Publications

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This report provides the DOE and industry with a general process for analyzing power electronics reliability. The analysis can help with understanding the main causes of failures, downtime, and cost and how to reduce them. One approach is to collect field maintenance data and use it directly to calculate reliability metrics related to each cause. Another approach is to model the functional structure of the equipment using a fault tree to derive system reliability from component reliability. Analysis of a fictitious device demonstrates the latter process. Optimization can use the resulting baseline model to decide how to improve reliability and/or lower costs. It is recommended that both electric utilities and equipment manufacturers make provisions to collect and share data in order to lay the groundwork for improving reliability into the future. Reliability analysis helps guide reliability improvements in hardware and software technology including condition monitoring and prognostics and health management.

Laser-induced incandescence measurements have recently been obtained from 10% and 30% toluene in methanol blended fuel pool fires of 2-m diameter. Calibration of the instrument was performed using an ethylene/air laminar diffusion flame produced by a Santoro-type burner which allowed the extraction of absolute soot-volume-fractions from these images. Performance of the optical probe was characterized using the laminar diffusion flame and corrections were implemented for signal dependence upon detector gain, flat field, and location within the probe laser sheet when processing the images. Probability density functions of the soot-volume fraction were constructed for the blended fuels used in this study and the mean values were determined to be 0.0077 and 0.028 ppm for the 10% and 30% blended fuels, respectively. Signal trapping was estimated for the two types of blended fuel and it was determined to be negligible for the 10% toluene/methanol blend and require {approx}10% correction for the 30% toluene/methanol blend.

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As FPGA logic density continues to increase, new techniques are needed to store initial configuration data efficiently, maintain usability, and minimize cost. In this paper, a novel compression technique is presented for Xilinx Virtex partially reconfigurable FPGAs. This technique relies on constrained hardware design and layout combined with a few simple compression techniques. This technique uses partial recon-figuration to separate a hardware design into two separate regions: a static and partial region. A bitstream containing only the static region is then compressed by removing empty frames. This bitstream will be stored in non-volatile memory and used for initialization. The remaining logic is configured through partial reconfiguration over a communication network. By applying this technique, a high level of compression was achieved (almost 90% for the V4 LX25). This compression technique requires no extra decompression circuitry and compression levels improve as device size increases. ©2009 IEEE.

Thermal transport across one-dimensional atomic chains is studied using a harmonic nonequilibrium Green's function formalism in the ballistic phonon transport regime. Introducing a mass impurity in the chain and mass loading in the thermal contacts leads to interference of phonon waves, which can be manipulated by varying the magnitude of the loading. This shows that thermal rectification is tunable in a completely harmonic system. © 2009 The American Physical Society.

An improved theoretical approach is presented to calculate and predict the quality factors of flexible microeantilevers affected by squeeze-film damping at low ambient pressures, and moderate to high Knudsen numbers. Veijola's model [1]. originally derived for a rigid oscillating plate near a wall, is extended to a flexible cantilever beam and both the gas inertia effect and slip boundary condition are considered in deriving resulting damping pressure. The model is used to predict the natural frequencies and quality factors of silicon microeantilevers with small gaps and their dependence on ambient pressure. In contrast to non-slip, continuum models, we find that quality factor depends strongly on ambient pressure, and that the damping of higher modes is more sensitive to ambient pressure than the fundamental. Copyright © 2008 by ASME.

This paper presents a novel micro-scale passive-latching mechanical shock sensor with reset capability. The device integrates a compliant bistable mechanism, designed to have a high contact force and low actuation force, with metal-to-metal electrical contacts that provide a means for interrogating the switch state. No electrical power is required during storage or sensing. Electrical power is only required to initialize, reset, self-test, or interrogate the device, allowing the mechanism to be used in low-power and long shelf-life applications. The sensor has a footprint of about 1 mm2, allowing multiple devices to be integrated on a single chip for arrays of acceleration thresholds, redundancy, and/or multiple sense directions. Modeling and experimental results for a few devices with different thresholds in the 100g to 400g range are given. Centrifuge test results show that the accelerations required to toggle the switches are higher than current model predictions. Resonant frequency measurements suggest that the springs may be stiffer than predicted. Hammer-strike tests demonstrate the feasibility of using the devices as sensors for actual mechanical shock events. Copyright © 2008 by ASME.

