the public; and (3) development of a multi-purpose test environment for conducting controlled experiments that enables systems and human performance measurement. These research and development investments would transform cyber operations from an art to a science, enabling systems solutions to be engineered to address a range of situations. Organizations would be able to move beyond the current state where key decisions (e.g. personnel assignment) are made on a largely ad hoc basis to a state in which there exist institutionalized processes for assuring the right people are doing the right jobs in the right way. These developments lay the groundwork for emergence of a professional class of cyber defenders with defined roles and career progressions, with higher levels of personnel commitment and retention. Finally, the operational impact would be evident in improved performance, accompanied by a shift to a more proactive response in which defenders have the capacity to exert greater control over the cyber battlespace.

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