This paper presents Sandia National Laboratories' Out-door Weapons of Mass Destruction Decision Analysis Center (Out-DAC) and, through an example case study, derives lessons for its use. This tool, related to similar capabilities at Sandia, can be used to determine functional requirements for a detection system of aerosol-released threats outdoors. Essential components of OutDAC are a population database, a meteorological dataset, an atmospheric transport and dispersion model and an optimization toolkit. Detector placement is done through optimization against a library of hypothe-sized attack scenarios by minimizing either the mean or value-at-risk of undetected infections. These scenarios are the product of a Monte Carlo simulation intended to characterize the uncertainty associated with the threat. An example case study illustrates that Monte Carlo convergence is dependent on the statistic of interest. Furthermore, the quality of the detector placement optimization may be tied to the convergence level of the Monte Carlo simulation. © 2009 IEEE.

This report summarizes the Combinatorial Algebraic Topology: software, applications & algorithms workshop (CAT Workshop). The workshop was sponsored by the Computer Science Research Institute of Sandia National Laboratories. It was organized by CSRI staff members Scott Mitchell and Shawn Martin. It was held in Santa Fe, New Mexico, August 29-30. The CAT Workshop website has links to some of the talk slides and other information, http://www.cs.sandia.gov/CSRI/Workshops/2009/CAT/index.html. The purpose of the report is to summarize the discussions and recap the sessions. There is a special emphasis on technical areas that are ripe for further exploration, and the plans for follow-up amongst the workshop participants. The intended audiences are the workshop participants, other researchers in the area, and the workshop sponsors.

Fibers doped with rare-earth constituents such as Yb3+ and Er3+, as well as fibers co-doped with these species, form an essential part of many optical systems requiring amplification. This study consists of two separate investigations examining the effects of gamma-radiation-induced photodarkening on the behavior of rare-earth doped fibers. In one part of this study, a suite of previously irradiated rare-earth doped fibers was heated to an elevated temperature of 300°C and the transmittance monitored over an 8-hour period. Transmittance recoveries of ~10 - 20% were found for Er3+- doped fiber, while recoveries of ~5 - 15% and ~20% were found for Yb3+- and Yb3+/Er3+ co-doped fibers, respectively. In the other part of this study, an Yb3+-doped fiber was actively pumped by a laser diode during a gamma-radiation exposure to simulate the operation of an optical amplifier in a radiation environment. The response of the amplified signal was observed and monitored over time. A significant decrease in amplifier output was observed to result from the gamma-radiation exposure. © 2009 SPIE.

The potential for aging effects in silicon electronics is a concern for systems with prolonged service lives that contain electronics that must function in extreme radiation environments. A set of laserbased diagnostic techniques is described that is used to provide ongoing awareness of changes in the radiation response of aging discrete and integrated circuits. ©2009 IEEE.

A new class of microphotonic-resonators, Adiabatic Resonant Microrings (ARMs), is introduced. The ARM resonator geometry enables heater elements to be formed within the resonator, simultaneously enabling record low-power (4.4μW/GHz) and record high-speed (1μs) thermal tuning. ©2009 Optical Society of America.

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An electromagnetic analysis is performed on different first wall designs for the ITER device. The electromagnetic forces and torques present due to a plasma disruption event are calculated and compared for the different designs.

An electromagnetic analysis is performed on the ITER shield modules under different plasma disruption scenarios using the OPERA-3d software. The modeling procedure is explained, electromagnetic torques are presented, and results of the modeling are discussed.

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Three hundred-plus years of successful theoretical development and application of probability theory provide sufficient justification for it as the mathematical context in which to analyze the uncertainty in the performance of engineering and scientific systems. In this document, we propose a joint probabilistic and deterministic function analytic approach as the means for the development of advanced techniques that feature a strong connection between classical deterministic and probabilistic methods. We know of no other means to achieve simultaneous, balanced approximations across these two constituents. We present foundational materials on the general approach to particular aspects of functional analysis, which are relevant to probability, and emphasize the common elements it shares, and the close connections it provides, to various classical deterministic mathematical analysis elements. Finally, we describe how to use the joint approach as a means to augment deterministic analysis methods in a particular Hilbert space context, and thus enable a rigorous framework for commingling deterministic and probabilistic analysis tools in an application setting. © 2009 John Wiley & Sons, Ltd.

Terrorist acts are intentional and therefore differ significantly from "dumb" random acts that are the subject of most risk analyses. There is significant epistemic (state of knowledge) uncertainty associated with such intentional acts, especially for the likelihood of specific attack scenarios. Also, many of the variables of concern are not numeric and should be treated as purely linguistic (words). Epistemic uncertainty can be addressed using the belief/plausibility measure of uncertainty, an extension of the traditional probability measure of uncertainty. Fuzzy sets can be used to segregate a variable into purely linguistic values. Linguistic variables can be combined using an approximate reasoning rule base to map combinations of fuzzy sets of the constituent variables to fuzzy sets of the resultant variable. We have implemented the mathematics of fuzzy sets, approximate reasoning, and belief/plausibility into Java software tools. The PoolEvidence© software tool combines evidence (pools) from different experts. The LinguisticBelief© software tool evaluates the risk associated with scenarios of concern using the pooled evidence as input. The tools are not limited to the evaluation of terrorist risk; they are useful for evaluating any decision involving significant epistemic uncertainty and linguistic variables. Sandia National Laboratories' analysts have applied the tools to: risk of terrorist acts, security of nuclear materials, cyber security, prediction of movements of plumes of hazardous materials, and issues with nuclear weapons. This paper focuses on evaluating the risk of acts of terrorism. ©2009 IEEE.

Optimization for complex systems in engineering often involves the use of expensive computer simulation. By combining statistical emulation using treed Gaussian processes with pattern search optimization, we are able to perform robust local optimization more efficiently and effectively than when using either method alone. Our approach is based on the augmentation of local search patterns with location sets generated through improvement prediction over the input space.We further develop a computational framework for asynchronous parallel implementation of the optimization algorithm. We demonstrate our methods on two standard test problems and our motivating example of calibrating a circuit device simulator. © 2009 American Statistical Association.

We have performed molecular dynamics simulations of cascade damage in the gadolinium pyrochlore Gd{sub 2}Zr{sub 2}O{sub 7}, comparing results obtained from traditional methodologies that ignore the effect of electron-ion interactions with a 'two-temperature model' in which the electronic subsystem is modeled using a diffusion equation to determine the electronic temperature. We find that the electron-ion interaction friction coefficient {gamma}{sub p} is a significant parameter in determining the behavior of the system following the formation of the primary knock-on atom (here, a U{sup 3+} ion). The mean final U{sup 3+} displacement and the number of defect atoms formed is shown to decrease uniformly with increasing {gamma}{sub p}; however, other properties, such as the final equilibrium temperature and the oxygen-oxygen radial distribution function show a more complicated dependence on {gamma}{sub p}.

This report documents progress in discovering new catalytic technologies that will support the development of advanced biofuels. The global shift from petroleum-based fuels to advanced biofuels will require transformational breakthroughs in biomass deconstruction technologies, because current methods are neither cost effective nor sufficiently efficient or robust for scaleable production. Discovery and characterization of lignocellulolytic enzyme systems adapted to extreme environments will accelerate progress. Obvious extreme environments to mine for novel lignocellulolytic deconstruction technologies include aridland ecosystems (ALEs), such as those of the Sevilleta Long Term Ecological Research (LTER) site in central New Mexico (NM). ALEs represent at least 40% of the terrestrial biosphere and are classic extreme environments, with low nutrient availability, high ultraviolet radiation flux, limited and erratic precipitation, and extreme variation in temperatures. ALEs are functionally distinct from temperate environments in many respects; one salient distinction is that ALEs do not accumulate soil organic carbon (SOC), in marked contrast to temperate settings, which typically have large pools of SOC. Low productivity ALEs do not accumulate carbon (C) primarily because of extraordinarily efficient extracellular enzyme activities (EEAs) that are derived from underlying communities of diverse, largely uncharacterized microbes. Such efficient enzyme activities presumably reflect adaptation to this low productivity ecosystem, with the result that all available organic nutrients are assimilated rapidly. These communities are dominated by ascomycetous fungi, both in terms of abundance and contribution to ecosystem-scale metabolic processes, such as nitrogen and C cycling. To deliver novel, robust, efficient lignocellulolytic enzyme systems that will drive transformational advances in biomass deconstruction, we have: (1) secured an award through the Department of Energy (DoE) Joint Genome Institute (JGI) to perform metatranscriptomic functional profiling of eukaryotic microbial communities of blue grama grass (Bouteloua gracilis) rhizosphere (RHZ) soils and (2) isolated and provided initial genotypic and phenotypic characterization data for thermophilic fungi. Our preliminary results show that many strains in our collection of thermophilic fungi frequently outperform industry standards in key assays; we also demonstrated that this collection is taxonomically diverse and phenotypically compelling. The studies summarized here are being performed in collaboration with University of New Mexico and are based at the Sevilleta LTER research site.